Understanding the relationship between environmental factors and vital rates is an important step in predicting a species’ response to environmental change. Species associated with sea ice are of particular concern because sea ice is projected to decrease rapidly in polar environments with continued levels of greenhouse gas emissions. The relationship between sea ice and the vital rates of the Spectacled Eider, a threatened species that breeds in Alaska and Russia and winters in the Bering Sea, appears to be complex. While severe ice can impede foraging for benthic prey, ice also suppresses wave action and provides a platform on which eiders roost, thereby reducing thermoregulation costs. We analyzed a 23‐year mark‐recapture dataset for Spectacled Eiders nesting on Kigigak Island in western Alaska, and tested survival models containing different ice and weather‐related covariates. We found that much of the variation in eider survival could be explained by the number of days per year with >95% sea ice concentration at the Bering Sea core wintering area. Furthermore, the data supported a quadratic relationship with sea ice rather than a linear one, indicating that intermediate sea ice concentrations were optimal for survival. We then used matrix population models to project population trajectories using General Circulation Model (GCM) outputs of daily sea ice cover. GCMs projected reduced sea ice at the wintering area by year 2100 under a moderated emissions scenario (RCP 4.5) and nearly ice‐free conditions under an unabated emissions scenario (RCP 8.5). Under RCP 4.5, stochastic models projected an increase in population size until 2069 coincident with moderate ice conditions, followed by a decline in population size as ice conditions shifted from intermediate to mostly ice‐free. Under RCP 8.5, eider abundance increased until 2040 and then decreased to near extirpation toward the end of the century as the Bering Sea became ice‐free. Considerable uncertainty around parameter estimates for survival in years with minimal sea ice contributed to variation in stochastic projections of future population size, and this uncertainty could be reduced with additional survival data from low‐ice winters.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4637","usgsCitation":"Christie, K.S., Hollmen, T.E., Flint, P.L., and Douglas, D., 2018, Non‐linear effect of sea ice: Spectacled Eider survival declines at both extremes of the ice spectrum: Ecology and Evolution, v. 8, no. 23, p. 11808-11818, https://doi.org/10.1002/ece3.4637.","productDescription":"11 p.","startPage":"11808","endPage":"11818","ipdsId":"IP-093761","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468178,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4637","text":"Publisher Index Page"},{"id":360610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":" Kigigak Island","volume":"8","issue":"23","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-20","publicationStatus":"PW","scienceBaseUri":"5c1cb85de4b0708288c83817","contributors":{"authors":[{"text":"Christie, Katherine S.","contributorId":177114,"corporation":false,"usgs":false,"family":"Christie","given":"Katherine","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":754733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hollmen, Tuula E.","contributorId":211728,"corporation":false,"usgs":false,"family":"Hollmen","given":"Tuula","email":"","middleInitial":"E.","affiliations":[{"id":16211,"text":"Alaska SeaLife Center","active":true,"usgs":false}],"preferred":false,"id":754734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":754731,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":150115,"corporation":false,"usgs":true,"family":"Douglas","given":"David C.","email":"ddouglas@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":754732,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201657,"text":"70201657 - 2018 - Exposure of Alaska brown bears (Ursus arctos) to bacterial, viral, and parasitic agents varies spatiotemporally and may be influenced by age","interactions":[],"lastModifiedDate":"2019-08-15T11:45:00","indexId":"70201657","displayToPublicDate":"2018-12-20T10:34:30","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Exposure of Alaska brown bears (Ursus arctos) to bacterial, viral, and parasitic agents varies spatiotemporally and may be influenced by age","docAbstract":"We collected blood and serum from 155 brown bears (Ursus arctos) inhabiting five locations in Alaska during 2013–16 and tested samples for evidence of prior exposure to a suite of bacterial, viral, and parasitic agents. Antibody seroprevalence among Alaska brown bears was estimated to be 15% for Brucella spp., 10% for Francisella tularensis, 7% for Leptospira spp., 18% for canine adenovirus type 1 (CAV-1), 5% for canine distemper virus (CDV), 5% for canine parvovirus, 5% for influenza A virus (IAV), and 44% for Toxoplasma gondii. No samples were seropositive for antibodies to Trichinella spp. Point estimates of prior exposure to pathogens among brown bears at previously unsampled locations generally fell within the range of estimates for previously or contemporaneously sampled bears in Alaska. Statistical support was found for variation in antibody seroprevalence among bears by location or age cohort for CAV-1, CDV, IAV, and Toxoplasma gondii. There was limited concordance in comparisons between our results and previous serosurveys regarding spatial and age-related trends in antibody seroprevalence among Alaska brown bears suggestive of temporal variation. However, we found evidence that the seroprevalence of CAV-1 antibodies is consistently high in bears inhabiting SW Alaska and the cumulative probability of exposure may increase with age. We found evidence for seroconversion or seroreversion to six different infectious agents in one or more bears. Results of this study increase our collective understanding of disease risk to both Alaska brown bear populations and humans that utilize this resource.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2018-07-173","usgsCitation":"Ramey, A.M., Cleveland, C.A., Hilderbrand, G., Joly, K., Gustine, D.D., Mangipane, B., Leacock, W.B., Crupi, A.P., Hill, D.E., Dubey, J.P., and Yabsley, M.J., 2018, Exposure of Alaska brown bears (Ursus arctos) to bacterial, viral, and parasitic agents varies spatiotemporally and may be influenced by age: Journal of Wildlife Diseases, v. 55, no. 3, p. 576-588, https://doi.org/10.7589/2018-07-173.","productDescription":"13 p.","startPage":"576","endPage":"588","ipdsId":"IP-099360","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468179,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7589/2018-07-173","text":"Publisher Index Page"},{"id":437641,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94FFEUJ","text":"USGS data 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\"}}]}","volume":"55","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c1cb85ee4b0708288c8381b","contributors":{"editors":[{"text":"Leacock, William B.","contributorId":211732,"corporation":false,"usgs":false,"family":"Leacock","given":"William","email":"","middleInitial":"B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":754745,"contributorType":{"id":2,"text":"Editors"},"rank":7}],"authors":[{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":754735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cleveland, Christopher A.","contributorId":211729,"corporation":false,"usgs":false,"family":"Cleveland","given":"Christopher","email":"","middleInitial":"A.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":754736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hilderbrand, Grant V. 0000-0002-0051-8315 ghilderbrand@usgs.gov","orcid":"https://orcid.org/0000-0002-0051-8315","contributorId":199764,"corporation":false,"usgs":true,"family":"Hilderbrand","given":"Grant V.","email":"ghilderbrand@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":754737,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Joly, Kyle","contributorId":53117,"corporation":false,"usgs":false,"family":"Joly","given":"Kyle","email":"","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":754738,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gustine, David D. dgustine@usgs.gov","contributorId":3776,"corporation":false,"usgs":true,"family":"Gustine","given":"David","email":"dgustine@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":754739,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mangipane, Buck","contributorId":211731,"corporation":false,"usgs":false,"family":"Mangipane","given":"Buck","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":754740,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leacock, William B.","contributorId":211732,"corporation":false,"usgs":false,"family":"Leacock","given":"William","email":"","middleInitial":"B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":754766,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crupi, Anthony P.","contributorId":211733,"corporation":false,"usgs":false,"family":"Crupi","given":"Anthony","email":"","middleInitial":"P.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":754741,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hill, Dolores E.","contributorId":211734,"corporation":false,"usgs":false,"family":"Hill","given":"Dolores","email":"","middleInitial":"E.","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":754742,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Dubey, Jitender P.","contributorId":206206,"corporation":false,"usgs":false,"family":"Dubey","given":"Jitender","email":"","middleInitial":"P.","affiliations":[{"id":37284,"text":"United States Department of Agriculture, Agricultural Research Service, Beltsville Agricultural Research Center, Animal Parasitic Diseases Laboratory, Building 1001, Beltsville, MD, 20705-2350, USA","active":true,"usgs":false}],"preferred":false,"id":754743,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Yabsley, Michael J.","contributorId":76985,"corporation":false,"usgs":false,"family":"Yabsley","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13266,"text":"Warnell School of Forestry and Natural Resources, The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":754744,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70201359,"text":"sir20185167 - 2018 - Flood-inundation maps for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek at Ithaca, New York","interactions":[],"lastModifiedDate":"2018-12-20T16:27:27","indexId":"sir20185167","displayToPublicDate":"2018-12-20T06:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5167","displayTitle":"Flood-Inundation Maps for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek at Ithaca, New York","title":"Flood-inundation maps for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek at Ithaca, New York","docAbstract":"Digital flood-inundation maps for a 2.9-square-mile area of Ithaca, New York, were created in 2015–18 by the U.S. Geological Survey in cooperation with the City of Ithaca, New York, and the New York State Department of State. The flood-inundation maps depict estimates of the maximum areal extent and depth of flooding corresponding to selected flood frequencies for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek and selected water-surface elevations of Cayuga Lake.
Flood profiles for the stream reaches were computed by combining a one-dimensional step-backwater model for the stream channels and a two-dimensional model for the overbank areas. The resulting hydraulic model was calibrated by using water-surface profiles from five observed storm events. The model was then used to compute 15 water-surface profiles for 5 flood frequencies (50-, 10-, 2-, 1-, and 0.2-percent annual exceedance probabilities, or 2-, 10-, 50-, 100-, and 500-year recurrence intervals) and 3 lake levels (representing average conditions, a 2-year-high condition, and a 100-year-high condition). The simulated water-surface profiles were then combined with a digital elevation model (derived from light detection and ranging data having 0.31‑foot vertical accuracy and 3.3-foot horizontal resolution) to delineate the maximum area flooded at each water level.
Flood-inundation maps and geographic information system flood-extent polygons and depth grids are available in the data release associated with this report. These maps can provide emergency management personnel and residents with information that is critical for flood-management planning, flood-response activities, and postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185167","collaboration":"Prepared in cooperation with the City of Ithaca, New York, and the New York State Department of State","usgsCitation":"Nystrom, E.A., Lilienthal, A.G., III, and Coon, W.F., 2018, Flood-inundation maps for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek at Ithaca, New York: U.S. Geological Survey Scientific Investigations Report 2018–5167, 27 p., https://doi.org/10.3133/sir20185167. \n\n","productDescription":"Report: viii, 27 p.; Data release","ipdsId":"IP-097931","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":437643,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V8ED23","text":"USGS data release","linkHelpText":"Geospatial dataset of flood-inundation maps for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek at Ithaca, New York"},{"id":360375,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V8ED23 ","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial dataset of flood-inundation maps for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek at Ithaca, New York, 2018"},{"id":360373,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5167/coverthb.jpg"},{"id":360374,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5167/sir20185167.pdf","text":"Report","size":"6.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5167"}],"country":"United States","state":"New York","city":"Ithaca","otherGeospatial":"Cascadilla Creek, Cayuga Inlet, Fall Creek, Sixmile Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.53213500976562,\n 42.413825296776835\n ],\n [\n -76.48578643798827,\n 42.413825296776835\n ],\n [\n -76.48578643798827,\n 42.46994435756588\n ],\n [\n -76.53213500976562,\n 42.46994435756588\n ],\n [\n -76.53213500976562,\n 42.413825296776835\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180
A series of laboratory experiments was conducted to better understand the behavior of grass carp eggs and larvae in moving water in order to develop and implement new strategies for control and prediction of their dispersal and drift at early life stages. Settling velocity and density of a representative sample of eggs were estimated, and three trials of flume experiments with different flow conditions were conducted with live eggs in a temperature-controlled setting with a mobile sediment bed. In these trials, egg and larval stages were continuously analyzed over periods of 80 hours; and eggs and larvae interactions with the flow and sediment bed were monitored and characterized qualitatively and quantitatively. Survival rates were quantified after each trial, highlighting physical causes for increased mortality. Detailed flow analysis was correlated to the observed drifting and swimming behavior of eggs and larvae, to estimate distributions across the water depth, as well as traveling and swimming speeds. Evidence of the influence of mean and turbulent flow in the suspension and transport of eggs are reported, and swimming patterns of larvae at different developmental stages are described. These findings support the development of new strategies for monitoring the spread of grass carp eggs and larvae in rivers, and provide new inputs to predict conditions favorable for spawning and hatching, allowing for mitigation measures at early life stages, which are critical to control their dispersal.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0208326","usgsCitation":"Prada, A.F., George, A.E., Stahlschmidt, B.H., Chapman, D., and Tinoco, R.O., 2018, Survival and drifting patterns of grass carp eggs and larvae in response to interactions with flow and sediment in a laboratory flume: PLoS ONE, v. 13, no. 12, p. 1-19, https://doi.org/10.1371/journal.pone.0208326.","productDescription":"e0208326; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-098037","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":468180,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0208326","text":"Publisher Index Page"},{"id":360663,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"12","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-19","publicationStatus":"PW","scienceBaseUri":"5c1e0a2fe4b0708288cb020f","contributors":{"authors":[{"text":"Prada, Andres F.","contributorId":211778,"corporation":false,"usgs":false,"family":"Prada","given":"Andres","email":"","middleInitial":"F.","affiliations":[{"id":38317,"text":"Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL","active":true,"usgs":false}],"preferred":false,"id":754851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Amy E. 0000-0003-1150-8646 ageorge@usgs.gov","orcid":"https://orcid.org/0000-0003-1150-8646","contributorId":3950,"corporation":false,"usgs":true,"family":"George","given":"Amy","email":"ageorge@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":754850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stahlschmidt, Benjamin H. 0000-0001-6197-662X","orcid":"https://orcid.org/0000-0001-6197-662X","contributorId":211250,"corporation":false,"usgs":true,"family":"Stahlschmidt","given":"Benjamin","email":"","middleInitial":"H.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":754852,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":754853,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tinoco, Rafael O.","contributorId":211779,"corporation":false,"usgs":false,"family":"Tinoco","given":"Rafael","email":"","middleInitial":"O.","affiliations":[{"id":38317,"text":"Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL","active":true,"usgs":false}],"preferred":false,"id":754854,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70201603,"text":"70201603 - 2018 - Survey of Arctic Alaskan wildlife for influenza A antibodies: Limited evidence for exposure of mammals","interactions":[],"lastModifiedDate":"2019-06-18T09:57:37","indexId":"70201603","displayToPublicDate":"2018-12-18T09:22:22","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Survey of Arctic Alaskan wildlife for influenza A antibodies: Limited evidence for exposure of mammals","docAbstract":"Influenza A viruses (IAVs) are maintained in wild waterbirds and have the potential to infect a broad range of species, including wild mammals. The Arctic Coastal Plain of Alaska supports a diverse suite of species, including waterfowl that are common hosts of IAVs. Mammals co-occur with geese and other migratory waterbirds during the summer breeding season, providing a plausible mechanism for interclass transmission of IAVs. To estimate IAV seroprevalence and identify the subtypes to which geese, loons, Arctic foxes (Vulpes lagopus), caribou (Rangifer tarandus), and polar bears (Ursus maritimus) are potentially exposed, we used a blocking enzyme-linked immunosorbent assay (bELISA) and a hemagglutination inhibition (HI) assay to screen for antibodies to IAVs in samples collected during spring and summer of 2012–16. Apparent IAV seroprevalence using the bELISA was 50.7% in geese (range by species: 46.1–52.8%), 9.2% in loons, (range by species: 3.4–20.0%), and 0.4% in Arctic foxes. We found no evidence for exposure to IAVs in polar bears or caribou by either assay. Among geese, we estimated detection probability from replicate bELISA analyses to be 0.92 and also found good concordance (>85%) between results from bELISA and HI assays, which identified antibodies reactive to H1, H6, and H9 subtype IAVs. In contrast, the HI assay detected antibodies in only one of seven loon samples that were positive by bELISA; that sample had low titers to both H4 and H5 IAV subtypes. Our results provide evidence that a relatively high proportion of waterbirds breeding on the Arctic Coastal Plain are exposed to IAVs, although it is unknown whether such exposure occurs locally or on staging or wintering grounds. In contrast, seroprevalence of IAVs in concomitant mammals is apparently low.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2018-05-128","usgsCitation":"Van Hemert, C.R., Spivey, T.J., Uher-Koch, B.D., Atwood, T.C., Sinnett, D.R., Meixell, B.W., Hupp, J.W., Jiang, K., Adams, L., Gustine, D.D., Ramey, A.M., and Wan, X., 2018, Survey of Arctic Alaskan wildlife for influenza A antibodies: Limited evidence for exposure of mammals: Journal of Wildlife Diseases, v. 55, no. 2, p. 387-398, https://doi.org/10.7589/2018-05-128.","productDescription":"12 p.","startPage":"387","endPage":"398","ipdsId":"IP-097920","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":437650,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FPXQTP","text":"USGS data release","linkHelpText":"Serological Data on Influenza A from Birds and Mammals on the Arctic Coastal Plain of Northern Alaska, 2011-2017"},{"id":360442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160,\n 69\n ],\n [\n -149.5,\n 69\n ],\n [\n -149.5,\n 71.5\n ],\n [\n -160,\n 71.5\n ],\n [\n -160,\n 69\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c1a1531e4b0708288c23520","contributors":{"authors":[{"text":"Van Hemert, Caroline R. 0000-0002-6858-7165 cvanhemert@usgs.gov","orcid":"https://orcid.org/0000-0002-6858-7165","contributorId":3592,"corporation":false,"usgs":true,"family":"Van Hemert","given":"Caroline","email":"cvanhemert@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":754478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spivey, Timothy J. 0000-0003-2735-2770 tspivey@usgs.gov","orcid":"https://orcid.org/0000-0003-2735-2770","contributorId":198763,"corporation":false,"usgs":true,"family":"Spivey","given":"Timothy","email":"tspivey@usgs.gov","middleInitial":"J.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":754479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Uher-Koch, Brian D. 0000-0002-1885-0260 buher-koch@usgs.gov","orcid":"https://orcid.org/0000-0002-1885-0260","contributorId":5117,"corporation":false,"usgs":true,"family":"Uher-Koch","given":"Brian","email":"buher-koch@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":754480,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":754481,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sinnett, David R.","contributorId":199479,"corporation":false,"usgs":false,"family":"Sinnett","given":"David","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":754482,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meixell, Brandt W. 0000-0002-6738-0349 bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":754483,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hupp, Jerry W. 0000-0002-6439-3910 jhupp@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-3910","contributorId":127803,"corporation":false,"usgs":true,"family":"Hupp","given":"Jerry","email":"jhupp@usgs.gov","middleInitial":"W.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":754484,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jiang, Kaijun","contributorId":211603,"corporation":false,"usgs":false,"family":"Jiang","given":"Kaijun","email":"","affiliations":[],"preferred":false,"id":754485,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":754486,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gustine, David D. 0000-0003-1087-1937","orcid":"https://orcid.org/0000-0003-1087-1937","contributorId":201734,"corporation":false,"usgs":false,"family":"Gustine","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":754487,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":754488,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wan, Xiu-Feng","contributorId":173959,"corporation":false,"usgs":false,"family":"Wan","given":"Xiu-Feng","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":754489,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70201503,"text":"70201503 - 2018 - Time-to-detection occupancy modeling: An efficient method for analyzing the occurrence of amphibians and reptiles","interactions":[],"lastModifiedDate":"2025-01-02T14:32:22.520282","indexId":"70201503","displayToPublicDate":"2018-12-17T10:08:56","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Time-to-detection occupancy modeling: An efficient method for analyzing the occurrence of amphibians and reptiles","docAbstract":"Occupancy models provide a reliable method of estimating species distributions while accounting for imperfect detectability. The cost of accounting for false absences is that detection and nondetection surveys typically require repeated visits to a site or multiple-observer techniques. More efficient methods of collecting data to estimate detection probabilities would allow additional sites to be surveyed for the same amount of effort, which would support more precise estimation of covariate effects to improve inference about underlying ecological processes. Time-to-detection surveys allow the estimation of detection probability based on a single site visit by one observer, and therefore might be an efficient technique for herpetological occupancy studies. We evaluated the use of time-to-detection surveys to estimate the occupancy of pond-breeding amphibians at Point Reyes National Seashore, California, USA, including variables that affected detection rates and the probability of occurrence. We found that detection times were short enough, and occupancy was high enough, to estimate reliably the probability of occurrence of three pond-breeding amphibians at Point Reyes National Seashore, and that survey and site conditions had species-specific effects on detection rates. In particular, pond characteristics affected detection times of all commonly detected species. Probability of occurrence of Sierran Treefrogs (Hyliola sierra) and Rough-Skinned Newts (Taricha granulosa) was negatively related to the detection of fish and pond area. Time-to-detection surveys can provide an efficient method for estimating detection probabilities and accounting for false absences in occupancy studies of reptiles and amphibians.
","language":"English","publisher":"The Society for the Study of Amphibians and Reptiles","doi":"10.1670/18-049","usgsCitation":"Halstead, B., Kleeman, P.M., and Rose, J.P., 2018, Time-to-detection occupancy modeling: An efficient method for analyzing the occurrence of amphibians and reptiles: Journal of Herpetology, v. 52, no. 4, p. 415-424, https://doi.org/10.1670/18-049.","productDescription":"10 p.; Data Release","startPage":"415","endPage":"424","ipdsId":"IP-098079","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":437651,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A9LA1O","text":"USGS data release","linkHelpText":"Time to detection data for Point Reyes pond-breeding amphibians, 2017"},{"id":360358,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Point Reyes National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.03451538085939,\n 37.92578434712101\n ],\n [\n -122.68913269042967,\n 37.92578434712101\n ],\n [\n -122.68913269042967,\n 38.24842651622814\n ],\n [\n -123.03451538085939,\n 38.24842651622814\n ],\n [\n -123.03451538085939,\n 37.92578434712101\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c18c423e4b006c4f856acce","contributors":{"authors":[{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":754352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":754353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":754354,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201474,"text":"70201474 - 2018 - Quantifying uncertainty in simulated streamflow and runoff from a continental-scale monthly water balance model","interactions":[],"lastModifiedDate":"2018-12-14T10:42:57","indexId":"70201474","displayToPublicDate":"2018-12-14T10:42:52","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying uncertainty in simulated streamflow and runoff from a continental-scale monthly water balance model","docAbstract":"One important component of continental-scale hydrologic modeling is quantifying the level of uncertainty in long-term hydrologic simulations and providing a range of possible simulated streamflow and/or runoff values for gaged and ungaged locations. In this paper, uncertainty was quantified for simulated streamflow and runoff generated from a monthly water balance model (MWBM) at 1575 streamgages and 109,951 hydrologic response units (HRUs), which span the conterminous United States (CONUS). A stochastic-approach, which incorporated the properties of modeled streamflow residuals back into the simulated model output, was used to create time series of upper and lower uncertainty intervals (UIs) around the simulated monthly time series. This approach was applied to an existing hydrologic regionalization implementation. Metrics used to evaluate the UIs across the CONUS (the coverage ratio, average width index, and interval skill score) indicated that on average the UIs were reliable, skillful, and sharp in being able to both contain measured streamflow observations and reduce estimates of uncertainty based on expected model predictions. These uncertainty evaluation metrics can complement each other in characterizing model skill and uncertainty over large-scale domains.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2018.10.005","usgsCitation":"Bock, A.R., Farmer, W.H., and Hay, L., 2018, Quantifying uncertainty in simulated streamflow and runoff from a continental-scale monthly water balance model: Advances in Water Resources, v. 122, p. 166-175, https://doi.org/10.1016/j.advwatres.2018.10.005.","productDescription":"10 p.","startPage":"166","endPage":"175","ipdsId":"IP-094722","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":360293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c14cfb5e4b006c4f8545d26","contributors":{"authors":[{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":754253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren E. 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":211478,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":754252,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70239437,"text":"70239437 - 2018 - Communicating information on nature-related topics: Preferred information channels and trust in sources","interactions":[],"lastModifiedDate":"2023-01-13T13:18:11.190282","indexId":"70239437","displayToPublicDate":"2018-12-12T07:15:19","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Communicating information on nature-related topics: Preferred information channels and trust in sources","docAbstract":"How information is communicated influences the public’s environmental perceptions and behaviors. Information channels and sources both play an important role in the dissemination of information. Trust in a source is often used as a proxy for whether a particular piece of information is credible. To determine preferences for information channels and trust in various sources for information on nature-related topics, a mail-out survey was sent to randomly selected U.S. addresses (n = 1,030). Diverse groups of people may have differing communication preferences. Therefore, we explored differences in channel preferences and trust by demographics using regression models. Overall, the most preferred channels were personal experience, reading online content, and watching visual media online. The most trusted sources were science organizations, universities, and friends/family. Channel preferences varied the most by education level and age, while source trust was most influenced by education, race, age, and size of current residence (rural-urban). The influence of demographics varied depending on the individual channel and source, with some groups preferring certain channels or sources but not others. Results are useful to consider when disseminating information on nature-related topics to a general public audience. More broadly, results also suggest spreading information using different channels and sources depending on the specific audience being targeted.
While the relationship between coyotes (Canis latrans) and house cats (Felis catus) may be characterized as one between predators and their prey, coyote interactions with domestic dogs (C. lupus familiaris) appear to be more varied and may include behaviors associated with canid sociality. While encounters between coyotes and dogs are difficult to observe, we capitalized on publicly available video recordings of coyote-dog encounters to observe canid behaviors and examined 35 video clips downloaded from YouTube during fall 2014. We identified coyote-dog interactions that were playful, agonistic, or predatory; those that we could not clearly categorize were labeled as other/undetermined. We found that both species were recorded directing play to the other species, which led to mutual play bouts. We observed a similar number of agonistic encounters, which included dogs biting coyotes and coyotes biting dogs. The main difference in agonistic behavior was that coyotes usually showed defensive aggression while dogs did not show defensive aggression. We also observed coyotes ambushing and bite-shaking small dogs in 3 video clips, from which the dogs escaped, but we did not see predatory behavior of dogs towards coyotes. Dog size may be related to types of interactions. No small dogs were involved in agonistic interactions, and only 1 small dog was observed playing with a coyote. From these videos, we conclude that the relationship between coyotes and dogs cannot be simply described as predator-prey; indeed, much of it appears to be social behavior divided between playful and agonistic. Future work that aims to explain the proximate correlates of play and aggression would provide more information for managers who wish to educate humans to reduce wildlife-human-dog conflicts.
","language":"English","publisher":"Utah State University- Berryman Institute","doi":"10.26077/ab4z-t030","usgsCitation":"Boydston, E.E., Abelson, E.S., Kazanjian, A., and Blumstein, D.T., 2018, Canid vs. canid: Insights into coyote–dog encounters from social media: Human-Wildlife Interactions, v. 12, no. 2, p. 233-242, https://doi.org/10.26077/ab4z-t030.","productDescription":"10 p.","startPage":"233","endPage":"242","ipdsId":"IP-091201","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":360086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c0f897ae4b0c53ecb2c71f0","contributors":{"authors":[{"text":"Boydston, Erin E. 0000-0002-8452-835X eboydston@usgs.gov","orcid":"https://orcid.org/0000-0002-8452-835X","contributorId":1705,"corporation":false,"usgs":true,"family":"Boydston","given":"Erin","email":"eboydston@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":753413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abelson, Eric S.","contributorId":211227,"corporation":false,"usgs":false,"family":"Abelson","given":"Eric","email":"","middleInitial":"S.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":753414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kazanjian, Ari","contributorId":211228,"corporation":false,"usgs":false,"family":"Kazanjian","given":"Ari","email":"","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":753415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blumstein, Daniel T.","contributorId":150453,"corporation":false,"usgs":false,"family":"Blumstein","given":"Daniel","email":"","middleInitial":"T.","affiliations":[{"id":18023,"text":"Ecology and Evolutionary Biology, UCLA","active":true,"usgs":false}],"preferred":false,"id":753416,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201268,"text":"70201268 - 2018 - Eco‐evolutionary rescue promotes host–pathogen coexistence","interactions":[],"lastModifiedDate":"2018-12-10T10:02:08","indexId":"70201268","displayToPublicDate":"2018-12-10T10:02:05","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Eco‐evolutionary rescue promotes host–pathogen coexistence","docAbstract":"Emerging infectious pathogens are responsible for some of the most severe host mass mortality events in wild populations. Yet, effective pathogen control strategies are notoriously difficult to identify, in part because quantifying and forecasting pathogen spread and disease dynamics is challenging. Following an outbreak, hosts must cope with the presence of the pathogen, leading to host–pathogen coexistence or extirpation. Despite decades of research, little is known about host–pathogen coexistence post‐outbreak when low host abundances and cryptic species make these interactions difficult to study. Using a novel disease‐structured N‐mixture model, we evaluate empirical support for three host–pathogen coexistence hypotheses (source–sink, eco‐evolutionary rescue, and spatial variation in pathogen transmission) in a Neotropical amphibian community decimated by Batrachochytrium dendrobatidis (Bd) in 2004. During 2010–2014, we surveyed amphibians in Parque Nacional G. D. Omar Torríjos Herrera, Coclé Province, El Copé, Panama. We found that the primary driver of host–pathogen coexistence was eco‐evolutionary rescue, as evidenced by similar amphibian survival and recruitment rates between infected and uninfected hosts. Average apparent monthly survival rates of uninfected and infected hosts were both close to 96%, and the expected number of uninfected and infected hosts recruited (via immigration/reproduction) was less than one host per disease state per 20‐m site. The secondary driver of host–pathogen coexistence was spatial variation in pathogen transmission as we found that transmission was highest in areas of low abundance but there was no support for the source–sink hypothesis. Our results indicate that changes in the host community (i.e., through genetic or species composition) can reduce the impacts of emerging infectious disease post‐outbreak. Our disease‐structured N‐mixture model represents a valuable advancement for conservation managers trying to understand underlying host–pathogen interactions and provides new opportunities to study disease dynamics in remnant host populations decimated by virulent pathogens.
","language":"English","publisher":"ESA","doi":"10.1002/eap.1792","usgsCitation":"DiRenzo, G.V., Zipkin, E.F., Campbell Grant, E.H., Royle, J.A., Longo, A.V., Zamudio, K.R., and Lips, K.R., 2018, Eco‐evolutionary rescue promotes host–pathogen coexistence: Ecological Applications, v. 28, no. 8, p. 1948-1962, https://doi.org/10.1002/eap.1792.","productDescription":"15 p.","startPage":"1948","endPage":"1962","ipdsId":"IP-082685","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468195,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.1792","text":"Publisher Index Page"},{"id":360085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-03","publicationStatus":"PW","scienceBaseUri":"5c0f897ae4b0c53ecb2c71f3","contributors":{"authors":[{"text":"DiRenzo, Graziella V.","contributorId":192177,"corporation":false,"usgs":false,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":753432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zipkin, Elise F. 0000-0003-4155-6139","orcid":"https://orcid.org/0000-0003-4155-6139","contributorId":192755,"corporation":false,"usgs":false,"family":"Zipkin","given":"Elise","email":"","middleInitial":"F.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":753433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":753431,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":753434,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Longo, Ana V.","contributorId":202587,"corporation":false,"usgs":false,"family":"Longo","given":"Ana","email":"","middleInitial":"V.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":753435,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zamudio, Kelly R.","contributorId":8320,"corporation":false,"usgs":true,"family":"Zamudio","given":"Kelly","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":753436,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lips, Karen R.","contributorId":26258,"corporation":false,"usgs":true,"family":"Lips","given":"Karen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":753437,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208211,"text":"70208211 - 2018 - IUPAC Periodic Table of the Elements and Isotopes (IPTEI) for the education community (IUPAC Technical Report)","interactions":[],"lastModifiedDate":"2020-01-31T06:46:40","indexId":"70208211","displayToPublicDate":"2018-12-08T06:42:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3207,"text":"Pure and Applied Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"IUPAC Periodic Table of the Elements and Isotopes (IPTEI) for the education community (IUPAC Technical Report)","docAbstract":"The IUPAC (International Union of Pure and Applied Chemistry) Periodic Table of the Elements and Isotopes (IPTEI) was created to familiarize students, teachers, and non-professionals with the existence and importance of isotopes of the chemical elements. The IPTEI is modeled on the familiar Periodic Table of the Chemical Elements. The IPTEI is intended to hang on the walls of chemistry laboratories and classrooms. Each cell of the IPTEI provides the chemical name, symbol, atomic number, and standard atomic weight of an element. Color-coded pie charts in each element cell display the stable isotopes and the relatively long lived radioactive isotopes having characteristic terrestrial isotopic compositions that determine the standard atomic weight of each element. The background color scheme of cells categorizes the 118 elements into four groups: (1) white indicates the element has no standard atomic weight, (2) blue indicates the element has only one isotope that is used to determine its standard atomic weight, which is given as a single value with an uncertainty, (3) yellow indicates the element has two or more isotopes that are used to determine its standard atomic weight, which is given as a single value with an uncertainty, and (4) pink indicates the element has a well-documented variation in its atomic weight, and the standard atomic weight is expressed as an interval. An element-by-element review accompanies the IPTEI and includes a chart of all known stable and radioactive isotopes for each element. Practical applications of isotopic measurements and technologies are included for the following fields: forensic science, geochronology, Earth-system sciences, environmental science, and human health sciences, including medical diagnosis and treatment.","language":"English","publisher":"De Gruyter","doi":"10.1515/pac-2015-0703","usgsCitation":"Holden, N.E., Coplen, T.B., Bohlke, J., Tarbox, L.V., Benefield, J., de Laeter, J.R., Mahaffy, P.G., O’Connor nee Singleton, G., Roth, E., Tepper, D., Walczyk, T., Wieser, M.E., and Yoneda, S., 2018, IUPAC Periodic Table of the Elements and Isotopes (IPTEI) for the education community (IUPAC Technical Report): Pure and Applied Chemistry, v. 90, no. 12, p. 1833-2092, https://doi.org/10.1515/pac-2015-0703.","productDescription":"260 p.","startPage":"1833","endPage":"2092","ipdsId":"IP-077158","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468197,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1515/pac-2015-0703","text":"Publisher Index Page"},{"id":371782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Holden, Norman E.","contributorId":189167,"corporation":false,"usgs":false,"family":"Holden","given":"Norman","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":780971,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - 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2018 - Characterizing toxicity of metal‐contaminated sediments from the Upper Columbia River, Washington, USA, to benthic invertebrates","interactions":[],"lastModifiedDate":"2018-12-07T14:00:10","indexId":"70201214","displayToPublicDate":"2018-12-07T14:00:06","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing toxicity of metal‐contaminated sediments from the Upper Columbia River, Washington, USA, to benthic invertebrates","docAbstract":"Sediments from the Upper Columbia River, Washington, USA, are contaminated with metals from smelting operations. We conducted short‐term and long‐term tests with the midge Chironomus dilutus and the amphipod Hyalella azteca and short‐term tests with the freshwater mussel Lampsilis siliquoidea with 54 sediments from the Upper Columbia River to characterize thresholds for toxicity of metals to benthic invertebrates. Test sediments were screened for toxicity by comparisons with low‐metal reference sediments. Toxic effects on amphipods occurred primarily in sediments from the upstream (riverine) reach, and toxic effects on midges occurred in sediments from both the upstream reach and the downstream (reservoir) reach. Little toxicity was observed in mussel tests. Toxicity thresholds (20% effect concentrations [EC20s]) for metals in sediment and porewater were estimated from logistic concentration–response models. Copper (Cu) concentrations in the simultaneously extracted metal fraction of sediments and bioavailable Cu in porewater, as characterized by biotic ligand models, had consistent associations with toxicity endpoints. Concentration–response models for sediment Cu produced EC20s for 6 endpoints, with long‐term amphipod survival and reproduction being the most sensitive. A logistic regression model fitted to an endpoint sensitivity distribution for sediment Cu predicted that approximately one‐half of the sediments tested would be toxic to at least one endpoint and that approximately 20% of test sediments would be toxic to more than half of the endpoints. These results indicate that sediments from the upstream reach of the Upper Columbia River, which contain high concentrations of metals associated with slags, cause a wide range of toxic effects in laboratory tests and are likely to have adverse effects on benthic invertebrate communities.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.4276","usgsCitation":"Besser, J.M., Steevens, J.A., Kunz, J.L., Brumbaugh, W., Ingersoll, C.G., Cox, S.E., Mebane, C.A., Balistrieri, L.S., Sinclair, J.A., and MacDonald, D.D., 2018, Characterizing toxicity of metal‐contaminated sediments from the Upper Columbia River, Washington, USA, to benthic invertebrates: Environmental Toxicology and Chemistry, v. 37, no. 12, p. 3102-3114, https://doi.org/10.1002/etc.4276.","productDescription":"13 p.","startPage":"3102","endPage":"3114","ipdsId":"IP-097897","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":360059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Upper Columbia River","volume":"37","issue":"12","publishingServiceCenter":{"id":4,"text":"Rolla 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James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":753286,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brumbaugh, William G. 0000-0003-0081-375X","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":202358,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":753287,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 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amphibian","interactions":[],"lastModifiedDate":"2020-12-29T13:39:05.613643","indexId":"70217043","displayToPublicDate":"2018-12-04T07:36:11","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Twenty-nine years of population dynamics in a small-bodied montane amphibian","docAbstract":"Identifying population declines before they reach crisis proportions is imperative given the current global decline in vertebrate fauna and associated challenges and expense of recovery. Understanding life histories and how the environment influences demography are critical aspects of this challenge, as is determining the biological relevance of covariates that are best supported by the data. We used 29 yr of data on chorus frogs at two sites to estimate demographic parameters, examine life history, assess weather‐related covariates, and determine the magnitude of process variation in target parameters. Average estimates of survival probabilities were 0.51 (Standard Error [SE] = 0.04) and 0.43 (SE = 0.04), and average estimates of recruitment probabilities were 0.64 (SE = 0.07) and 0.44 (SE = 0.04). Process variation accounted for ≥76% of the total temporal variation in both parameters at one pond and in survival probability alone at the other, suggesting that the covariates in our top models were explaining predominantly process rather than sampling variation. Estimates of population growth rates indicated a declining population at one pond (i.e., negative population growth rates in 15 of 18 yr), and comparisons with historical estimates suggested declines in survival probability at the other. The amount of deviance explained was low, providing little support for the influence of covariates on target parameters, despite model selection support. Synthesis and applications: This analysis illustrates the value of disentangling components of variance when assessing demographic drivers and highlights the need for adequate demographic information in assigning conservation labels.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2522","usgsCitation":"Muths, E., Scherer, R., Amburgey, S.M., and Corn, P., 2018, Twenty-nine years of population dynamics in a small-bodied montane amphibian: Ecosphere, v. 9, no. 12, e02522, 15 p., https://doi.org/10.1002/ecs2.2522.","productDescription":"e02522, 15 p.","ipdsId":"IP-073404","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468206,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2522","text":"Publisher Index Page"},{"id":437659,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BZAPLB","text":"USGS data release","linkHelpText":"Demographic data from two chorus frog populations in Colorado"},{"id":381718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"12","noUsgsAuthors":false,"publicationDate":"2018-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":245923,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":807332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scherer, R D","contributorId":245924,"corporation":false,"usgs":false,"family":"Scherer","given":"R D","affiliations":[{"id":13470,"text":"Conservation Science Partners","active":true,"usgs":false}],"preferred":false,"id":807333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amburgey, S M 0000-0002-7100-7811","orcid":"https://orcid.org/0000-0002-7100-7811","contributorId":245926,"corporation":false,"usgs":false,"family":"Amburgey","given":"S","email":"","middleInitial":"M","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":807334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Corn, PS","contributorId":245928,"corporation":false,"usgs":false,"family":"Corn","given":"PS","email":"","affiliations":[{"id":49365,"text":"Aldo Leopold Wilderness Research","active":true,"usgs":false}],"preferred":false,"id":807335,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201575,"text":"70201575 - 2018 - Land mollusks of the California Channel Islands: An overview of diversity, populations, and conservation status","interactions":[],"lastModifiedDate":"2020-12-16T16:16:07.072337","indexId":"70201575","displayToPublicDate":"2018-12-01T13:44:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Land mollusks of the California Channel Islands: An overview of diversity, populations, and conservation status","docAbstract":"The land snails and slugs have the highest level of endemism among all major animal groups on the California Channel Islands, with nearly 75% of the native terrestrial species confined to one or more of the 8 islands. In spite of this endemism, and in spite of the rarity of some species, the snails and slugs are one of the most poorly known groups. We present the first comprehensive overview of the land mollusk fauna of the Channel Islands, along with the results of recent intensive inventory studies. Surveys on San Clemente Island have increased the number of land mollusk species known from that island by 50%, and a single survey trip to Santa Rosa Island more than doubled the number of species known on that island. More additions to the land snail and slug fauna are certain for the poorly surveyed northern Channel Islands. This new information has provided insight into trends in species diversity and biogeographic patterns, with marked differences in species composition between the northern and southern islands. Our surveys to date suggest a strong link between the recovery of native vegetation on the islands and the population status of land snails and slugs, with substantially larger numbers of native mollusks on those islands that have been free of nonnative mammals the longest. Survey work is continuing, but it is clear that some very rare endemic snails and slugs on the islands merit specific management attention.
","language":"English","publisher":"Monte L. Bean Life Science Museum, Brigham Young University","doi":"10.3398/064.078.0419","usgsCitation":"Drost, C.A., Nekola, J.C., Roth, B., and Pearce, T.A., 2018, Land mollusks of the California Channel Islands: An overview of diversity, populations, and conservation status: Western North American Naturalist, v. 78, no. 4, p. 799-810, https://doi.org/10.3398/064.078.0419.","productDescription":"12 p.","startPage":"799","endPage":"810","ipdsId":"IP-088858","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488968,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarsarchive.byu.edu/wnan/vol78/iss4/29","text":"External Repository"},{"id":360479,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Channel Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.3282470703125,\n 32.79651010951669\n ],\n [\n -118.27880859375001,\n 33.37641235124676\n ],\n [\n -118.5369873046875,\n 33.52307880890422\n ],\n [\n -119.5147705078125,\n 34.102707993174874\n ],\n [\n -120.531005859375,\n 34.08906131584994\n ],\n [\n -120.3277587890625,\n 33.85673152928873\n ],\n [\n -119.54223632812501,\n 33.17434155100208\n ],\n [\n -118.4051513671875,\n 32.7503226078097\n ],\n [\n -118.3282470703125,\n 32.79651010951669\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c1a1532e4b0708288c23523","contributors":{"authors":[{"text":"Drost, Charles A. 0000-0002-4792-7095 charles_drost@usgs.gov","orcid":"https://orcid.org/0000-0002-4792-7095","contributorId":3151,"corporation":false,"usgs":true,"family":"Drost","given":"Charles","email":"charles_drost@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":754466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nekola, Jeffrey C.","contributorId":26214,"corporation":false,"usgs":false,"family":"Nekola","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":754467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roth, Barry","contributorId":211600,"corporation":false,"usgs":false,"family":"Roth","given":"Barry","email":"","affiliations":[{"id":38271,"text":"San Francisco, CA 94117, barry_roth@yahoo.com","active":true,"usgs":false}],"preferred":false,"id":754468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearce, Timothy A.","contributorId":211601,"corporation":false,"usgs":false,"family":"Pearce","given":"Timothy","email":"","middleInitial":"A.","affiliations":[{"id":38272,"text":"Carnegie Museum of Natural History, Pittsburgh, PA 15213, PearceT@carnegiemnh.org","active":true,"usgs":false}],"preferred":false,"id":754469,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201700,"text":"70201700 - 2018 - Building a response network to investigate potential pathogens associated with unionid mortality events","interactions":[],"lastModifiedDate":"2020-12-15T22:37:43.071724","indexId":"70201700","displayToPublicDate":"2018-12-01T13:41:45","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1492,"text":"Ellipsaria","active":true,"publicationSubtype":{"id":10}},"title":"Building a response network to investigate potential pathogens associated with unionid mortality events","docAbstract":"Unexplained mortality events have confounded the mussel conservation community for over 30 years. While the effects of chemical pollutants and environmental factors have been examined, few investigations have focused on the identification of potential mussel pathogens. Consequently, very little is known regarding the impact that pathogens have on freshwater mussel health, especially as they pertain to propagation efforts. There are several barriers that have hindered progress in the study of freshwater mussel disease, one of which is lack of appropriate diagnostic tools, and another is lack of guidance for field personnel regarding sampling procedures and laboratory contacts.
","language":"English","publisher":"Freshwater Mollusk Conservation Society","usgsCitation":"Leis, E., Waller, D.L., Knowles, S., Goldberg, T., Putnam, J.G., Richard, J., Erickson, S., Blevins, E., and Weinzinger, J., 2018, Building a response network to investigate potential pathogens associated with unionid mortality events: Ellipsaria, v. 20, no. 4, p. 44-45.","productDescription":"2 p.","startPage":"44","endPage":"45","ipdsId":"IP-103320","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":361031,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":360686,"type":{"id":15,"text":"Index Page"},"url":"https://molluskconservation.org/Ellipsaria-archive.html"}],"volume":"20","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Leis, Eric","contributorId":179325,"corporation":false,"usgs":false,"family":"Leis","given":"Eric","affiliations":[],"preferred":false,"id":754894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waller, Diane L. 0000-0002-6104-810X dwaller@usgs.gov","orcid":"https://orcid.org/0000-0002-6104-810X","contributorId":5272,"corporation":false,"usgs":true,"family":"Waller","given":"Diane","email":"dwaller@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":754893,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knowles, Susan 0000-0002-0254-6491 sknowles@usgs.gov","orcid":"https://orcid.org/0000-0002-0254-6491","contributorId":5254,"corporation":false,"usgs":true,"family":"Knowles","given":"Susan","email":"sknowles@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":754895,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldberg, Tony","contributorId":211788,"corporation":false,"usgs":false,"family":"Goldberg","given":"Tony","affiliations":[{"id":38319,"text":"UW Madison","active":true,"usgs":false}],"preferred":false,"id":754896,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Putnam, Joel G. 0000-0002-5464-4587 jgputnam@usgs.gov","orcid":"https://orcid.org/0000-0002-5464-4587","contributorId":5783,"corporation":false,"usgs":true,"family":"Putnam","given":"Joel","email":"jgputnam@usgs.gov","middleInitial":"G.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":754901,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Richard, Jordan","contributorId":211789,"corporation":false,"usgs":false,"family":"Richard","given":"Jordan","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":754897,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Erickson, Sarah","contributorId":211790,"corporation":false,"usgs":false,"family":"Erickson","given":"Sarah","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":754898,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blevins, Emilie","contributorId":211792,"corporation":false,"usgs":false,"family":"Blevins","given":"Emilie","email":"","affiliations":[{"id":38320,"text":"Xerxes Society, OR","active":true,"usgs":false}],"preferred":false,"id":754900,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Weinzinger, Jesse","contributorId":211791,"corporation":false,"usgs":false,"family":"Weinzinger","given":"Jesse","email":"","affiliations":[{"id":38155,"text":"WI DNR","active":true,"usgs":false}],"preferred":false,"id":754899,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70201688,"text":"70201688 - 2018 - Hourly analyses of the large storms and atmospheric rivers that provide most of California's precipitation in only 10 to 100 hours per year","interactions":[],"lastModifiedDate":"2018-12-21T13:29:21","indexId":"70201688","displayToPublicDate":"2018-12-01T13:29:16","publicationYear":"2018","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":"Hourly analyses of the large storms and atmospheric rivers that provide most of California's precipitation in only 10 to 100 hours per year","docAbstract":"California is regularly impacted by floods and droughts, primarily as a result of too many or too few atmospheric rivers (ARs). This study analyzes a two-decade-long hourly precipitation dataset from 176 California weather stations and a 3-hourly AR chronology to report variations in rainfall events across California and their association with ARs. On average, 10-40 and 60-120 hours of rainfall in southern and northern California, respectively, are responsible for more than half of annual rainfall accumulations. Approximately 10-30% of annual precipitation at locations across the state is from only one large storm. On average, northern California receives 25-45 rainfall events annually (40-50% of which are AR-related). These events typically have longer durations and higher event-precipitation totals than those in southern California. Northern California also receives more AR landfalls with longer durations and stronger Integrated Vapor Transport (IVT). On average, ARs contribute 79%, 76%, and 68% of extreme-rainfall accumulations (i.e., top 5% events annually) in the north coast, northern Sierra, and Transverse Ranges of southern California, respectively.
The San Francisco Bay Area terrain gap in the California Coast Range allows more AR water vapor to reach inland over the Delta and Sacramento Valley, and thus, influences precipitation in the Delta’s catchment. This is particularly important for extreme precipitation in the northern Sierra Nevada, including river basins above Oroville Dam and Shasta Dam.
This study highlights differences between rainfall and AR characteristics in coastal versus inland northern California, differences that largely determine the regional geography of flood risks and water-reliability. These analyses support water resource, flood, levee, wetland, and ecosystem management within the catchment of the San Francisco estuary system by describing regional characteristics of ARs and their influence on rainfall on an hourly timescale.
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Martin","contributorId":150276,"corporation":false,"usgs":false,"family":"Ralph","given":"F.","email":"","middleInitial":"Martin","affiliations":[{"id":17953,"text":"Earth Systems Research Lab, NOAA","active":true,"usgs":false}],"preferred":false,"id":754858,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oakley, Nina S.","contributorId":197885,"corporation":false,"usgs":false,"family":"Oakley","given":"Nina","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":754859,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rutz, Jonathan J.","contributorId":197886,"corporation":false,"usgs":false,"family":"Rutz","given":"Jonathan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":754860,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202320,"text":"70202320 - 2018 - Historical patterns of wildfire ignition sources in California ecosystems","interactions":[],"lastModifiedDate":"2019-02-22T13:01:08","indexId":"70202320","displayToPublicDate":"2018-12-01T13:01:03","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Historical patterns of wildfire ignition sources in California ecosystems","docAbstract":"State and federal agencies have reported fire causes since the early 1900s, explicitly for the purpose of helping land managers design fire-prevention programs. We document fire-ignition patterns in five homogenous climate divisions in California over the past 98 years on state Cal Fire protected lands and 107 years on federal United States Forest Service lands. Throughout the state, fire frequency increased steadily until a peak c. 1980, followed by a marked drop to 2016. There was not a tight link between frequency of ignition sources and area burned by those sources and the relationships have changed over time. Natural lightning-ignited fires were consistently fewer from north to south and from high to low elevation. Throughout most of the state, human-caused fires dominated the record and were positively correlated with population density for the first two-thirds of the record, but this relationship reversed in recent decades. We propose a mechanistic multi-variate model of factors driving fire frequency, where the importance of different factors has changed over time. Although ignition sources have declined markedly in recent decades, one notable exception is powerline ignitions. One important avenue for future fire-hazard reduction will be consideration of solutions to reduce this source of dangerous fires.
","language":"English","publisher":"International Association of Wildland Fire","doi":"10.1071/WF18026","usgsCitation":"Keeley, J.E., and Syphard, A.D., 2018, Historical patterns of wildfire ignition sources in California ecosystems: International Journal of Wildland Fire, v. 27, no. 12, p. 781-799, https://doi.org/10.1071/WF18026.","productDescription":"19 p.","startPage":"781","endPage":"799","ipdsId":"IP-095350","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468216,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wf18026","text":"Publisher Index Page"},{"id":361467,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"27","issue":"12","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":757820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Syphard, Alexandra D.","contributorId":8977,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":757821,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70201660,"text":"70201660 - 2018 - Remote sensing vegetation index methods to evaluate changes in greenness and evapotranspiration in riparian vegetation in response to the Minute 319 environmental pulse flow to Mexico","interactions":[],"lastModifiedDate":"2018-12-21T11:42:18","indexId":"70201660","displayToPublicDate":"2018-12-01T11:42:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5272,"text":"Proceedings of the International Association of Hydrological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing vegetation index methods to evaluate changes in greenness and evapotranspiration in riparian vegetation in response to the Minute 319 environmental pulse flow to Mexico","docAbstract":"During the spring of 2014, 130 million m3 of water were released from the United States' Morelos Dam on the lower Colorado River to Mexico, allowing water to reach the Gulf of California for the first time in 13 years. Our study assessed the effects of water transfer or ecological environmental flows from one nation to another, using remote sensing. Spatial applications for water resource evaluation are important for binational, integrated water resources management and planning for the Colorado River, which includes seven basin states in the US plus two states in Mexico. Our study examined the effects of the historic binational experiment (the Minute 319 agreement) on vegetative response along the riparian corridor. We used 250 m Moderate Resolution Imaging Spectroradiometer (MODIS), Enhanced Vegetation Index (EVI) and 30 m Landsat 8 satellite imagery to track evapotranspiration (ET) and the normalized difference vegetation index (NDVI). Our analysis showed an overall increase in NDVI and evapotranspiration (ET) in the year following the 2014 pulse, which reversed a decline in those metrics since the last major flood in 2000. NDVI and ET levels decreased in 2015, but were still significantly higher (P < 0.001) than pre-pulse (2013) levels. Preliminary findings show that the decline in 2015 persisted into 2016 and 2017. We continue to analyse results for 2018 in comparison to short-term (2013–2018) and long-term (2000–2018) trends. Our results support the conclusion that these environmental flows from the US to Mexico via the Minute 319 “pulse” had a positive, but short-lived (1 year), impact on vegetation growth in the delta.
","language":"English","publisher":"International Association of Hydrological Sciences","doi":"10.5194/piahs-380-45-2018","usgsCitation":"Nagler, P.L., Jarchow, C., and Glenn, E., 2018, Remote sensing vegetation index methods to evaluate changes in greenness and evapotranspiration in riparian vegetation in response to the Minute 319 environmental pulse flow to Mexico: Proceedings of the International Association of Hydrological Sciences, v. 380, p. 45-54, https://doi.org/10.5194/piahs-380-45-2018.","productDescription":"10 p.","startPage":"45","endPage":"54","ipdsId":"IP-097590","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468221,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/piahs-380-45-2018","text":"Publisher Index Page"},{"id":360670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","otherGeospatial":" Colorado River Delta","volume":"380","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-18","publicationStatus":"PW","scienceBaseUri":"5c1e0a30e4b0708288cb021b","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":754756,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarchow, Christopher J. 0000-0002-0424-4104","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":211737,"corporation":false,"usgs":false,"family":"Jarchow","given":"Christopher J.","affiliations":[{"id":38314,"text":"USGS Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":754757,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, Edward P.","contributorId":56542,"corporation":false,"usgs":false,"family":"Glenn","given":"Edward P.","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":754758,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201299,"text":"70201299 - 2018 - Biodiversity of amphibians and reptiles at the Camp Cady Wildlife Area, Mojave Desert, California and comparisons with other desert locations","interactions":[],"lastModifiedDate":"2018-12-11T11:12:48","indexId":"70201299","displayToPublicDate":"2018-12-01T11:12:43","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1153,"text":"California Fish and Game","active":true,"publicationSubtype":{"id":10}},"title":"Biodiversity of amphibians and reptiles at the Camp Cady Wildlife Area, Mojave Desert, California and comparisons with other desert locations","docAbstract":"We examined the biodiversity of amphibian and reptile species living in and near constructed ponds in the riparian area at the Camp Cady Wildlife Area (CCWA) in the Mojave Desert of San Bernardino County, California, based on field work from 1998-1999, 2016-2017, review of the literature, and searches for museum specimens using VertNet.org. A total of 11 species (201 captures), including two frogs and toads (one non-native frog), one turtle, three snakes, and five lizards were captured at terrestrial drift fences with pitfall traps encircling two ponds (0.5 hectares total) on the property in 1999. Four additional species (one frog, one lizard, and two snakes) were previously reported in 1978 from a ranch 1.6 km southwest from CCWA for a total of 15 species in the local area. The southwestern pond turtle (Actinemys pallida), was commonly observed at CCWA from 1998 to 1999 and documented as a breeding population. However, the species was extirpated at CCWA sometime after 2014 when the last individuals were photographed, and none have been detected since then despite significant efforts to do so. Biodiversity of amphibians and reptiles at CCWA is relatively low compared with sites elsewhere in the Mojave Desert with more elevational diversity. The 14 native species documented at CCWA accounts for approximately 21% of the native reptile and amphibian species reported by Stewart (1994) for the entire Mojave Desert, including peripheral species. Our smaller sample likely represents a group of easily detected species and is biased toward those found in or near water, especially amphibians. However, the relative proportion of amphibians vs. reptiles that inhabited CCWA in the last 40 years is not significantly different from the recently compiled proportions at five military installations in the California deserts. The herpetofauna inhabiting CCWA is notable for including riparian obligates like the western toad (Anaxyrus boreas), Northern Baja California treefrog (Pseudacris h. hypochondriaca), and A. pallida that are otherwise absent from large portions of the Mojave Desert. Other species are typical of those that are expected in the low-elevation creosote scrubdominated ecosystem in the area.
","language":"English","publisher":"California Department of Fish and Wildllife","usgsCitation":"Cummings, K.L., Puffer, S., Holmen, J.B., Wallace, J.K., Lovich, J.E., Meyer-Wilkins, K., Petersen, C., and Lovich, R.E., 2018, Biodiversity of amphibians and reptiles at the Camp Cady Wildlife Area, Mojave Desert, California and comparisons with other desert locations: California Fish and Game, v. 104, no. 3, p. 129-147.","productDescription":"19 p.","startPage":"129","endPage":"147","ipdsId":"IP-095405","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":360153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":360115,"type":{"id":15,"text":"Index Page"},"url":"https://nrm.dfg.ca.gov/Documents/ContextDocs.aspx?cat=OCEO-CFGJournal"}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.23486328125,\n 32.690243035492266\n ],\n [\n -114.49951171875,\n 32.690243035492266\n ],\n [\n -114.49951171875,\n 36.230981283477924\n ],\n [\n -118.23486328125,\n 36.230981283477924\n ],\n [\n -118.23486328125,\n 32.690243035492266\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"104","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a8e5e4b034bf6a7e4ddd","contributors":{"authors":[{"text":"Cummings, Kristy L. 0000-0002-8316-5059","orcid":"https://orcid.org/0000-0002-8316-5059","contributorId":202061,"corporation":false,"usgs":true,"family":"Cummings","given":"Kristy","email":"","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":753528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Puffer, Shellie R. 0000-0003-4957-0963","orcid":"https://orcid.org/0000-0003-4957-0963","contributorId":193099,"corporation":false,"usgs":true,"family":"Puffer","given":"Shellie R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":753529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holmen, Jenny B.","contributorId":211276,"corporation":false,"usgs":false,"family":"Holmen","given":"Jenny","email":"","middleInitial":"B.","affiliations":[{"id":38215,"text":"7400 Falls Creek Main, Durango, CO 81301, USA","active":true,"usgs":false}],"preferred":false,"id":753534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wallace, Jason K.","contributorId":211277,"corporation":false,"usgs":false,"family":"Wallace","given":"Jason","email":"","middleInitial":"K.","affiliations":[{"id":38216,"text":"California Desert Studies Consortium, Department of Biological Science, California State University, Fullerton, POB 490, Baker, CA 92309, USA","active":true,"usgs":false}],"preferred":false,"id":753535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":753530,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meyer-Wilkins, Kathie","contributorId":8742,"corporation":false,"usgs":false,"family":"Meyer-Wilkins","given":"Kathie","affiliations":[],"preferred":false,"id":753531,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Petersen, Chris","contributorId":211274,"corporation":false,"usgs":false,"family":"Petersen","given":"Chris","email":"","affiliations":[{"id":38213,"text":"Naval Facilities Engineering Command Atlantic, 6506 Hampton Blvd., Norfolk, VA 23508 USA (CP)","active":true,"usgs":false}],"preferred":false,"id":753532,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lovich, Robert E.","contributorId":211275,"corporation":false,"usgs":false,"family":"Lovich","given":"Robert","email":"","middleInitial":"E.","affiliations":[{"id":38214,"text":"Naval Facilities Engineering Command Southwest, 1220 Pacific Highway, San Diego, CA 92132, USA","active":true,"usgs":false}],"preferred":false,"id":753533,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70195184,"text":"70195184 - 2018 - Zone identification and oil saturation prediction in a waterflooded field: Residual oil zone, East Seminole Field, Texas, Permian Basin","interactions":[],"lastModifiedDate":"2019-03-27T10:18:50","indexId":"70195184","displayToPublicDate":"2018-12-01T10:18:41","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"displayTitle":"Zone Identification and Oil Saturation Prediction in a Waterflooded Field: Residual Oil Zone, East Seminole Field, Texas, Permian Basin","title":"Zone identification and oil saturation prediction in a waterflooded field: Residual oil zone, East Seminole Field, Texas, Permian Basin","docAbstract":"Recently, the miscible CO2-EOR tertiary process used in the main pay zone (MP) of suitable reservoirs has broadened to include exploitation of the underlying residual oil zone (ROZ) where a significant amount of oil may remain. The objective of this study is to identify the ROZ and to assess the remaining oil in a brownfield ROZ by using core data and conventional well logs with probabilistic and predictive methods.
Core and log data from three wells located in the East Seminole Field in Gaines County, Texas, were used to identify the MP and ROZ in the San Andres Limestone, and to predict oil saturations. The core measurements were used to calculate probabilistic in-situ oil saturations within the MP and the ROZ as a function of depth. Well logs, in combination with core data and calculated saturations, on the other hand, were used to develop two expert systems using artificial neural networks (ANN); one to identify the ROZ and MP, and the other to predict oil saturation. These systems were also supported by a classification and regression tree (CART) analysis to delineate the rules that lead to classifications of zones.
Results showed that expert systems developed and calibrated by combining core and well log data can identify MP and ROZ with a success score of more than 90%. Saturations within these zones can be predicted with a correlation coefficient of around 0.6 for testing and 0.8 for training data. The analyses showed that neutron porosity and density well log readings are the most influential ones to identify zones in this field and to predict oil saturations in the MP and ROZ. To explain the relationships of input data with the results, a rule-based system was also applied, which revealed the underlying petrophysical differences between MP and ROZ.
This new predictive approach using machine learning techniques, could potentially address the challenges that previous studies have come up against in defining the ROZ within the formation and quantifying remaining oil saturations. The method can potentially be applied to additional fields and help reliably identify the ROZ and estimate saturations for future resource evaluations.
A primary goal for Chesapeake Bay watershed restoration is to improve stream health and function in 10% of stream miles by 2025. Predictive spatial modeling of stream conditions, when accurate, is one method to fill gaps in monitoring coverage and estimate baseline conditions for restoration goals. Predictive modeling can also monitor progress as additional data become available. We developed a random forests model to predict biological condition of small streams (<200 km2 in drainage) in the Chesapeake Bay watershed. Biological condition was measured with the Chesapeake Bay Basin-wide Index of Biotic Integrity (Chessie BIBI), a stream macroinvertebrate index. Our goal was to predict biological condition in all unsurveyed small streams present in a 1:24,000 scale catchment layer as a 2004–2008 baseline. We reclassified the 5-category Chessie BIBI ratings into two categories, poor and fair/good, to align with management goals of the Chesapeake Bay Program. The model included 12 geospatial predictor variables including measures on spatial location, bioregion, land cover, soil, precipitation, and number of dams in local catchments. We trained the model with a random 75% subset of Chessie BIBI data (n = 1449), and used the remaining 25% of Chessie BIBI data (n = 484) as test data. The model performed well, correctly predicting 72% of samples in training data and 73% of samples in test data, but model accuracy varied among bioregions. We performed uncertainty analyses by adding bands of either ±0.05 or ±0.10 BIBI units to the cutoff between poor and fair/good. These uncertainty analyses resulted in 14.5% (±0.05 band) and 24.8% (±0.10 band) of samples in test data being classified as in uncertain condition. For 95,877 small stream reaches in the Chesapeake Bay watershed, the model predicted 64% in fair/good condition, the ±0.05 uncertainty analyses predicted 57% in fair/good condition, and the ±0.10 uncertainty analysis predicted 50% in fair/good condition. These reported values have different implications for the number of improved stream miles required to meet the goal of improving 10%. Incorporating uncertainty provides an assessment of model strength as well as confidence in predictions. We, therefore, suggest increased reporting of uncertainty in studies that spatially predict stream conditions.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/700701","usgsCitation":"Maloney, K.O., Smith, Z.M., Buchanan, C., Nagel, A., and Young, J.A., 2018, Predicting biological conditions for small headwater streams in the Chesapeake Bay watershed: Freshwater Science, v. 4, no. 37, p. 795-809, https://doi.org/10.1086/700701.","productDescription":"15 p.","startPage":"795","endPage":"809","ipdsId":"IP-094122","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":460801,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/700701","text":"Publisher Index Page"},{"id":362172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n 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M.","contributorId":214279,"corporation":false,"usgs":false,"family":"Smith","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":39005,"text":"ICPRB","active":true,"usgs":false}],"preferred":false,"id":759530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buchanan, Claire","contributorId":214280,"corporation":false,"usgs":false,"family":"Buchanan","given":"Claire","affiliations":[{"id":39005,"text":"ICPRB","active":true,"usgs":false}],"preferred":false,"id":759531,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nagel, Andrea","contributorId":214281,"corporation":false,"usgs":false,"family":"Nagel","given":"Andrea","email":"","affiliations":[{"id":39005,"text":"ICPRB","active":true,"usgs":false}],"preferred":false,"id":759532,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":759533,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227784,"text":"70227784 - 2018 - Comparing growth and body condition of indoor-reared, outdoor-reared, and direct-released juvenile Mojave desert tortoises","interactions":[],"lastModifiedDate":"2022-01-31T14:46:36.019542","indexId":"70227784","displayToPublicDate":"2018-12-01T08:40:57","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"title":"Comparing growth and body condition of indoor-reared, outdoor-reared, and direct-released juvenile Mojave desert tortoises","docAbstract":"Desert tortoise populations have declined, and head-starting hatchlings in captivity until they are larger and older — and presumably more likely to survive — is one strategy being evaluated for species recovery. Previous studies have reared hatchlings in outdoor, predator-proof pens for 5–9 years before release, in efforts to produce hatchlings in excess of 100–110 mm midline carapace length that are believed to be predation-resistant. We began a comparative study to evaluate indoor-rearing to shorten this rearing period by facilitating faster initial growth. We assigned 70 neonates from the 2015 hatching season to three treatment groups: 1) indoor-reared (n = 30), 2) outdoor-reared (n = 20), and 3) direct-release (n = 20). Direct-release hatchlings were released shortly after hatching in September 2015 and monitored 1–2x per week with radio telemetry. We head-started the indoor- and outdoor-reared treatment groups for 7 mo before releasing them in April 2016. Indoor-reared tortoises were fed 5x per week (Sep–Mar). Outdoor-reared tortoises had access to native forage and were given supplemental water and food once per week while active before winter dormancy. Indoor-reared tortoises grew >16x faster than direct-release tortoises and >8x faster than outdoor-reared tortoises. However, indoor-reared tortoises weighed less and had softer shells than comparatively sized older (3–4 year-old) tortoises raised outdoors. Increasing the duration of the indoor-rearing period or incorporating a combination of both indoor and later outdoor husbandry may increase shell hardness among head-starts, while retaining the growth-promoting effect of indoor rearing and shortening overall captivity duration.
","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Daly, J.A., Buhlman, K.A., Todd, B.D., Moore, C.T., Peaden, J., and Tuberville, T.D., 2018, Comparing growth and body condition of indoor-reared, outdoor-reared, and direct-released juvenile Mojave desert tortoises: Herpetological Conservation and Biology, v. 13, no. 3, p. 622-633.","productDescription":"12 p.","startPage":"622","endPage":"633","ipdsId":"IP-092840","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395130,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/contents_vol13_issue3.html"}],"country":"United States","state":"California","county":"San Bernardino County","otherGeospatial":"Mojave National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.8895263671875,\n 35.04798673426734\n ],\n [\n -115.34545898437499,\n 35.576916524038616\n ],\n [\n -116.0870361328125,\n 35.55010533588552\n ],\n [\n -116.378173828125,\n 35.15584570226544\n ],\n [\n -116.44958496093749,\n 34.84536693184101\n ],\n [\n -116.0211181640625,\n 34.58799745550482\n ],\n [\n -115.58166503906251,\n 34.538237527295756\n ],\n [\n -114.9444580078125,\n 34.66935854524543\n ],\n [\n -114.840087890625,\n 34.84987503195418\n ],\n [\n -114.8895263671875,\n 35.04798673426734\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Daly, J. A.","contributorId":272613,"corporation":false,"usgs":false,"family":"Daly","given":"J.","email":"","middleInitial":"A.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":832233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buhlman, K. A.","contributorId":272614,"corporation":false,"usgs":false,"family":"Buhlman","given":"K.","email":"","middleInitial":"A.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":832234,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Todd, B. D.","contributorId":272615,"corporation":false,"usgs":false,"family":"Todd","given":"B.","email":"","middleInitial":"D.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":832235,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832236,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peaden, J. M.","contributorId":272616,"corporation":false,"usgs":false,"family":"Peaden","given":"J. M.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":832237,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tuberville, T. D.","contributorId":272617,"corporation":false,"usgs":false,"family":"Tuberville","given":"T.","email":"","middleInitial":"D.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":832238,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201809,"text":"70201809 - 2018 - Estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data","interactions":[],"lastModifiedDate":"2019-01-30T16:10:17","indexId":"70201809","displayToPublicDate":"2018-11-30T15:18:46","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data","docAbstract":"Landscape carbon (C) flux estimates are necessary for assessing the ability of terrestrial ecosystems to buffer further increases in anthropogenic carbon dioxide (CO2) emissions. Advances in remote sensing have allowed for coarse-scale estimates of gross primary productivity (GPP) (e.g., MODIS 17), yet efforts to assess spatial patterns in respiration lag behind those of GPP. Here, we demonstrate a method to predict growing season soil respiration at a regional scale in a forested ecosystem. We related field measurements (n=144) of growing season soil respiration across subalpine forests in the Southern Rocky Mountains ecoregion to a suite of biophysical predictors with a Random Forest model (30 m pixel size). We found that Landsat Enhanced Vegetation Index (EVI), growing season AI, temperature, precipitation, elevation, and slope aspect explained spatiotemporal variability in soil respiration. Our model had a psuedo-r2 of 0.45 and root mean squared error (RMSE) of roughly one-quarter of the mean value of respiration. Predicted growing season soil respiration across the region was remarkably consistent across 2004, 2005 and 2006 (150-d averages of 542.8, 544.3, and 536.5 g C m-2, respectively). Yet, we observed substantial variability in spatial patterns of soil respiration predictions that varied between years, suggesting that our method is sensitive to changes in respiration drivers. We compared our estimates to MODIS GPP and nocturnal net ecosystem exchange (NEE) derived from eddy covariance towers as a proxy for ecosystem respiration. Averaged across the predictive region, mean predicted growing season soil respiration was 73% of MODIS GPP, while predicted soil respiration was generally within 20% of nocturnal NEE from eddy covariance towers. This study demonstrated that geospatial and remotely-sensed datasets can be used in a statistical modeling framework to estimate soil respiration at landscape scales.
","language":"English","publisher":"AGU","doi":"10.1029/2018JG004613","usgsCitation":"Berryman, E.M., Vanderhoof, M.K., Bradford, J.B., Hawbaker, T., Henne, P., Burns, S.P., Frank, J.M., Birdsey, R.A., and Ryan, M.G., 2018, Estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data: Journal of Geophysical Research G: Biogeosciences, v. 123, no. 10, p. 3231-3249, https://doi.org/10.1029/2018JG004613.","productDescription":"19 p.","startPage":"3231","endPage":"3249","ipdsId":"IP-097679","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":437667,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99TRHPB","text":"USGS data release","linkHelpText":"Data release for estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data"},{"id":360845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108,\n 39\n ],\n [\n -104,\n 39\n ],\n [\n -104,\n 41.5\n ],\n [\n -108,\n 41.5\n ],\n [\n -108,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"10","noUsgsAuthors":false,"publicationDate":"2018-10-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Berryman, Erin Michele 0000-0001-8699-2474 eberryman@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-2474","contributorId":5765,"corporation":false,"usgs":true,"family":"Berryman","given":"Erin","email":"eberryman@usgs.gov","middleInitial":"Michele","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":755441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":755442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":755443,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":755444,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":755445,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burns, Sean P.","contributorId":98921,"corporation":false,"usgs":true,"family":"Burns","given":"Sean","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":755446,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Frank, John M.","contributorId":11969,"corporation":false,"usgs":true,"family":"Frank","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":755447,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Birdsey, Richard A.","contributorId":17751,"corporation":false,"usgs":true,"family":"Birdsey","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":755448,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ryan, Michael G.","contributorId":202371,"corporation":false,"usgs":false,"family":"Ryan","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":33176,"text":"Rocky Mountain Research Station, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":755449,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70201136,"text":"70201136 - 2018 - Sewage loading and microbial risk in urban waters of the Great Lakes","interactions":[],"lastModifiedDate":"2018-11-30T15:08:37","indexId":"70201136","displayToPublicDate":"2018-11-30T15:07:27","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3888,"text":"Elementa: Science of the Anthropocene","active":true,"publicationSubtype":{"id":10}},"title":"Sewage loading and microbial risk in urban waters of the Great Lakes","docAbstract":"Despite modern sewer system infrastructure, the release of sewage from deteriorating pipes and sewer overflows is a major water pollution problem in US cities, particularly in coastal watersheds that are highly developed with large human populations. We quantified fecal pollution sources and loads entering Lake Michigan from a large watershed of mixed land use using host-associated indicators. Wastewater treatment plant influent had stable concentrations of human Bacteroides and human Lachnospiraceae with geometric mean concentrations of 2.77 × 107 and 5.94 × 107 copy number (by quantitative PCR) per 100 ml, respectively. Human-associated indicator levels were four orders of magnitude higher than norovirus concentrations, suggesting that these human-associated bacteria could be sensitive indicators of pathogen risk. Norovirus concentrations in these same samples were used in calculations for quantitative microbial risk assessment. Assuming a typical recreational exposure to untreated sewage in water, concentrations of 7,800 copy number of human Bacteroides per 100 mL or 14,000 copy number of human Lachnospiraceae per 100 mL corresponded to an illness risk of 0.03. These levels were exceeded in estuarine waters during storm events with greater than 5 cm of rainfall. Following overflows from combined sewer systems (which must accommodate both sewage and stormwater), concentrations were 10-fold higher than under rainfall conditions. Automated high frequency sampling allowed for loads of human-associated markers to be determined, which could then be related back to equivalent volumes of untreated sewage that were released. Evidence of sewage contamination decreased as ruminant-associated indicators increased approximately one day post-storm, demonstrating the delayed impact of upstream agricultural sources on the estuary. These results demonstrate that urban areas are a diffuse source of sewage contamination to urban waters and that storm-driven release of sewage, particularly when sewage overflows occur, creates a serious though transient human health risk.
","language":"English","publisher":"University of California Press","doi":"10.1525/elementa.301","usgsCitation":"McLellan, S.L., Sauer, E.P., Corsi, S., Bootsma, M.J., Boehm, A.B., Spencer, S.K., and Borchardt, M.A., 2018, Sewage loading and microbial risk in urban waters of the Great Lakes: Elementa: Science of the Anthropocene, v. 6, p. 1-15, https://doi.org/10.1525/elementa.301.","productDescription":"Article 46; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-096539","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":468225,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1525/elementa.301","text":"Publisher Index Page"},{"id":359858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Milwaukee River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.5,\n 42.9\n ],\n [\n -87.835693359375,\n 42.9\n ],\n [\n -87.835693359375,\n 43.7\n ],\n [\n -88.5,\n 43.7\n ],\n [\n -88.5,\n 42.9\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-20","publicationStatus":"PW","scienceBaseUri":"5c025a68e4b0815414cc782c","contributors":{"authors":[{"text":"McLellan, Sandra L. 0000-0003-3283-1151","orcid":"https://orcid.org/0000-0003-3283-1151","contributorId":210968,"corporation":false,"usgs":false,"family":"McLellan","given":"Sandra","email":"","middleInitial":"L.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":752869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauer, Elizabeth P.","contributorId":210969,"corporation":false,"usgs":false,"family":"Sauer","given":"Elizabeth","email":"","middleInitial":"P.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":752870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752868,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bootsma, Melinda J.","contributorId":210970,"corporation":false,"usgs":false,"family":"Bootsma","given":"Melinda","email":"","middleInitial":"J.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":752871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boehm, Alexandria B. 0000-0002-8162-5090","orcid":"https://orcid.org/0000-0002-8162-5090","contributorId":210971,"corporation":false,"usgs":false,"family":"Boehm","given":"Alexandria","email":"","middleInitial":"B.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":752872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spencer, Susan K.","contributorId":210972,"corporation":false,"usgs":false,"family":"Spencer","given":"Susan","email":"","middleInitial":"K.","affiliations":[{"id":38162,"text":"United States Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":752873,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Borchardt, Mark A. 0000-0002-6471-2627","orcid":"https://orcid.org/0000-0002-6471-2627","contributorId":210973,"corporation":false,"usgs":false,"family":"Borchardt","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":38162,"text":"United States Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":752874,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70200820,"text":"sir20185154 - 2018 - Groundwater-storage change and land-surface elevation change in Tucson Basin and Avra Valley, south-central Arizona--2003-2016","interactions":[],"lastModifiedDate":"2019-03-25T09:30:31","indexId":"sir20185154","displayToPublicDate":"2018-11-29T13:02:02","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5154","displayTitle":"Groundwater-Storage Change and Land-Surface Elevation Change in Tucson Basin and Avra Valley, South-Central Arizona—2003–2016","title":"Groundwater-storage change and land-surface elevation change in Tucson Basin and Avra Valley, south-central Arizona--2003-2016","docAbstract":"The U.S. Geological Survey monitors groundwater-storage change and land-surface elevation change caused by groundwater withdrawal in Tucson Basin and Avra Valley—the two most populated alluvial basins within the Tucson Active Management Area. The Tucson Active Management Area is one of five active management areas in Arizona established by the 1980 Groundwater Management Act and governed by the Arizona Department of Water Resources. Gravity and land-surface elevation change were monitored every 1 to 3 years at wells and benchmarks in Tucson Basin and Avra Valley from 2003 to 2016. Monitoring resulted in estimates of land-surface elevation change and groundwater-storage change. Interferometric synthetic aperture radar (InSAR) interferograms showing land-surface elevation change were constructed for the Tucson metropolitan area from (1) May 2003 to July 2006, (2) July 2006 to June 2008, (3) June 2008 to April 2011, (4) April 2011 to November 2014, and (5) November 2014 to March 2016. For the Tucson metropolitan area, maximum subsidence of about 2 inches occurred during May 2003 to July 2006. From July 2006 to June 2008, maximum subsidence of approximately 0.8 inches occurred in two regions in the Tucson metropolitan area. From June 2008 to April 2011, about 0.8 inches of subsidence also occurred in two regions. Additionally, for the period April 2011 to November 2014, a maximum of about 0.9 inches of subsidence occurred in the same two regions of Tucson Basin. For the entire monitoring period from May 2003 to March 2016, maximum subsidence of as much as 5.3 inches occurred in the Tucson metropolitan area south of Irvington Road between south 12th Avenue and south Park Avenue, and as much as 4 inches in central Tucson south of Broadway between Country Club Road and Craycroft Road. The InSAR data indicated that there was no significant land-surface deformation from 2003 to 2016 in Avra Valley, and no change in either basin from 2014 to 2016.
The volume of stored groundwater in the monitored part of Tucson Basin showed net zero change from spring 2003 to summer 2006. From summer 2006 to summer 2008 the volume of stored groundwater in the monitored part of Tucson Basin increased approximately 50,000 acre-feet; however, overdraft conditions resumed from summer 2008 to spring 2011, resulting in decreased storage of approximately 178,000 acre-feet. From spring 2011 to fall 2014, the volume of stored groundwater in Tucson Basin decreased about 200,000 acre-feet, following a period of lower than average rainfall in 2012 and 2013. The volume of stored groundwater in the monitored part of Tucson Basin increased approximately 167,000 acre-feet from fall 2014 to spring 2016.
Groundwater storage in Avra Valley increased during the entire monitoring period from spring 2003 to spring 2016, largely as a result of managed recharge of Central Arizona Project water in the monitored region. From 2003 to 2016, artificial recharge in Avra Valley totaled approximately 1,788,000 acre-feet, and in Tucson Basin artificial recharge for the entire period was about 636,790 acre-feet. Artificial recharge exceeded pumping in Avra Valley for each time interval. Pumping in Tucson Basin exceeded artificial recharge for every period except 2014 to 2016. Overall, long-term water-level declines have stabilized or reversed since 2000 at most areas in Tucson Basin and Avra Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185154","collaboration":"Prepared in cooperation with the Arizona Department of Water Resources, Pima County, Tucson Water, the Town of Oro Valley, the Town of Marana, and the Metropolitan Domestic Water Improvement District","usgsCitation":"Carruth, R.L., Kahler, L.M., and Conway, B.D., 2018, Groundwater-storage change and land-surface elevation change in Tucson Basin and Avra Valley, south-central Arizona—2003–2016: U.S. Geological Survey Scientific Investigations Report 2018–5154, 34 p., https://doi.org/10.3133/sir20185154.","productDescription":"vii, 34 p.","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-019853","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":359796,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5154/coverthb.jpg"},{"id":359797,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5154/sir20185154.pdf","text":"Report","size":"26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5154"}],"country":"United States","state":"Arizona","otherGeospatial":"Avra Valley, Tucson Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.5936279296875,\n 31.33311153820117\n ],\n [\n -110.44281005859375,\n 31.33311153820117\n ],\n [\n -110.44281005859375,\n 32.90726224488304\n ],\n [\n -111.5936279296875,\n 32.90726224488304\n ],\n [\n -111.5936279296875,\n 31.33311153820117\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719