Illegal killing of nongame wildlife is a global yet poorly documented problem. The prevalence and ecological consequences of illegal killing are often underestimated or completely unknown. We review the practice of legal recreational shooting and present data gathered from telemetry, surveys, and observations on its association with illegal killing of wildlife (birds and snakes) within conservation areas in Idaho, USA. In total, 33% of telemetered long‐billed curlews (Numenius americanus) and 59% of other bird carcasses found with known cause of death (or 32% of total) were illegally shot. Analysis of spatial distributions of illegal and legal shooting is consistent with birds being shot illegally in the course of otherwise legal recreational shooting, but snakes being intentionally sought out and targeted elsewhere, in locations where they congregate. Preliminary public surveys indicate that most recreational shooters find abhorrent the practice of illegal killing of wildlife. Viewed through this lens, our data may imply only a small fraction of recreational shooters is responsible for this activity. This study highlights a poorly known conservation problem that could have broad implications for some species and populations of wildlife.
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Physical and economic data about water in many nations are becoming more widely integrated through application of the System of Environmental-Economic Accounts for Water (SEEA-Water), which enables the tracking of linkages between water and the economy. We present the first national and subnational SEEA-Water accounts for the United States. We compile accounts for water: (1) physical supply and use, (2) productivity, (3) quality, and (4) emissions for roughly the years 2000 to 2015. Total U.S. water use declined by 22% from 2000 to 2015, falling in 44 states though groundwater use increased in 21 states. Water-use reductions, combined with economic growth, led to increases in water productivity for the overall national economy (65%), mining (99%), and agriculture (68%). Surface-water quality trends were most evident at regional levels, and differed by water-quality constituent and region. This work provides (1) a baseline of recent historical water resource trends and their value in the U.S., and (2) a roadmap for the completion of future accounts for water, a critical ecosystem service. Our work also aids in the interpretation of ecosystem accounts in the context of long-term water resources trends.
heir value in the U.S., and (2) a roadmap for the completion of future accounts for water, a critical ecosystem service. Our work also aids in the interpretation of ecosystem accounts in the context of long-term water resources trends.
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kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":800450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ancona, Zachary H. 0000-0001-5430-0218 zancona@usgs.gov","orcid":"https://orcid.org/0000-0001-5430-0218","contributorId":5578,"corporation":false,"usgs":true,"family":"Ancona","given":"Zachary","email":"zancona@usgs.gov","middleInitial":"H.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":800451,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hass, Julie L.","contributorId":211867,"corporation":false,"usgs":false,"family":"Hass","given":"Julie","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":800452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glynn, Pierre D. 0000-0001-8804-7003 pglynn@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7003","contributorId":2141,"corporation":false,"usgs":true,"family":"Glynn","given":"Pierre","email":"pglynn@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":800453,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wentland, Scott","contributorId":211876,"corporation":false,"usgs":false,"family":"Wentland","given":"Scott","affiliations":[{"id":38340,"text":"Bureau of Economic Analysis","active":true,"usgs":false}],"preferred":false,"id":800454,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vardon, Michael","contributorId":211875,"corporation":false,"usgs":false,"family":"Vardon","given":"Michael","email":"","affiliations":[{"id":16807,"text":"Australian National University","active":true,"usgs":false}],"preferred":false,"id":800455,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fay, John P.","contributorId":207571,"corporation":false,"usgs":false,"family":"Fay","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":800456,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70214980,"text":"70214980 - 2020 - Predicting bird guilds using vegetation composition and structure on a wild and scenic river in Arizona","interactions":[],"lastModifiedDate":"2020-12-29T21:37:34.223766","indexId":"70214980","displayToPublicDate":"2020-09-25T09:03:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Predicting bird guilds using vegetation composition and structure on a wild and scenic river in Arizona","docAbstract":"Riparian areas are among the most ecologically diverse terrestrial ecosystems but make up <2% of landscape area in southwestern USA. Many species of resident and neotropical migratory birds utilize riparian habitats for breeding, foraging, and nesting. We quantified vegetation composition and structure to predict bird guilds on Wild and Scenic portions of the Verde River, Arizona. We grouped plant species into guilds based on similar functional traits to describe composition. We surveyed birds during the breeding and migrating season to determine abundance and categorized species into guilds using preferences of breeding habitat, foraging substrate, and nest placement. Riparian obligate and facultative breeding guilds were most common. Both vegetation composition and structure were useful predictors of birds. Vegetation structure was most complex in gallery riparian forest. Abundance of riparian-obligate birds in the breeding guild were positively associated with vegetation structure of dense, multi-canopy canopy and tall trees. Abundance of most bird guilds were positively associated with composition of tall trees (Populus fremontii, Salix gooddingii) and drought tolerant shrubs (Prosopis velutina, Celtis reticulata). Our findings show complex riparian habitat important to wildlife is created by both composition and structure of near-stream vegetation that is tied to hydrology and sensitive to flow change.
Spanning Canada, the United States, and Mexico, North America contains two populations of the migratory monarch butterfly (Danaus plexippus). The smaller “western” population overwinters in groves along the California coast and breeds west of the Rocky Mountains, while the much larger “eastern” population breeds east of the Rocky Mountains and overwinters in Oyamel fir forests in central Mexico. Both populations have declined in the last 20 to 30 years, leading to a formal petition in 2014 to list the species as threatened or endangered under the US Endangered Species Act (ESA) and a recommendation in 2016 for listing as endangered under the Canadian Species at Risk act.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2020.576281","usgsCitation":"Diffendorfer, J., Thogmartin, W.E., Drum, R.G., and Schultz, C.B., 2020, Editorial: North American monarch butterfly ecology and conservation: Frontiers in Ecology and Conservation, v. 8, 576281, 4 p., https://doi.org/10.3389/fevo.2020.576281.","productDescription":"576281, 4 p.","ipdsId":"IP-118385","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":455223,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2020.576281","text":"Publisher Index Page"},{"id":403469,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United 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Maria L.","contributorId":292974,"corporation":false,"usgs":false,"family":"Pappas","given":"Maria","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":846363,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":846331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":846332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drum, Ryan G.","contributorId":171941,"corporation":false,"usgs":false,"family":"Drum","given":"Ryan","email":"","middleInitial":"G.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":846333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schultz, Cheryl B. 0000-0003-3388-8950","orcid":"https://orcid.org/0000-0003-3388-8950","contributorId":292946,"corporation":false,"usgs":false,"family":"Schultz","given":"Cheryl","middleInitial":"B.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":846334,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216488,"text":"70216488 - 2020 - Sea‐level rise will drive divergent sediment transport patterns on fore reefs and reef flats, potentially causing erosion on atoll islands","interactions":[],"lastModifiedDate":"2020-11-23T14:12:16.975375","indexId":"70216488","displayToPublicDate":"2020-09-25T07:58:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7358,"text":"Journal of Geophysical Research – Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Sea‐level rise will drive divergent sediment transport patterns on fore reefs and reef flats, potentially causing erosion on atoll islands","docAbstract":"Atoll reef islands primarily consist of unconsolidated sediment, and their ocean‐facing shorelines are maintained by sediment produced and transported across their reefs. Changes in incident waves can alter cross‐shore sediment exchange and, thus, affect the sediment budget and morphology of atoll reef islands. Here we investigate the influence of sea level rise and projected wave climate change on wave characteristics and cross‐shore sediment transport across an atoll reef at Kwajalein Island, Republic of the Marshall Islands. Using a phase‐resolving model, we quantify the influence on sediment transport of quantities not well captured by wave‐averaged models, namely, wave asymmetry and skewness and flow acceleration. Model results suggest that for current reef geometry, sea level, and wave climate, potential bedload transport is directed onshore, decreases from the fore reef to the beach, and is sensitive to the influence of flow acceleration. We find that a projected 12% decrease in annual wave energy by 2100 CE has negligible influence on reef flat hydrodynamics. However, 0.5–2.0 m of sea level rise increases wave heights, skewness, and shear stress on the reef flat and decreases wave skewness and shear stress on the fore reef. These hydrodynamic changes decrease potential sediment inputs onshore from the fore reef where coral production is greatest but increase potential cross‐reef sediment transport from the outer reef flat to the beach. Assuming sediment production on the fore reef remains constant or decreases due to increasing ocean temperatures and acidification, these processes have the potential to decrease net sediment delivery to atoll islands, causing erosion.
Stream fish survival and recruitment are products of a physicochemical environment that affects growth and provides refuge; yet, the drivers of spatiotemporal variation in juvenile fish abundance remain unclear. Understanding how physicochemical conditions drive spatial and temporal patterns in fish abundances provides insight into how conditions across stream networks influence fish population success, thereby providing direction to managers about the types and locations of conservation actions that would be most beneficial. Using snorkel and habitat surveys of 120 sites sampled from 2015 to 2017, we evaluated the multiscale relationships among physicochemical features, hydrology, and age-0 Smallmouth Bass (Micropterus dolomieu velox) abundance in relation to network spatial position. Abundance of age-0 bass was spatiotemporally variable in relation to a July streamflow–network position interaction, a pool depth–stream size interaction, and a stream temperature–network position interaction. High flows at the end of the nesting season were related to lower age-0 abundance, but this effect was dampened in stream reaches in close proximity to larger mainstems. In small streams, reaches with deeper pool habitat supported higher age-0 bass abundances, but this trend was not apparent in larger tributaries and mainstem systems. Generally, colder streams had lower age-0 Smallmouth Bass abundance, though this relationship was not apparent in reaches adjacent to larger streams that generally supported higher age-0 bass abundances. Conservation actions that (1) facilitate habitat connectivity within and among streams, (2) limit future anthropogenic practices that alter natural geomorphology by creating shallower stream channels, and (3) maintain adequate flow magnitude and timing to support channel complexity (e.g., deeper pools within smaller catchments) would be most beneficial to supporting rearing habitat for age-0 riverine Smallmouth Bass.
Sequoia Scientific’s LISST-ABS is a submersible acoustic instrument that measures the acoustic backscatter sensor (ABS) concentration at a point within a river, stream, or creek. Compared to traditional physical methods for measuring suspended-sediment concentration (SSC), sediment surrogates like the LISST-ABS offer continuous data that can be calibrated with physical SSC samples. Data were collected at 10 U.S. Geological Survey streamflow-gaging stations between January 10, 2016, and February 21, 2018, across the contiguous United States to test the accuracy and effectiveness of using the LISST-ABS as a surrogate for measuring the concentration of suspended sediment in a dynamic fluvial system. Correlation coefficients (Pearson’s r values) relating the ABS concentration and SSC from physical samples ranged from r = 0.718 to r = 0.956 at the 10 stations with the mean percentage of fines (percentage of the sediment less than 62.5 microns in diameter) ranging from 65 to 100 percent (with minimum and maximum values of 18 and 100 percent, respectively). The LISST-ABS instruments used in this field evaluation were factory-calibrated to accurately determine SSC for grains in the diameter range of 75–90 microns. Note that the sensor responds to grains of arbitrary sizes, but the accuracy varies at sizes other than this calibration size. For operational use, regression models could be determined for the ABS concentrations and SSC values or the instrument could be recalibrated to sediments for each fluvial environment. However, such calibrations were beyond the scope of this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201096","collaboration":"Federal Interagency Sedimentation Project and Observing Systems Division","usgsCitation":"Manaster, A.E., Straub, T.D., Wood, M.S., Bell, J.M., Dombroski, D.E., and Curran, C.A., 2020, Field evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor: U.S. Geological Survey Open-File Report 2020–1096, 26 p., https://doi.org/10.3133/ofr20201096.","productDescription":"Report: v, 26 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-116096","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":378643,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1096/coverthb.jpg"},{"id":378644,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1096/ofr20201096.pdf","text":"Report","size":"3.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1096"},{"id":378645,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LROJE4","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data for field evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor"}],"contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
The key to Nelson’s Sparrow (Ammospiza nelsoni nelsoni) management is providing dense grasses or emergent vegetation near damp areas or freshwater wetlands. Nelson’s Sparrows have been reported to use habitats with 20–122 centimeters (cm) average vegetation height, 41 cm visual obstruction reading, 40–58 percent grass cover, 24 percent forb cover, 5 percent shrub cover, 13 percent bare ground, and 2–7 cm litter depth.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842KK","usgsCitation":"Shaffer, J.A., Igl, L.D., Johnson, D.H., Sondreal, M.L., Goldade, C.M., Rabie, P.A., and Euliss, B.R., 2020, The effects of management practices on grassland birds—Nelson’s Sparrow (Ammospiza nelsoni nelsoni), chap. KK of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 10 p., https://doi.org/10.3133/pp1842KK.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095138","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":378704,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/kk/coverthb.jpg"},{"id":378705,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/kk/pp1842kk.pdf","text":"Report","size":"2.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–KK"}],"contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Migration is a period of high activity and exposure during which risks and energetic demand on individuals may be greater than during nonmigratory periods. Stopover locations can help mitigate these threats by providing supplemental energy en route to the animal’s end destination. Effective conservation of migratory species therefore requires an understanding of use of space that provides resources to migratory animals at stopover sites. We conducted a radio-telemetry study of a short-distance migrant, the American Woodcock (Scolopax minor), at an important stopover site, the Cape May Peninsula, New Jersey. Our objectives were to describe land-cover types used by American Woodcock and evaluate home range habitat selection for individuals that stopover during fall migration and those that choose to overwinter. We radio-marked 271 individuals and collected 1,949 locations from these birds (0–21 points individual–1) over 4 yr (2010 to 2013) to inform resource selection functions of land-cover types and other landscape characteristics by this species. We evaluated these relationships at multiple spatial extents for (1) birds known to have ultimately left the peninsula (presumed migrants), and (2) birds known to have remained on the peninsula into the winter (presumed winter residents). We found that migrants selected deciduous wetland forest, agriculture, mixed shrub, coniferous wetland forest, and coniferous shrub, while wintering residents selected deciduous wetland forest, coniferous shrub, and deciduous shrub. We used these results to develop predictive models of potential habitat: 7.80% of the peninsula was predicted to be potential stopover habitat for American Woodcock (95% classification accuracy) and 4.96% of the peninsula was predicted to be potential wintering habitat (85% classification accuracy). Our study is the first to report habitat relationships for migratory American Woodcock in the coastal U.S. and provides important spatial tools for local and regional managers to support migratory and winter resident woodcock populations into the future.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duaa046","usgsCitation":"Allen, B.L., McAuley, D., and Blomberg, E.J., 2020, Migratory status determines resource selection by American Woodcock at an important fall stopover, Cape May, New Jersey: The Condor, duaa046, 16 p., https://doi.org/10.1093/condor/duaa046.","productDescription":"duaa046, 16 p.","ipdsId":"IP-092164","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":436781,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7R49PZ2","text":"USGS data release","linkHelpText":"Multiscale resource selection by American Woodcock (Scolopax minor) during fall migration at Cape May, New Jersey"},{"id":379018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Cape May","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.6024169921875,\n 38.852542390364235\n ],\n [\n -74.06982421875,\n 38.852542390364235\n ],\n [\n -74.06982421875,\n 39.51675478434244\n ],\n [\n -75.6024169921875,\n 39.51675478434244\n ],\n [\n -75.6024169921875,\n 38.852542390364235\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2020-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Brian L.","contributorId":171560,"corporation":false,"usgs":false,"family":"Allen","given":"Brian","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":800447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAuley, Daniel 0000-0003-3674-6392 dmcauley@usgs.gov","orcid":"https://orcid.org/0000-0003-3674-6392","contributorId":215182,"corporation":false,"usgs":true,"family":"McAuley","given":"Daniel","email":"dmcauley@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":800448,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blomberg, Erik J.","contributorId":17543,"corporation":false,"usgs":false,"family":"Blomberg","given":"Erik","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":800449,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215097,"text":"70215097 - 2020 - Why did Great Basin Eocene magmatism generate Carlin-type gold deposits when extensive Jurassic to Middle Miocene magmatism did not? Lessons from the Cortez Region, Northern Nevada, USA","interactions":[],"lastModifiedDate":"2020-10-08T14:06:42.685909","indexId":"70215097","displayToPublicDate":"2020-09-24T09:03:04","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Why did Great Basin Eocene magmatism generate Carlin-type gold deposits when extensive Jurassic to Middle Miocene magmatism did not? Lessons from the Cortez Region, Northern Nevada, USA","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Vision for discovery: Geological Society of Nevada symposium proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"8th Symposium of Geological Society of Nevada","conferenceDate":"May 14-24, 2020","conferenceLocation":"Reno/Lake Tahoe, NV","language":"English","publisher":"Geological Society of Nevada","usgsCitation":"Henry, C., John, D.A., Heizler, M.T., Leonardson, R.W., Colgan, J.P., Watts, K., Ressel, M.W., and Cousens, B.L., 2020, Why did Great Basin Eocene magmatism generate Carlin-type gold deposits when extensive Jurassic to Middle Miocene magmatism did not? Lessons from the Cortez Region, Northern Nevada, USA, in Vision for discovery: Geological Society of Nevada symposium proceedings, Reno/Lake Tahoe, NV, May 14-24, 2020.","ipdsId":"IP-115532","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":379229,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Cortez region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.6143798828125,\n 40.11588965267845\n ],\n [\n -115.87829589843751,\n 40.11588965267845\n ],\n [\n -115.87829589843751,\n 40.67647212850004\n ],\n [\n -116.6143798828125,\n 40.67647212850004\n ],\n [\n -116.6143798828125,\n 40.11588965267845\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Henry, Christopher D.","contributorId":175501,"corporation":false,"usgs":false,"family":"Henry","given":"Christopher D.","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":800831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":800832,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heizler, Matt T. 0000-0002-3911-4932","orcid":"https://orcid.org/0000-0002-3911-4932","contributorId":229568,"corporation":false,"usgs":false,"family":"Heizler","given":"Matt","email":"","middleInitial":"T.","affiliations":[{"id":41669,"text":"New Mexico Bureau of Geology and Mineral Resources, New Mexico Tech","active":true,"usgs":false}],"preferred":false,"id":800833,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leonardson, Robert W.","contributorId":242799,"corporation":false,"usgs":false,"family":"Leonardson","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":800834,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colgan, Joseph P. 0000-0001-6671-1436 jcolgan@usgs.gov","orcid":"https://orcid.org/0000-0001-6671-1436","contributorId":1649,"corporation":false,"usgs":true,"family":"Colgan","given":"Joseph","email":"jcolgan@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":800835,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":800836,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ressel, Michael W.","contributorId":242800,"corporation":false,"usgs":false,"family":"Ressel","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":800837,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cousens, Brian L. 0000-0002-9704-6974","orcid":"https://orcid.org/0000-0002-9704-6974","contributorId":242801,"corporation":false,"usgs":false,"family":"Cousens","given":"Brian","email":"","middleInitial":"L.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":800838,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70214091,"text":"sim3461 - 2020 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","interactions":[{"subject":{"id":70214091,"text":"sim3461 - 2020 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","indexId":"sim3461","publicationYear":"2020","noYear":false,"displayTitle":"Geologic Framework and Hydrostratigraphy of the Edwards and Trinity Aquifers Within Northern Medina County, Texas","title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas"},"predicate":"SUPERSEDED_BY","object":{"id":70258397,"text":"sim3526 - 2024 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","indexId":"sim3526","publicationYear":"2024","noYear":false,"title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas"},"id":1}],"supersededBy":{"id":70258397,"text":"sim3526 - 2024 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","indexId":"sim3526","publicationYear":"2024","noYear":false,"title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas"},"lastModifiedDate":"2024-09-20T17:56:40.050301","indexId":"sim3461","displayToPublicDate":"2020-09-24T08:37:02","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3461","displayTitle":"Geologic Framework and Hydrostratigraphy of the Edwards and Trinity Aquifers Within Northern Medina County, Texas","title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","docAbstract":"The karstic Edwards and Trinity aquifers are classified as major sources of water in south-central Texas by the Texas Water Development Board. During 2018–20 the U.S. Geological Survey, in cooperation with the Edwards Aquifer Authority, mapped and described the geologic framework and hydrostratigraphy of the rocks composing the Edwards and Trinity aquifers in northern Medina County from field observations of the surficial expressions of the rocks. The thicknesses of the mapped lithostratigraphic members and hydrostratigraphic units were also estimated from field observations.
The Cretaceous-age rocks (listed in ascending order) in the study area are part of the Trinity Group (lower and upper members of the Glen Rose Limestone), Edwards Group (Kainer Formation [and its stratigraphic equivalent, the Fort Terrett Formation] and Person Formation), Devils River Limestone, Washita Group (Georgetown Formation, Del Rio Clay, and Buda Limestone), Eagle Ford Group, Austin Group, Taylor Group, and Late Cretaceous igneous intrusive rocks. The groups and formations are composed primarily of relatively thick layers of clays, shales, and limestone. The igneous rocks are coarse-grained ultramafic in composition.
The principal structural feature in northern Medina County is the Balcones fault zone, which is the result of late Oligocene and early Miocene extensional faulting and fracturing resulting from the eastern Edwards Plateau uplift. In the Balcones fault zone, most of the faults in the study area are high-angle to vertical, en echelon, normal faults that are predominately downthrown to the southeast.
Hydrostratigraphically, the rocks exposed in the study area (listed in descending order from land surface as they appear in a stratigraphic column) are igneous, the upper confining unit to the Edwards aquifer, the Edwards aquifer, the upper zone of the Trinity aquifer, and the upper part of the middle zone of the Trinity aquifer. The karstic carbonate Edwards and Trinity aquifers developed as a result of their original depositional history, primary and secondary porosity, diagenesis, fracturing, and faulting. These factors have resulted in development of modified porosity, permeability, and transmissivity within and between the aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3461","collaboration":"Prepared in cooperation with the Edwards Aquifer Authority","usgsCitation":"Clark, A.K., Morris, R.E., and Pedraza, D.E., 2020, Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas: U.S. Geological Survey Scientific Investigations Map 3461, 13 p. pamphlet, 1 pl., scale 1:24,000, https://doi.org/10.3133/sim3461.","productDescription":"Report: vi, 13 p.; Sheet: 48 inches x 36 inches; Data Release","numberOfPages":"23","onlineOnly":"N","ipdsId":"IP-112816","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":378661,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HHMBX8","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial dataset of the geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas, at 1:24,000 scale"},{"id":378659,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3461/sim3461_pamphlet.pdf","text":"Pamphlet","size":"1.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3461 Pamphlet"},{"id":378658,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3461/coverthb1.jpg"},{"id":378660,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3461/sim3461.pdf","text":"Map sheet","size":"30.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3461"}],"country":"United States","state":"Texas","county":"Medina County","otherGeospatial":"Edwards and Trinity Aquifers","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.46609497070312,\n 29.31514119318728\n ],\n [\n -98.79867553710936,\n 29.31514119318728\n ],\n [\n -98.79867553710936,\n 29.6510621496229\n ],\n [\n -99.46609497070312,\n 29.6510621496229\n ],\n [\n -99.46609497070312,\n 29.31514119318728\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Die-offs of seabirds in Alaska have occurred with increased frequency since 2015. In 2018, on St. Lawrence Island, seabirds were reported washing up dead on beaches starting in late May, peaking in June, and continuing until early August. The cause of death was documented to be starvation, leading to the conclusion that a severe food shortage was to blame. We use physiology and colony-based observations to examine whether food shortage is a sufficient explanation for the die-off, or if evidence indicates an alternative cause of starvation such as disease. Specifically, we address what species were most affected, the timing of possible food shortages, and food shortage severity in a historical context. We found that thick-billed murres (Uria lomvia) were most affected by the die-off, making up 61% of all bird carcasses encountered during beach surveys. Thick-billed murre carcasses were proportionately more numerous (26:1) than would be expected based on ratios of thick-billed murres to co-occurring common murres (U. aalge) observed on breeding study plots (7:1). Concentrations of the stress hormone corticosterone, a reliable physiological indicator of nutritional stress, in thick-billed murre feathers grown in the fall indicate that foraging conditions in the northern Bering Sea were poor in the fall of 2017 and comparable in severity to those experienced by murres during the 1976–1977 Bering Sea regime shift. Concentrations of corticosterone in feathers grown during the pre-breeding molt indicate that foraging conditions in late winter 2018 were similar to previous years. The 2018 murre egg harvest in the village of Savoonga (on St. Lawrence Is.) was one-fifth the 1993–2012 average, and residents observed that fewer birds laid eggs in 2018. Exposure of thick-billed murres to nutritional stress in August, however, was no different in 2018 compared to 2016, 2017, and 2019, and was comparable to levels observed on St. George Island in 2003–2017. Prey abundance, measured by the National Oceanic and Atmospheric Administration in bottom-trawl surveys, was also similar in 2018 to 2017 and 2019, supporting the evidence that food was not scarce in the summer of 2018 in the vicinity of St. Lawrence Island. Of two moribund thick-billed murres collected at the end of the mortality event, one tested positive for a novel re-assortment H10 strain of avian influenza with Eurasian components, likely contracted during the non-breeding season. It is not currently known how widely spread infection of murres with the novel virus was, thus insufficient evidence exists to attribute the die-off to an outbreak of avian influenza. We conclude that food shortage alone is not an adequate explanation for the mortality of thick-billed murres in 2018, and highlight the importance of rapid response to mortality events in order to document alternative or confounding causes of mortality.
The Science Data Management Branch (SDM) of the U.S. Geological Survey (USGS) provides data management expertise and leadership and develops guidance and tools to support the USGS in providing the nation with reliable scientific information on the basis of which to describe the Earth. The SDM suite of tools supports the USGS Data Management Lifecycle by facilitating quality assurance, description, curation, and publishing of the Bureau's scientific data. The SDM suite of tools includes the USGS Data Management Website, USGS Science Data Catalog, Digital Object Identifier Tool, ScienceBase, ScienceBase Data Release Tool, Metadata Wizard, and Online Metadata Editor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203041","usgsCitation":"Hutchison, V.B., Liford, A.N., McClees-Funinan, Ricardo, Zolly, Lisa, Ignizio, D.A., Langseth, M.L., Serna, B.S., Sellers, E.A., Hsu, Leslie, Norkin, Tamar, McNiff, Marcia, Donovan, G.C., 2020, USGS enterprise tools for efficient and effective management of science data: U.S. Geological Survey Fact Sheet 2020–3041, 2 p., https://doi.org/10.3133/fs20203041.","productDescription":"4 p.","onlineOnly":"Y","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":378676,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3041/coverthb.jpg"},{"id":378677,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3041/fs20203041.pdf","text":"Report","size":"2.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3041"}],"contact":"Director, Science Analytics and Synthesis
U.S. Geological Survey
108 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Aquatic waterfowl, particularly those in the order Anseriformes and Charadriiformes, are the ecological reservoir of avian influenza viruses (AIVs). Dabbling ducks play a recognized role in the maintenance and transmission of AIVs. Furthermore, the pathogenesis of highly pathogenic AIV (HPAIV) in dabbling ducks is well characterized. In contrast, the role of diving ducks in HPAIV maintenance and transmission remains unclear. In this study, the pathogenesis of a North American A/Goose/1/Guangdong/96-lineage clade 2.3.4.4 group A H5N2 HPAIV, A/Northern pintail/Washington/40964/2014, in diving sea ducks (surf scoters, Melanitta perspicillata) was characterized.
Intrachoanal inoculation of surf scoters with A/Northern pintail/Washington/40964/2014 (H5N2) HPAIV induced mild transient clinical disease whilst concomitantly shedding high virus titers for up to 10 days post-inoculation (dpi), particularly from the oropharyngeal route. Virus shedding, albeit at low levels, continued to be detected up to 14 dpi. Two aged ducks that succumbed to HPAIV infection had pathological evidence for co-infection with duck enteritis virus, which was confirmed by molecular approaches. Abundant HPAIV antigen was observed in visceral and central nervous system organs and was associated with histopathological lesions.
Collectively, surf scoters, are susceptible to HPAIV infection and excrete high titers of HPAIV from the respiratory and cloacal tracts whilst being asymptomatic. The susceptibility of diving sea ducks to H5 HPAIV highlights the need for additional research and surveillance to further understand the contribution of diving ducks to HPAIV ecology.
","language":"English","publisher":"Springer","doi":"10.1186/s12917-020-02579-x","usgsCitation":"Luczo, J.M., Prosser, D., Pantin-Jackwood, M.J., Berlin, A., and Spackman, E., 2020, The pathogenesis of a North American H5N2 clade 2.3.4.4 group A highly pathogenic avian influenza virus in surf scoters (Melanitta perspicillata): BMC Veterinary Research, v. 16, 351, 10 p., https://doi.org/10.1186/s12917-020-02579-x.","productDescription":"351, 10 p.","ipdsId":"IP-115428","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":455237,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12917-020-02579-x","text":"Publisher Index Page"},{"id":378746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","noUsgsAuthors":false,"publicationDate":"2020-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Luczo, Jasmine M.","contributorId":241114,"corporation":false,"usgs":false,"family":"Luczo","given":"Jasmine","email":"","middleInitial":"M.","affiliations":[{"id":48207,"text":"USDA SEPRL","active":true,"usgs":false}],"preferred":false,"id":799587,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":799588,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pantin-Jackwood, Mary J.","contributorId":197094,"corporation":false,"usgs":false,"family":"Pantin-Jackwood","given":"Mary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":799589,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Berlin, Alicia 0000-0002-5275-3077 aberlin@usgs.gov","orcid":"https://orcid.org/0000-0002-5275-3077","contributorId":168416,"corporation":false,"usgs":true,"family":"Berlin","given":"Alicia","email":"aberlin@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":799590,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spackman, Erica","contributorId":53647,"corporation":false,"usgs":false,"family":"Spackman","given":"Erica","email":"","affiliations":[],"preferred":false,"id":799591,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70222610,"text":"70222610 - 2020 - Wait and snap: eastern snapping turtles (Chelydra serpentina) prey on migratory fish at road-stream crossing culverts","interactions":[],"lastModifiedDate":"2021-08-09T13:54:27.396441","indexId":"70222610","displayToPublicDate":"2020-09-23T08:48:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1028,"text":"Biology Letters","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Wait and snap: eastern snapping turtles (Chelydra serpentina) prey on migratory fish at road-stream crossing culverts","title":"Wait and snap: eastern snapping turtles (Chelydra serpentina) prey on migratory fish at road-stream crossing culverts","docAbstract":"There is growing evidence that culverts at road-stream crossings can increase fish density by reducing stream width and fish movement rates, making these passageways ideal predator ambush locations. In this study, we used a combination of videography and δ13C stable isotope analyses to investigate predator–prey interactions at a road-stream crossing culvert. Eastern snapping turtles (Chelydra serpentina) were found to regularly reside within the culvert to ambush migratory river herring (Alosa spp.). Resident fish species displayed avoidance of the snapping turtles, resulting in zero attempted attacks on these fish. In contrast, river herring did not display avoidance and were attacked by a snapping turtle on 79% of approaches with a 15% capture rate. Stable isotope analyses identified an apparent shift in turtle diet to consumption of river herring in turtles from culvert sites that was not observed in individuals from non-culvert sites. These findings suggest that anthropogenic barriers like culverts that are designed to allow passage may create predation opportunities by serving as a bottleneck to resident and migrant fish movement.
","language":"English","publisher":"The Royal Society","doi":"10.1098/rsbl.2020.0218","usgsCitation":"Alcott, D.J., Long, M., and Castro-Santos, T.R., 2020, Wait and snap: eastern snapping turtles (Chelydra serpentina) prey on migratory fish at road-stream crossing culverts: Biology Letters, v. 16, no. 9, 20200218, https://doi.org/10.1098/rsbl.2020.0218.","productDescription":"20200218","ipdsId":"IP-118228","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":455239,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsbl.2020.0218","text":"Publisher Index Page"},{"id":387779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Alcott, Derrick James 0000-0001-7765-1889","orcid":"https://orcid.org/0000-0001-7765-1889","contributorId":261904,"corporation":false,"usgs":true,"family":"Alcott","given":"Derrick","email":"","middleInitial":"James","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":820739,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Michael 0000-0001-6735-6878","orcid":"https://orcid.org/0000-0001-6735-6878","contributorId":261905,"corporation":false,"usgs":false,"family":"Long","given":"Michael","email":"","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":820740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":820741,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215716,"text":"70215716 - 2020 - Does the Darcy-Buckingham Law apply to flow through unsaturated porous rock?","interactions":[],"lastModifiedDate":"2020-10-28T13:20:09.284709","indexId":"70215716","displayToPublicDate":"2020-09-23T08:15:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Does the Darcy-Buckingham Law apply to flow through unsaturated porous rock?","docAbstract":"Geomagnetic perturbations (BGEO) related to magnetospheric ultralow frequency (ULF) waves induce electric fields within the conductive Earth—geoelectric fields (EGEO)—that in turn drive geomagnetically induced currents. Though numerous past studies have examined ULF wave BGEO from a space weather perspective, few studies have linked ULF waves with EGEO. Using recently available magnetotelluric impedance and EGEO measurements in the contiguous United States, we explore the relationship between ULF waves and EGEO. We use satellite, ground‐based radar, BGEO, and EGEO measurements in a case study of a plasmaspheric virtual resonance (PVR), demonstrating that the PVR EGEO has significant spatial variation in contrast to a relatively uniform BGEO, consistent with spatially varying Earth conductivity. We further show ULF wave EGEO measurements during two moderate storms of ∼1 V/km. We use both results to highlight the need for more research characterizing ULF wave EGEO.
Soft sediment deformation structures are common in fine-grained pyroclastic deposits and are often taken, along with other characteristics, to indicate that deposits were emplaced in a wet and cohesive state. At Ubehebe Crater (Death Valley, California, USA), deposits were emplaced by multiple explosions, both directly from pyroclastic surges and by rapid remobilization of fresh, fine-ash-rich deposits off steep slopes as local granular flows. With the exception of the soft sediment deformation structures themselves, there is no evidence of wet deposition. We conclude that deformation was a result of destabilization of fresh, fine-grained deposits with elevated pore-gas pressure and dry cohesive forces. Soft sediment deformation alone is not sufficient to determine whether parent pyroclastic surges contained liquid water and caused wet deposition of strata.
During winter 2017–18 coastal areas of New England were impacted by the January 4, and March 2–4, 2018, nor’easters. The U.S. Geological Survey (USGS), under an interagency agreement with the Federal Emergency Management Agency (FEMA), collected total water level data (the combination of tide, storm surge, wave runup and setup, and freshwater input) using the North American Vertical Datum of 1988 (NAVD 88) from high-water marks and continuous water-level sensors, to better understand the areal extent, timing, and impact of coastal flooding from strong storms.
During the January 4, 2018, nor’easter the National Oceanic and Atmospheric Administration (NOAA) Boston, Massachusetts, tide gage recorded the highest total water level on record of 9.66 ft. During the March 2–4, 2018, nor’easter, the Boston tide gage recorded its third highest total water level on record of 9.16 ft.
After the January and March 2018 nor’easter storms, the USGS deployed field teams that identified and flagged high-water marks along the coastlines of eastern Massachusetts in January and from Portland, Maine, south to the Connecticut-New York State border in March. In preparation for the approach of the March 2018 nor’easter, the USGS deployed 35 temporary water-level sensors along the coastline of New England to collect total water level data during the storm. Total water level data were also collected at 28 tide gages and 14 coastal streamgages (affected tidally or by tidal backwater during coastal storms) in New England during both nor’easters.
Total water level elevations at 71 high-water marks collected after the January 2018 nor’easter in coastal areas of eastern Massachusetts ranged from 5.8 to 15.1 feet (ft), with an average elevation of 9.4 ft and a median elevation of 9.6 ft. Total water level elevations at 10 tide gages and 7 coastal streamgages from Portland to Cape Cod Bay ranged from 4.8 to 11.2 ft, with an average of 9.1 ft and a median of 9.6 ft. Following the March 2018 nor’easter, 111 high-water marks were collected along the New England coastline. Of the 111 high-water marks, 100 were along the eastern coastline of New England from Portland to Cape Cod and had elevations that ranged from 5.3 to 15.1 ft, with an average of 8.9 ft and a median of 8.6 ft. The remaining 11 high-water marks along the southern coastline of New England in Connecticut, Rhode Island, and Massachusetts had elevations that ranged from 3.1 to 7.5 ft, with an average of 4.3 ft and a median of 4.9 ft. Total water level elevations for 19 USGS temporary water-level sensors from Portland to Cape Cod Bay ranged from 6.2 to 10.4 ft, with an average of 8.4 ft and a median of 8.7 ft. Total water level elevations at 10 tide gages and 6 coastal streamgages from Portland to Cape Cod Bay ranged from 7.8 to 10.8 ft, with an average of 9.1 ft and a median of 9.2 ft.
There were 10 tide gages and 5 coastal streamgages with data from both nor’easters from Portland to Cape Cod Bay; for the January nor’easter, the average and median elevations were about 0.3 and 0.5 ft higher, respectively, than for the March nor’easter. At the 52 high-water mark locations with data for both nor’easters in Massachusetts, the average and median elevations were 0.1 and 0.4 ft higher, respectively, for the January nor’easter than for the March nor’easter.
At 10 tide gages along the coastline from Portland to Cape Cod Bay, the observed peak total water level elevations for the January nor’easter ranged from 1.6 to 3.7 ft higher than the concurrent predicted elevations, with an average of 2.8 ft and a median of 3.0 ft higher. For the March nor’easter, the observed peak total water level elevations ranged from 1.8 to 4.0 ft higher than the concurrent predicted elevations, with an average of 2.7 ft and a median of 3.0 ft higher. This is approximately the amount of storm surge that was experienced during the highest tides of the two nor’easters along the coastline from Portland to Cape Cod Bay.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205048","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Bent, G.C., and Taylor, N.J., 2020, Total water level data from the January and March 2018 nor’easters for coastal areas of New England: U.S. Geological Survey Scientific Investigations Report 2020–5048, 47 p., https://doi.org/10.3133/sir20205048.","productDescription":"Report: vii, 47 p.; 2 Data Releases","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-108335","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":378670,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://stn.wim.usgs.gov/FEV/#NoreasterofMarch2018","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- Flood Event Viewer, March 2018 nor’easter"},{"id":378666,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5048/coverthb.jpg"},{"id":378669,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://stn.wim.usgs.gov/FEV/#NoreasterJanuary2018","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- Flood Event Viewer, January 2018 nor’easter"},{"id":378667,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5048/sir20205048.pdf","text":"Report","size":"4.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5048"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.86279296875,\n 44.80132682904856\n ],\n [\n -67.203369140625,\n 45.213003555993964\n ],\n [\n -67.32421875,\n 45.120052841530544\n ],\n [\n -67.412109375,\n 45.282617057517406\n ],\n [\n -67.423095703125,\n 45.606352077118316\n ],\n [\n -67.752685546875,\n 45.72152152227954\n ],\n [\n -67.796630859375,\n 47.092565552235705\n ],\n [\n -68.31298828125,\n 47.368594345213374\n ],\n [\n -68.92822265625,\n 47.21956811231547\n ],\n [\n -69.027099609375,\n 47.42065432071318\n ],\n [\n -69.2138671875,\n 47.45780853075031\n ],\n [\n -70.048828125,\n 46.70973594407157\n ],\n [\n -70.279541015625,\n 46.17983040759436\n ],\n [\n -70.455322265625,\n 45.71385093029221\n ],\n [\n -70.77392578125,\n 45.4524242413431\n ],\n [\n -71.015625,\n 45.298075138707965\n ],\n [\n -71.290283203125,\n 45.298075138707965\n ],\n [\n -71.510009765625,\n 44.99588261816546\n ],\n [\n -71.619873046875,\n 44.55133484083592\n ],\n [\n -72.015380859375,\n 44.33956524809713\n ],\n [\n -72.45483398437499,\n 43.42100882994726\n ],\n [\n -72.53173828125,\n 42.90011265525328\n ],\n [\n -72.4658203125,\n 42.76314586689492\n ],\n [\n -73.27880859375,\n 42.771211138625894\n ],\n [\n -73.509521484375,\n 42.09822241118974\n ],\n [\n -73.54248046875,\n 41.31082388091818\n ],\n [\n -73.740234375,\n 41.07935114946899\n ],\n [\n -73.641357421875,\n 41.00477542222947\n ],\n [\n -72.861328125,\n 41.253032440653186\n ],\n [\n -72.059326171875,\n 41.20345619205131\n ],\n [\n -70.345458984375,\n 41.30257109430557\n ],\n [\n -69.971923828125,\n 41.178653972331674\n ],\n [\n -69.80712890625,\n 41.236511201246216\n ],\n [\n -69.93896484375,\n 42.04113400940807\n ],\n [\n -70.57617187499999,\n 42.73894375124377\n ],\n [\n -69.98291015625,\n 43.6599240747891\n ],\n [\n -66.97265625,\n 44.645208223744035\n ],\n [\n -66.86279296875,\n 44.80132682904856\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Keys to Prairie Falcon (Falco mexicanus) management include maintaining cliffs with suitable recesses for use as nest sites (that is, the substrate that supports the nest or the specific location of the nest on the landscape), protecting nest sites from human disturbance by designating buffer zones, and maintaining open landscapes and habitats that support populations of ground squirrels (Urocitellus species) and small birds.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842S","usgsCitation":"DeLong, J.P., and Steenhof, K., 2020, The effects of management practices on grassland birds—Prairie Falcon (Falco mexicanus), chap. S of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 17 p., https://doi.org/10.3133/pp1842S.","productDescription":"iv, 17 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-093908","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":378641,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/s/coverthb.jpg"},{"id":378642,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/s/pp1842s.pdf","text":"Report","size":"2.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–S"}],"contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Mercury (Hg) has been a contaminant of concern for several decades in South Florida, particularly in the Florida Everglades. The transport and bioavailability of Hg in aquatic systems is intimately linked to dissolved organic carbon (DOC). In aquatic systems, Hg can be converted to methylmercury (MeHg), which is the form of Hg that bioaccumulates in food webs. The bioaccumulation of MeHg poses significant health risks to wildlife and humans. Fish consumption advisories triggered by elevated Hg levels first appeared in the 1980s in South Florida. Multiple structures regulate freshwater distribution to Everglades National Park, including S-12D. This report summarizes seasonal and annual concentration and load data from late September 2013 to April 2017 for the total of (1) filter-passing total mercury (FTHg), (2) filter-passing methylmercury (FMeHg), (3) particulate total mercury (PTHg), (4) particulate methylmercury (PMeHg) and, (5) DOC discharged through control structure S-12D. The loads of Hg fractions and DOC at control structure S-12D were determined by pairing discharge data with constituent concentrations estimated by empirical models based on surrogate in situ water-quality measurements.
Calculated concentrations of DOC ranged from 12.8 milligrams per liter (mg/L) to 27.9 mg/L with a mean of 18.8 mg/L during the study period. Annual loads of DOC ranged from 3,950 tons in 2015 to 10,900 tons in 2016. DOC loads increased linearly with an increase in flow, and the highest monthly DOC load of 1,630 tons was observed in February 2016.
Calculated concentrations of FTHg ranged from 0.35 to 1.55 nanograms per liter (ng/L) with a mean of 0.85 ng/L during the study period. Calculated concentrations of FMeHg ranged from 0.06 ng/L to 0.24 ng/L with a mean of 0.14 ng/L during the study period. Generally, FTHg and FMeHg concentrations were lower during periods of decreased flow and higher during periods of increased flow. Calculated PTHg concentrations ranged from 0.09 ng/L to 4.19 ng/L with a mean of 0.58 ng/L during the study period. Calculated PMeHg concentrations ranged from below the limit of detection <0.01 ng/L to 0.29 ng/L with a mean of 0.03 ng/L during the study period.
Loads of Hg were often zero or lowest from November to May, owing to the lack of flow or low-flow conditions. FTHg and FMeHg loads increased linearly with an increase in flow and typically were highest from June to October. During periods of increasing flow or following changes in gate operations, PTHg and PMeHg constituted a greater percentage of the total Hg load. Annual loads of total Hg (filter-passing and particulate) ranged from 254 grams in 2015 to 658 grams in 2016. FTHg was the predominant contributor to the total Hg load. Information presented herein provides the first assessment of DOC and Hg loads to Everglades National Park through control structure S-12D using continuous in situ measurements of discharge and constituent surrogates and compares the surrogate model approach to loads calculated from monthly sampling. Analysis of calculated and observed loads demonstrates the significance of flow data on calculating constituent loads.
Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Peak ground velocity (PGV) is a commonly used parameter in earthquake ground‐motion models (GMMs) and hazard analyses, because it is closely related to structural damage and felt ground shaking, and is typically measured on broadband seismometers. Here, we demonstrate that strainmeters, which directly measure in situ strain in the bulk rock, can easily be related to ground velocity by a factor of bulk shear‐wave velocity and, thus, can be used to measure strain‐estimated PGV. We demonstrate the parity of velocity to strain utilizing data from borehole strainmeters deployed along the plate boundaries of the west coast of the United States for nine recent
Australapatemon spp. are cosmopolitan trematodes that infect freshwater snails, aquatic leeches, and birds. Despite their broad geographic distribution, relatively little is known about interactions between Australapatemon spp. and their leech hosts, particularly under experimental conditions and in natural settings. We used experimental exposures to determine how Australapatemon burti cercariae dosage (number administered to leech hosts, Erpobdella microstoma) affected infection success (fraction to encyst as metacercariae), infection abundance, host survival, and host size over the 100 days following exposure. Interestingly, infection success was strongly density-dependent, such that there were no differences in metacercariae load even among hosts exposed to a 30-fold difference in cercariae. This relationship suggests that local processes (e.g., resource availability, interference competition, or host defenses) may play a strong role in parasite transmission. Our results also indicated that metacercariae did not become evident until ~4 weeks post exposure, with average load climbing until approximately 13 weeks. There was no evidence of metacercariae death or clearance over the census period. Parasite exposure had no detectable effects on leech size or survival, even with nearly 1,000 cercariae. Complementary surveys of leeches in California revealed that 11 of 14 ponds supported infection by A. burti (based on morphology and molecular sequencing), with an average prevalence of 32% and similar metacercariae intensity as in our experimental exposures. The extended development time and extreme density dependence of A. burti has implications for studying naturally occurring host populations, for which detected infections may represent only a fraction of cercariae to which animals have been exposed. Future investigation of these underlying mechanisms would be benefical in understanding host-parasite relationships.