Estimates of population characteristics of sport fishes inform fisheries management decisions and provide feedback on management strategies. Cheat Lake provides an unusual fishery in West Virginia because the hydropower reservoir supports a Yellow Perch Perca flavescens population. We estimated age structure, size structure, condition, total instantaneous mortality, growth, and summer diet for Cheat Lake Yellow Perch based on electrofishing collections in 2012. From 302 individuals, we observed a maximum age of 9 y. Maximum age, average size, and growth of females in the sample exceeded those of males. Cheat Lake Yellow Perch scored low on the relative weight index, but generally exhibited faster growth than other populations, even when compared by sex. Estimated annual survival was 0.63 (95% CI = 0.51–0.78), which is comparable to other exploited populations. These data support the presence of an ontogenetic diet shift from consumption of zooplankton to macroinvertebrates and fishes as Yellow Perch age. This study is the first evaluation we are aware of on Yellow Perch population characteristics in West Virginia, providing baseline data to enhance management decisions and direct future studies.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/012018-JFWM-007","usgsCitation":"Hilling, C., Taylor, N., Welsh, S.A., and Smith, D., 2018, Population characteristics of Yellow Perch in a central Appalachia hydropower reservoir: Journal of Fish and Wildlife Management, v. 9, no. 2, p. 486-495, https://doi.org/10.3996/012018-JFWM-007.","productDescription":"10 p.","startPage":"486","endPage":"495","ipdsId":"IP-093428","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468220,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/012018-jfwm-007","text":"Publisher Index Page"},{"id":395223,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Cheat Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.89978790283203,\n 39.658041943725856\n ],\n [\n -79.83352661132812,\n 39.658041943725856\n ],\n [\n -79.83352661132812,\n 39.71907125195918\n ],\n [\n -79.89978790283203,\n 39.71907125195918\n ],\n [\n -79.89978790283203,\n 39.658041943725856\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"2","noUsgsAuthors":false,"publicationDate":"2018-08-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Hilling, Corbin D.","contributorId":272977,"corporation":false,"usgs":false,"family":"Hilling","given":"Corbin D.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":832432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Nate D.","contributorId":272978,"corporation":false,"usgs":false,"family":"Taylor","given":"Nate D.","affiliations":[{"id":56173,"text":"West Virginia DNR","active":true,"usgs":false}],"preferred":false,"id":832433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":1483,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"swelsh@usgs.gov","middleInitial":"A.","affiliations":[{"id":205,"text":"Cooperative Research Units","active":false,"usgs":true}],"preferred":false,"id":832431,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Dustin M.","contributorId":272979,"corporation":false,"usgs":false,"family":"Smith","given":"Dustin M.","affiliations":[{"id":56173,"text":"West Virginia DNR","active":true,"usgs":false}],"preferred":false,"id":832434,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200961,"text":"ofr20181182 - 2018 - Fish behavior and abundance monitoring near a floating surface collector in North Fork Reservoir, Clackamas River, Oregon, using multi-beam acoustic imaging sonar","interactions":[],"lastModifiedDate":"2018-11-29T10:34:04","indexId":"ofr20181182","displayToPublicDate":"2018-11-28T12:59:22","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1182","displayTitle":"Fish behavior and abundance monitoring near a floating surface collector in North Fork Reservoir, Clackamas River, Oregon, Using Multi-Beam Acoustic Imaging Sonar","title":"Fish behavior and abundance monitoring near a floating surface collector in North Fork Reservoir, Clackamas River, Oregon, using multi-beam acoustic imaging sonar","docAbstract":"An imaging sonar was used to assess the behavior and abundance of fish sized the same as salmonid smolt and bull trout (Salvelinus confluentus) at the entrance to the juvenile fish floating surface collector (FSC) at North Fork Reservoir, Oregon. The purpose of the FSC is to collect downriver migrating juvenile salmonids (Chinook salmon [Oncorhynchus tshawytscha], Coho salmon [Oncorhynchus kisutch], and steelhead [Oncorhynchus mykiss]) at the North Fork Dam and to safely route them around the hydroelectric projects. The objective of the imaging sonar component of this study was to assess the behaviors of both smolt and predator-size fish (smolt [60–250 millimeter] and predator 350–650 [millimeter]) observed near the FSC and to determine if the presence of predator-size fish influenced the abundance of smolt-size fish. An imaging sonar was deployed near the entrance to the FSC during the spring smolt out-migration period. The imaging sonar technology was an informative tool for assessing abundance and spatial and temporal behaviors of both smolt and predator-size fish near the entrance of the FSC. Both smolt and predator-size fish were regularly observed near the entrance, with greater abundances observed during day than during night. Behavioral differences were also observed between the two fish-size classes, with smolt-size fish traveling straighter with more directed movement, and predator-size fish generally showing more milling behavior. Additionally, the presence of predator-size fish may be effecting the abundance and direction of travel of smolt-size fish, as counts of smolt-size fish were reduced in conjunction with the presence of predator-size fish and a greater proportion of smolt-size fish were observed traveling away from the FSC when predator-size fish were present than when predator-size fish were absent. Results of modeling potential predator-prey interactions and influences indicated that both the number of juvenile fish tracks and photoperiod had the strongest effects on the number of predator fish tracks, with more predator-size fish tracks observed as the number of smolt-size fish tracks increased. Overall, the results indicate that predator-size fish are present near the entrance of the FSC, concomitant with smolt-size fish, and their abundances and behaviors indicate that they may be drawn to the entrance of the FSC because of the abundance of prey-sized fish found there.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181182","collaboration":"Prepared in cooperation with Portland General Electric","usgsCitation":"Smith, C.D., Plumb J.M., and Adams, N.S. 2018, Fish behavior and abundance monitoring near a floating surface collector in North Fork Reservoir, Clackamas River, Oregon, using multi-beam acoustic imaging sonar: U.S. Geological Survey Open-File Report 2018-1182, 28 p., https://doi.org/10.3133/ofr20181182.","productDescription":"vi, 28 p.","onlineOnly":"Y","ipdsId":"IP-100791","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":359740,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1182/coverthb2.jpg"},{"id":359741,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1182/ofr20181182.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1182"}],"country":"United States","state":"Oregon","otherGeospatial":"North Fork Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.73376464843749,\n 45.0657615477031\n ],\n [\n -121.73263549804688,\n 45.0657615477031\n ],\n [\n -121.73263549804688,\n 45.45724086262233\n ],\n [\n -122.73376464843749,\n 45.45724086262233\n ],\n [\n -122.73376464843749,\n 45.0657615477031\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
Herbivores alter plant biodiversity (species richness) in many of the world’s ecosystems, but the magnitude and the direction of herbivore effects on biodiversity vary widely within and among ecosystems. One current theory predicts that herbivores enhance plant biodiversity at high productivity but have the opposite effect at low productivity. Yet, empirical support for the importance of site productivity as a mediator of these herbivore impacts is equivocal. Here, we synthesize data from 252 large-herbivore exclusion studies, spanning a 20-fold range in site productivity, to test an alternative hypothesis—that herbivore-induced changes in the competitive environment determine the response of plant biodiversity to herbivory irrespective of productivity. Under this hypothesis, when herbivores reduce the abundance (biomass, cover) of dominant species (for example, because the dominant plant is palatable), additional resources become available to support new species, thereby increasing biodiversity. By contrast, if herbivores promote high dominance by increasing the abundance of herbivory-resistant, unpalatable species, then resource availability for other species decreases reducing biodiversity. We show that herbivore-induced change in dominance, independent of site productivity or precipitation (a proxy for productivity), is the best predictor of herbivore effects on biodiversity in grassland and savannah sites. Given that most herbaceous ecosystems are dominated by one or a few species, altering the competitive environment via herbivores or by other means may be an effective strategy for conserving biodiversity in grasslands and savannahs globally.
","language":"English","publisher":"Nature","doi":"10.1038/s41559-018-0696-y","usgsCitation":"Koerner, S., Smith, M.D., Burkepile, D.E., Hanan, N.P., Avolio, M.L., Collins, S., Knapp, A., Lemoine, N.P., Forrestel, E.J., Eby, S., Thompson, D.I., Aguado-Santacruz, G.A., Anderson, J.P., Anderson, T.M., Angassa, A., Bagchi, S., Bakker, E.S., Bastin, G., Baur, L.E., Beard, K., Beever, E., Bohlen, P.J., Boughton, E.H., Canestro, D., Cesa, A., Chaneton, E., Cheng, J., D’Antonio, C.M., Deleglise, C., Dembele, F., Dorrough, J., Eldridge, D.J., Fernandez-Going, B., Fernandez-Lugo, S., Fraser, L.H., Freedman, B., Garcia-Salgado, G., Goheen, J.R., Guo, L., Husheer, S., Karembe, M., Knops, J.M., Kraaij, T., Kulmatiski, A., Kytoviita, M., Lezama, F., Loucougaray, G., Loydi, A., Milchunas, D.G., Milton, S.J., Morgan, J.W., Moxham, C., Nehring, K.C., Olff, H., Palmer, T.M., Rebollo, S., Riginos, C., Risch, A., Rueda, M., Sankaran, M., Sasaki, T., Schoenecker, K.A., Schultz, N.L., Schutz, M., Schwabe, A., Siebert, F., Smit, C., Stahlheber, K.A., Storm, C., Strong, D.J., Su, J., Tiruvaimozhi, Y.V., Tyler, C., Val, J., Vandegehuchte, M.L., Veblen, K.E., Vermeire, L., Ward, D., Wu, J., Young, T.P., Yu, Q., and Zelikova, T.J., 2018, Change in dominance determines herbivore effects on plant biodiversity: Nature Ecology & Evolution, v. 2, p. 1925-1932, https://doi.org/10.1038/s41559-018-0696-y.","productDescription":"8 p.","startPage":"1925","endPage":"1932","ipdsId":"IP-077293","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468263,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1038/s41559-018-0696-y","text":"External Repository"},{"id":359127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-29","publicationStatus":"PW","scienceBaseUri":"5bf67cf1e4b045bfcae2cfec","contributors":{"authors":[{"text":"Koerner, Sally E.","contributorId":208281,"corporation":false,"usgs":false,"family":"Koerner","given":"Sally E.","affiliations":[{"id":37771,"text":"Dept. of Integrative Biology, U. of S. 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Jishuai","contributorId":210429,"corporation":false,"usgs":false,"family":"Su","given":"Jishuai","email":"","affiliations":[],"preferred":false,"id":750688,"contributorType":{"id":1,"text":"Authors"},"rank":71},{"text":"Tiruvaimozhi, Yadugiri V.","contributorId":210430,"corporation":false,"usgs":false,"family":"Tiruvaimozhi","given":"Yadugiri","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":750689,"contributorType":{"id":1,"text":"Authors"},"rank":72},{"text":"Tyler, Claudia","contributorId":210431,"corporation":false,"usgs":false,"family":"Tyler","given":"Claudia","email":"","affiliations":[],"preferred":false,"id":750690,"contributorType":{"id":1,"text":"Authors"},"rank":73},{"text":"Val, James","contributorId":23007,"corporation":false,"usgs":true,"family":"Val","given":"James","email":"","affiliations":[],"preferred":false,"id":750691,"contributorType":{"id":1,"text":"Authors"},"rank":74},{"text":"Vandegehuchte, Martijn L.","contributorId":210432,"corporation":false,"usgs":false,"family":"Vandegehuchte","given":"Martijn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":750692,"contributorType":{"id":1,"text":"Authors"},"rank":75},{"text":"Veblen, Kari E.","contributorId":76872,"corporation":false,"usgs":false,"family":"Veblen","given":"Kari","email":"","middleInitial":"E.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":750693,"contributorType":{"id":1,"text":"Authors"},"rank":76},{"text":"Vermeire, Lance","contributorId":139806,"corporation":false,"usgs":false,"family":"Vermeire","given":"Lance","affiliations":[{"id":13278,"text":"USDA-ARS Fort Keogh LARRL. 243 Fort Keogh Road, Miles City, MT","active":true,"usgs":false}],"preferred":false,"id":750694,"contributorType":{"id":1,"text":"Authors"},"rank":77},{"text":"Ward, David","contributorId":140493,"corporation":false,"usgs":false,"family":"Ward","given":"David","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":750695,"contributorType":{"id":1,"text":"Authors"},"rank":78},{"text":"Wu, Jianshuang","contributorId":210433,"corporation":false,"usgs":false,"family":"Wu","given":"Jianshuang","email":"","affiliations":[],"preferred":false,"id":750696,"contributorType":{"id":1,"text":"Authors"},"rank":79},{"text":"Young, Truman P.","contributorId":210434,"corporation":false,"usgs":false,"family":"Young","given":"Truman","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":750697,"contributorType":{"id":1,"text":"Authors"},"rank":80},{"text":"Yu, Qiang","contributorId":104821,"corporation":false,"usgs":true,"family":"Yu","given":"Qiang","email":"","affiliations":[],"preferred":false,"id":750698,"contributorType":{"id":1,"text":"Authors"},"rank":81},{"text":"Zelikova, Tamara J.","contributorId":76615,"corporation":false,"usgs":true,"family":"Zelikova","given":"Tamara","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":750699,"contributorType":{"id":1,"text":"Authors"},"rank":82}]}} ,{"id":70249766,"text":"70249766 - 2018 - Factors affecting gray wolf (Canis lupus) encounter rate with elk (Cervus elaphus) in Yellowstone National Park","interactions":[],"lastModifiedDate":"2023-10-27T11:43:48.072488","indexId":"70249766","displayToPublicDate":"2018-10-27T06:41:29","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Factors affecting gray wolf (Canis lupus) encounter rate with elk (Cervus elaphus) in Yellowstone National Park","docAbstract":"Despite encounter rates being a key component of kill rate, few studies of large carnivore predation have quantified encounter rates with prey, the factors that influence them, and the relationship between encounter rate and kill rate. The study’s primary motivation was to determine the relationship between prey density and encounter rate in understanding the mechanism behind the functional response. Elk (Cervus elaphus Linnaeus, 1758) population decline and variable weather in northern Yellowstone National Park provided an opportunity to examine how these factors influenced wolf (Canis lupus Linnaeus, 1758) encounter rates with elk. We explored how factors associated with wolf kill rate and encounter rate in other systems (season, elk density, elk group density, average elk group size, snow depth, wolf pack size, and territory size) influenced wolf–elk encounter rate in Yellowstone National Park. Elk density was the only factor significantly correlated with wolf–elk encounter rate, and we found a nonlinear density-dependent relationship that may be a mechanism for a functional response in this system. Encounter rate was correlated with number of elk killed during early winter but not late winter. Weak effects of snow depth and elk group size on encounter rate suggest that these factors influence kill rate via hunting success because kill rate is the product of hunting success and encounter rate.
Lead mining first began in the Big River watershed during the 1700s. Lead was the primary metal mined throughout most of the 1700s and early 1800s and it continued to be mined until the mid-1900s. Barite mining began in the middle part of the watershed in the mid- to late 1800s. Although considerable attention has been given to concentrations of miningrelated trace elements (mostly cadmium, lead, and zinc) in the Big River and its tributaries draining the Old Lead Belt, there is less information regarding concentrations of mining-related trace elements in tributaries draining the Barite District in southeast Missouri, which is downstream from the Old Lead Belt, and the contribution of sediment transported from this district to trace elements in lower reaches of the Big River. The purpose of this report is to present results of an investigation of the distribution of mining-related trace elements in sediments in the middle reach of the Big River downstream from the Old Lead Belt and the Big River tributaries that drain a large part of the Barite District.
In general, concentrations of cadmium and lead in streambed sediment were largest in samples from the Big River and smallest in Barite District tributary samples. Concentrations of zinc were somewhat similar in the Big River and Barite District tributaries; however, higher concentrations were present in upstream Big River site samples, as well as in samples from one site on Maddin Creek and at another site on Old Mines Creek that drains the Barite District. Barium concentrations were considerably larger in samples from Barite District tributaries compared to samples collected on the Big River. Samples collected downstream from the Barite District on the Big River had considerably larger barium concentrations than samples collected upstream from the Barite District.
Flood-plain core samples were collected from 26 cores at 5 transect locations along tributaries in the Barite District. Of the individual 693 bulk (unsieved) samples from these cores analyzed by x-ray fluorescence, the probable effects concentration (PEC) values were exceeded for cadmium (PEC of 4.98 milligrams per kilogram [mg/kg], 218 samples), lead (PEC of 128 mg/kg, 91 samples), nickel (PEC of 48.6 mg/kg, 45 samples), and zinc (PEC of 459 mg/kg, 77 samples). Of the 693 samples, 21 exceeded the U.S. Environmental Protection Agency residential yard cleanup level of 400 mg/kg for lead; 19 of these were samples from a single transect near the mouth of Mineral Fork Creek where its flood plain joins the Big River flood plain.
Shortly after the December 2015 flood on the Big River (the third largest flood along the river since the 1950s), 23 samples of fine sediment deposited from the flood were collected from the Big River flood plain upstream and downstream from the Barite District and several tributaries. Overall, the general pattern of barium, lead, and zinc concentrations in the 2015 flood sediment samples was similar to that observed in the streambed-sediment samples.
Overall concentrations of barium were larger at Big River sites downstream from the Barite District, and cadmium, lead, and zinc concentrations were generally similar or smaller at sites downstream from the Barite District when compared to sites upstream from the Barite District. These data indicate a substantial influx of barium from the Barite District into the Big River but only a minimal influx of cadmium, lead, and zinc.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185103","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Smith, D.C., and Schumacher, J.G., 2018, Distribution of mining-related trace elements in streambed and flood-plain sediment along the middle Big River and tributaries in the Southeast Missouri Barite District, 2012–15: U.S. Geological Survey Scientific Investigations Report 2018–5103, 89 p., https://doi.org/10.3133/sir20185103.","productDescription":"Report: vii, 89 p.; Data Release","numberOfPages":"102","onlineOnly":"Y","ipdsId":"IP-090502","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":357852,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5103/sir20185103.pdf","text":"Report","size":"4.85 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5103"},{"id":357851,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5103/coverthb2.jpg"},{"id":357853,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OFYN3C","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Concentrations of Major and Trace Elements in Streambed and Floodplain Sediment along the Middle Big River and Tributaries in the Southeast Missouri Barite District and in Quality-Assurance Samples, 2012–15"}],"country":"United States","state":"Missouri","otherGeospatial":"Middle Big River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91,\n 37.5\n ],\n [\n -90,\n 37.5\n ],\n [\n -90,\n 38.5\n ],\n [\n -91,\n 38.5\n ],\n [\n -91,\n 37.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Aquatic invasive species (AIS) have spread throughout the United States via major rivers and tributaries. Locks and dams positioned along affected waterways, specifically lock chambers, are being evaluated as potential management sites to prevent further expansion into new areas. Recent research has shown that infusion of chemicals (e.g., carbon dioxide) into water can block or kill several invasive organisms and could be a viable option at navigational structures such as lock chambers because chemical infusion would not interfere with vessel passage or lock operation. Chemical treatments near lock structures will require large-scale fluid-mechanic systems and significant energy. Mixing must extend to all stagnation regions within a lock structure to prevent the passage of an invasive fish. This work describes the performance of both wall- and floor-based CO2-infused-water to water injection manifolds targeted for lock structures in terms of mixing time, mixing homogeneity, injection efficiency, and operational power requirements. Both systems have strengths and weaknesses so selection recommendations are given for applications such as open systems and closed systems.
","language":"English","publisher":"ASME","doi":"10.1115/1.4041361","usgsCitation":"Zolper, T.J., Cupp, A.R., and Smith, D.L., 2018, Investigating the mixing efficiencies of liquid-to-liquid chemical injection manifolds for aquatic invasive species management: Journal of Fluids Engineering, v. 141, no. 3, p. 1-14, https://doi.org/10.1115/1.4041361.","productDescription":"Article 031302; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-091100","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437722,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93J4EQ8","text":"USGS data release","linkHelpText":"Investigating the mixing efficiencies of liquid-to-liquid chemical injection manifolds for aquatic invasive species management:Data"},{"id":358968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"141","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-04","publicationStatus":"PW","scienceBaseUri":"5c10a92fe4b034bf6a7e5059","contributors":{"authors":[{"text":"Zolper, Thomas J.","contributorId":210258,"corporation":false,"usgs":false,"family":"Zolper","given":"Thomas","email":"","middleInitial":"J.","affiliations":[{"id":38093,"text":"University of Wisconsin - Platteville","active":true,"usgs":false}],"preferred":false,"id":750289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":750288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, David L.","contributorId":192711,"corporation":false,"usgs":false,"family":"Smith","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":750290,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228034,"text":"70228034 - 2018 - Spatial and temporal variability of myxozoan parasite, Myxobolus inornatus, prevalence in young of the year smallmouth bass in the Susquehanna River Basin, Pennsylvania","interactions":[],"lastModifiedDate":"2022-02-03T16:29:04.426671","indexId":"70228034","displayToPublicDate":"2018-08-17T10:24:20","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2286,"text":"Journal of Fish Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatial and temporal variability of myxozoan parasite, Myxobolus inornatus, prevalence in young of the year smallmouth bass in the Susquehanna River Basin, Pennsylvania","title":"Spatial and temporal variability of myxozoan parasite, Myxobolus inornatus, prevalence in young of the year smallmouth bass in the Susquehanna River Basin, Pennsylvania","docAbstract":"A myxozoan parasite, Myxobolus inornatus, is one disease agent identified in young of the year (YOY) smallmouth bass in the Susquehanna River Basin, Pennsylvania. We investigated spatial and temporal variability in M. Inornatus prevalence across the Susquehanna River Basin and at several out-of-basin sites. We examined potential land use drivers of M. Inornatus prevalence including agricultural and developed land use. In 1,267 YOY smallmouth bass collected from 32 sites during 2013–2016, M. Inornatus was documented in 43.6% of samples. Among-site variability in parasite prevalence was greater than among-year variability. The effect of agricultural land use on M. Inornatus prevalence had a high probability of being positively correlated at multiple spatial scales (probability of positive effect > 0.80). The effect of developed land use on M. Inornatus prevalence had a relatively high probability of being negatively correlated at multiple spatial scales (probability of negative effect > 0.70). Our results suggest that land use practices could be related to M. Inornatus infection of smallmouth bass. Further study will be necessary to determine whether disease dynamics are a consequence of effects on the host, alterations of instream habitat mediating invertebrate host dynamics and/or survival and dispersal of the parasite infective stage.
","language":"English","publisher":"Wiley","doi":"10.1111/jfd.12878","usgsCitation":"Schall, M.K., Blazer, V., Walsh, H., Smith, G.D., Wertz, T., and Wagner, T., 2018, Spatial and temporal variability of myxozoan parasite, Myxobolus inornatus, prevalence in young of the year smallmouth bass in the Susquehanna River Basin, Pennsylvania: Journal of Fish Diseases, v. 41, no. 11, p. 1689-1700, https://doi.org/10.1111/jfd.12878.","productDescription":"12 p.","startPage":"1689","endPage":"1700","ipdsId":"IP-096825","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Susquehanna River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.2393798828125,\n 39.73676229957947\n ],\n [\n -74.7894287109375,\n 39.73676229957947\n ],\n [\n -74.7894287109375,\n 41.88592102814744\n ],\n [\n -77.2393798828125,\n 41.88592102814744\n ],\n [\n -77.2393798828125,\n 39.73676229957947\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"11","noUsgsAuthors":false,"publicationDate":"2018-08-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Schall, Megan K.","contributorId":274359,"corporation":false,"usgs":false,"family":"Schall","given":"Megan","email":"","middleInitial":"K.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":832935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":832937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, Heather L.","contributorId":274360,"corporation":false,"usgs":false,"family":"Walsh","given":"Heather L.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":832938,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Geoffrey D.","contributorId":274361,"corporation":false,"usgs":false,"family":"Smith","given":"Geoffrey","email":"","middleInitial":"D.","affiliations":[{"id":36966,"text":"Pennsylvania Fish and Boat Commission","active":true,"usgs":false}],"preferred":false,"id":832939,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wertz, Timothy","contributorId":274363,"corporation":false,"usgs":false,"family":"Wertz","given":"Timothy","affiliations":[{"id":56607,"text":"Pennsylvania Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":832940,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832936,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198666,"text":"70198666 - 2018 - Estimating distemper virus dynamics among wolves and grizzly bears using serology and Bayesian state‐space models","interactions":[],"lastModifiedDate":"2018-09-28T09:07:15","indexId":"70198666","displayToPublicDate":"2018-08-14T14:12:42","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Estimating distemper virus dynamics among wolves and grizzly bears using serology and Bayesian state‐space models","docAbstract":"Many parasites infect multiple hosts, but estimating the transmission across host species remains a key challenge in disease ecology. We investigated the within and across host species dynamics of canine distemper virus (CDV) in grizzly bears (Ursus arctos) and wolves (Canis lupus) of the Greater Yellowstone Ecosystem (GYE). We hypothesized that grizzly bears may be more likely to be exposed to CDV during outbreaks in the wolf population because grizzly bears often displace wolves while scavenging carcasses. We used serological data collected from 1984 to 2014 in conjunction with Bayesian state‐space models to infer the temporal dynamics of CDV. These models accounted for the unknown timing of pathogen exposure, and we assessed how different testing thresholds and the potential for testing errors affected our conclusions. We identified three main CDV outbreaks (1999, 2005, and 2008) in wolves, which were more obvious when we used higher diagnostic thresholds to qualify as seropositive. There was some evidence for increased exposure rates in grizzly bears in 2005, but the magnitude of the wolf effect on bear exposures was poorly estimated and depended upon our prior distributions. Grizzly bears were exposed to CDV prior to wolf reintroduction and during time periods outside of known wolf outbreaks, thus wolves are only one of several potential routes for grizzly bear exposures. Our modeling approach accounts for several of the shortcomings of serological data and is applicable to many wildlife disease systems, but is most informative when testing intervals are short. CDV circulates in a wide range of carnivore species, but it remains unclear whether the disease persists locally within the GYE carnivore community or is periodically reintroduced from distant regions with larger host populations.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4396","usgsCitation":"Cross, P.C., van Manen, F.T., Viana, M., Almberg, E.S., Bachen, D., Brandell, E.E., Haroldson, M.A., Hudson, P.J., Stahler, D.R., and Smith, D.W., 2018, Estimating distemper virus dynamics among wolves and grizzly bears using serology and Bayesian state‐space models: Ecology and Evolution, v. 8, no. 17, p. 8726-8735, https://doi.org/10.1002/ece3.4396.","productDescription":"10 p.","startPage":"8726","endPage":"8735","ipdsId":"IP-094527","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468497,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4396","text":"Publisher Index Page"},{"id":356446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.137451171875,\n 42.147114459220994\n ],\n [\n -108.6328125,\n 42.147114459220994\n ],\n [\n -108.6328125,\n 45.65244828675087\n ],\n [\n -112.137451171875,\n 45.65244828675087\n ],\n [\n -112.137451171875,\n 42.147114459220994\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"17","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-05","publicationStatus":"PW","scienceBaseUri":"5b98a287e4b0702d0e842f3f","contributors":{"authors":[{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":742402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":742403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Viana, Mafalda 0000-0001-5975-6505","orcid":"https://orcid.org/0000-0001-5975-6505","contributorId":207013,"corporation":false,"usgs":false,"family":"Viana","given":"Mafalda","email":"","affiliations":[{"id":37430,"text":"Glasgow University","active":true,"usgs":false}],"preferred":false,"id":742404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Almberg, Emily S.","contributorId":207014,"corporation":false,"usgs":false,"family":"Almberg","given":"Emily","email":"","middleInitial":"S.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":742405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bachen, Daniel","contributorId":207015,"corporation":false,"usgs":false,"family":"Bachen","given":"Daniel","email":"","affiliations":[{"id":36895,"text":"Montana Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":742406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brandell, Ellen E. 0000-0002-2698-7013","orcid":"https://orcid.org/0000-0002-2698-7013","contributorId":207016,"corporation":false,"usgs":false,"family":"Brandell","given":"Ellen","email":"","middleInitial":"E.","affiliations":[{"id":25381,"text":"Penn State Univ.","active":true,"usgs":false}],"preferred":false,"id":742407,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":742408,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hudson, Peter J.","contributorId":192149,"corporation":false,"usgs":false,"family":"Hudson","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":742409,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stahler, Daniel R.","contributorId":179180,"corporation":false,"usgs":false,"family":"Stahler","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":742410,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Douglas W.","contributorId":207018,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas","email":"","middleInitial":"W.","affiliations":[{"id":37432,"text":"Yellowstone National Park","active":true,"usgs":false}],"preferred":false,"id":742411,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70201150,"text":"70201150 - 2018 - Temporal evaluation of estrogenic endocrine disruption markers in smallmouth bass (Micropterus dolomieu) reveals seasonal variability in intersex","interactions":[],"lastModifiedDate":"2018-12-03T08:41:54","indexId":"70201150","displayToPublicDate":"2018-07-26T08:19:01","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Temporal evaluation of estrogenic endocrine disruption markers in smallmouth bass (Micropterus dolomieu) reveals seasonal variability in intersex","title":"Temporal evaluation of estrogenic endocrine disruption markers in smallmouth bass (Micropterus dolomieu) reveals seasonal variability in intersex","docAbstract":"A reconnaissance project completed in 2009 identified intersex and elevated plasma vitellogenin in male smallmouth bass inhabiting the Missisquoi River, VT. In an attempt to identify the presence and seasonality of putative endocrine disrupting chemicals or other factors associated with these observations, a comprehensive reevaluation was conducted between September 2012 and June 2014. Here, we collected smallmouth bass from three physically partitioned reaches along the river to measure biomarkers of estrogenic endocrine disruption in smallmouth bass. In addition, polar organic chemical integrative samples (POCIS) were deployed to identify specific chemicals associated with biological observations. We did not observe biological differences across reaches indicating the absence of clear point source contributions to the observation of intersex. Interestingly, intersex prevalence and severity decreased in a stepwise manner over the timespan of the project. Intersex decreased from 92.8% to 28.1%. The only significant predictor of intersex prevalence was year of capture, based on logistic regression analysis. The mixed model of fish length and year-of-capture best predicted intersex severity. Intersex severity was also significantly different across late summer and early spring collections indicating seasonal changes in this metric. Plasma vitellogenin and liver vitellogenin Aa transcript abundance in males did not indicate exposure to estrogenic endocrine disrupting chemicals at any of the four sample collections. Analysis of chemicals captured by the POCIS as well as results of screening discrete water samples or POCIS extracts did not indicate the contribution of appreciable estrogenic chemicals. It is possible that unreported changes in land-use activity have ameliorated the problem, and our observations indicate recovery. Regardless, this work clearly emphasizes that single, snap shot sampling for intersex may not yield representative data given that the manifestation of this condition within a population can change dramatically over time.
","language":"English","publisher":"Elsever","doi":"10.1016/j.scitotenv.2018.07.167","usgsCitation":"Iwanowicz, L.R., Pinkney, A., Guy, C., Major, A., Munney, K., Blazer, V., Alvarez, D., Walsh, H.L., Sperry, A.J., Sanders, L., and Smith, D., 2018, Temporal evaluation of estrogenic endocrine disruption markers in smallmouth bass (Micropterus dolomieu) reveals seasonal variability in intersex: Science of the Total Environment, v. 646, p. 245-256, https://doi.org/10.1016/j.scitotenv.2018.07.167.","productDescription":"12 p.","startPage":"245","endPage":"256","ipdsId":"IP-095285","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":359860,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Missisquoi River","volume":"646","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c064ee3e4b0815414cecb10","contributors":{"authors":[{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":190787,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke","email":"liwanowicz@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":752925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pinkney, A.E.","contributorId":150385,"corporation":false,"usgs":false,"family":"Pinkney","given":"A.E.","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":752926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guy, C.P.","contributorId":22983,"corporation":false,"usgs":true,"family":"Guy","given":"C.P.","email":"","affiliations":[],"preferred":false,"id":752927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Major, A.M.","contributorId":150387,"corporation":false,"usgs":false,"family":"Major","given":"A.M.","email":"","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":752928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Munney, K.","contributorId":150388,"corporation":false,"usgs":false,"family":"Munney","given":"K.","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":752929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":752930,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Alvarez, David 0000-0002-6918-2709 dalvarez@usgs.gov","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":150499,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","email":"dalvarez@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":752931,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":752932,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sperry, Adam J. 0000-0002-4815-3730 asperry@usgs.gov","orcid":"https://orcid.org/0000-0002-4815-3730","contributorId":5872,"corporation":false,"usgs":true,"family":"Sperry","given":"Adam","email":"asperry@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":752933,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sanders, Lakyn R. lsanders@usgs.gov","contributorId":5714,"corporation":false,"usgs":true,"family":"Sanders","given":"Lakyn R.","email":"lsanders@usgs.gov","affiliations":[],"preferred":true,"id":752934,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Smith, D. R. 0000-0001-6074-9257","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":44108,"corporation":false,"usgs":true,"family":"Smith","given":"D. R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":752935,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70246645,"text":"70246645 - 2018 - BioTIME: A database of biodiversity time series for the Anthropocene","interactions":[],"lastModifiedDate":"2023-07-25T20:22:32.607753","indexId":"70246645","displayToPublicDate":"2018-07-24T08:23:31","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"BioTIME: A database of biodiversity time series for the Anthropocene","docAbstract":"The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.
The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.
BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).
BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.
BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.
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A combination of cameras and water-quality monitoring equipment was used to assess the frequency and duration of blooms and their effects on water quality. A surveillance camera captured color images every 15 minutes during daylight hours of the northwestern corner of Willow Creek Reservoir, where surface blooms tend to accumulate due to the prevailing summer winds. In 2015, a water-quality instrument was deployed in the northwestern corner of the reservoir to continuously measure water temperature, pH, dissolved oxygen, specific conductance, turbidity, total chlorophyll, and the blue-green algae pigment phycocyanin. In 2016, a water-quality instrument was used to collect measurements along transects throughout the reservoir to create spatial maps of water quality. The spatially integrated mapping process was repeated on three different days under varying algal conditions. Also in 2016, a telemetry connection was established allowing resource managers to view the reservoir images in near-real time.
Results from 2015 indicate that surface accumulations of cyanobacteria can form and dissipate within minutes in the reservoir, and that blooms can cause substantial changes to water quality. A persistent cyanobacterial bloom in August and September 2015 resulted in pH values of 9.5 standard units, 220 percent oxygen saturation, and pronounced increases in turbidity and total chlorophyll. The stationary water-quality instrument collected data during periods with and without blooms, increasing our understanding of the effects of blooms on water quality and revealing potential restoration benchmarks for the freshwater reservoir. The spatially integrated mapping data showed the variation in water quality across the reservoir that occurs during blooms and baseline conditions and indicated regions of the reservoir to focus restoration efforts. Additional spatial data collection can be timed to collect daily extremes.
The camera deployment in 2016 demonstrated that telemetering images from remote sites is possible and provides valuable and timely information. Monitoring with a surveillance camera is inexpensive and supplies data regarding surface-bloom presence or absence. The use of a camera can help target site visits to periods when blooms are observed, which may increase the accuracy of beginning and ending dates for water body closures.
Monitoring cyanobacterial blooms in Willow Creek Reservoir with multiple devices provided a more comprehensive dataset than any one monitoring method. The camera images showed when a surface bloom initiated and dissipated while the water-quality instrument revealed the magnitude, or potential severity, of the effects on water quality.
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2130 SW 5th Avenue
Portland, Oregon, 97201
We compare the thermophysical properties and particle sizes derived from the Mars Science Laboratory rover's Ground Temperature Sensor of the Bagnold dunes, specifically Namib dune, to those derived orbitally from Thermal Emission Imaging System, ultimately linking these measurements to ground truth particle sizes determined from Mars Hand Lens Imager images. In general, we find that all three datasets report consistent particle sizes for the Bagnold dunes (~110–350 μm and are within measurement and model uncertainties), indicating that particle sizes of homogeneous materials inferred from temperature measurements and thermophysical models are reliable. Furthermore, we examine the effects of two physical characteristics that could influence the modeled thermal inertia and particle sizes, including (1) fine‐scale (centimeter to meter scale) ripples and (2) thin layering of indurated/armored materials. To first order, we find that small‐scale ripples and thin (approximately centimeter scale) layers do not significantly affect the determination of bulk thermal inertia from orbital thermal data using a single nighttime temperature. Modeling of a layer of coarse or indurated material reveals that a thin layer (< ~5 mm; similar to what was observed by the Curiosity rover) would not significantly change the observed thermal properties of the surface and would be dominated by the properties of the underlying material. Thermal inertia and particle sizes of relatively homogeneous materials derived from nighttime orbital data should be considered as reliable, as long as there are no significant subpixel anisothermality effects (e.g., lateral mixing of multiple thermophysically distinct materials).
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2017JE005501","usgsCitation":"Edwards, C., Piqueux, S., Hamilton, V.E., Fergason, R.L., Herkenhoff, K., Vasavada, A.R., Bennett, K.A., Sacks, L., Lewis, K., and Smith, M.D., 2018, The thermophysical properties of the Bagnold Dunes, Mars: Ground truthing orbital data: Journal of Geophysical Research: Planets, v. 123, no. 5, p. 1307-1326, https://doi.org/10.1029/2017JE005501.","productDescription":"15 p.","startPage":"1307","endPage":"1326","ipdsId":"IP-085162","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":468722,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017je005501","text":"Publisher Index Page"},{"id":355551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Bagnold Dunes, Mars","volume":"123","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-31","publicationStatus":"PW","scienceBaseUri":"5b46e584e4b060350a15d1c0","contributors":{"authors":[{"text":"Edwards, Christopher S.","contributorId":206168,"corporation":false,"usgs":false,"family":"Edwards","given":"Christopher S.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":739692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Piqueux, Sylvain","contributorId":56986,"corporation":false,"usgs":false,"family":"Piqueux","given":"Sylvain","email":"","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":739693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hamilton, Victoria E.","contributorId":206169,"corporation":false,"usgs":false,"family":"Hamilton","given":"Victoria","email":"","middleInitial":"E.","affiliations":[{"id":37270,"text":"Southwest Research Institute, Boulder, Colo.","active":true,"usgs":false}],"preferred":false,"id":739694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fergason, Robin L. 0000-0002-2044-1714","orcid":"https://orcid.org/0000-0002-2044-1714","contributorId":206167,"corporation":false,"usgs":true,"family":"Fergason","given":"Robin","email":"","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":739691,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":206170,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":739695,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vasavada, Ashwin R.","contributorId":200409,"corporation":false,"usgs":false,"family":"Vasavada","given":"Ashwin","email":"","middleInitial":"R.","affiliations":[],"preferred":true,"id":739696,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bennett, Kristen A.","contributorId":206171,"corporation":false,"usgs":false,"family":"Bennett","given":"Kristen","email":"","middleInitial":"A.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":739697,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sacks, Leah","contributorId":206172,"corporation":false,"usgs":false,"family":"Sacks","given":"Leah","email":"","affiliations":[{"id":37271,"text":"Carelton College, Northfield, Minn.","active":true,"usgs":false}],"preferred":false,"id":739698,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lewis, Kevin","contributorId":195296,"corporation":false,"usgs":false,"family":"Lewis","given":"Kevin","affiliations":[],"preferred":false,"id":739699,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Michael D.","contributorId":206173,"corporation":false,"usgs":false,"family":"Smith","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":739700,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70197138,"text":"fs20183031 - 2018 - Klamath River Basin water-quality data","interactions":[],"lastModifiedDate":"2018-05-30T13:03:14","indexId":"fs20183031","displayToPublicDate":"2018-05-29T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3031","title":"Klamath River Basin water-quality data","docAbstract":"The Klamath River Basin stretches from the mountains and inland basins of south-central Oregon and northern California to the Pacific Ocean, spanning multiple climatic regions and encompassing a variety of ecosystems. Water quantity and water quality are important topics in the basin, because water is a critical resource for farming and municipal use, power generation, and for the support of wildlife, aquatic ecosystems, and endangered species. Upper Klamath Lake is the largest freshwater lake in Oregon (112 square miles) and is known for its seasonal algal blooms. The Klamath River has dams for hydropower and the upper basin requires irrigation water to support agriculture and grazing. Multiple species of endangered fish inhabit the rivers and lakes, and the marshes are key stops on the Pacific flyway for migrating birds. For these and other reasons, the water resources in this basin have been studied and monitored to support their management distribution.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183031","usgsCitation":"Smith, C.D., Rounds, S.A., and Orzol, L.L., 2018, Klamath River Basin water-quality data: U.S. Geological Survey Fact Sheet 2018-3031, 4 p., https://doi.org/10.3133/fs20183031.","productDescription":"4 p.","onlineOnly":"Y","ipdsId":"IP-096068","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":354491,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3031/fs20183031.pdf","text":"Report","size":"621 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3031"},{"id":354490,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3031/coverthb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath River Basin","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Understanding how wide-ranging animals use landscapes in which human use is highly heterogeneous is important for determining patterns of human–wildlife conflict and designing mitigation strategies. Here, we show how biological sign surveys in forested components of a human-dominated landscape can be combined with human interviews in agricultural portions of a landscape to provide a full picture of seasonal use of different landscape components by wide-ranging animals and resulting human–wildlife conflict. We selected Asian elephants (Elephas maximus) in Nepal to illustrate this approach. Asian elephants are threatened throughout their geographic range, and there are large gaps in our understanding of their landscape-scale habitat use. We identified all potential elephant habitat in Nepal and divided the potential habitat into sampling units based on a 10 km by 10 km grid. Forested areas within grids were surveyed for signs of elephant use, and local villagers were interviewed regarding elephant use of agricultural areas and instances of conflict. Data were analyzed using single-season and multi-season (dynamic) occupancy models. A single-season occupancy model applied to data from 139 partially or wholly forested grid cells estimated that 0.57 of grid cells were used by elephants. Dynamic occupancy models fit to data from interviews across 158 grid cells estimated that monthly use of non-forested, human-dominated areas over the preceding year varied between 0.43 and 0.82 with a minimum in February and maximum in October. Seasonal patterns of crop raiding by elephants coincided with monthly elephant use of human-dominated areas, and serious instances of human–wildlife conflict were common. Efforts to mitigate human–elephant conflict in Nepal are likely to be most effective if they are concentrated during August through December when elephant use of human-dominated landscapes and human–elephant conflict are most common.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/03949370.2017.1405847","usgsCitation":"Lamichhane, B.R., Subedi, N., Pokheral, C.P., Dhakal, M., Acharya, K.P., Pradhan, N.M., Smith, J.L., Malla, S., Thakuri, B.S., and Yackulic, C.B., 2018, Using interviews and biological sign surveys to infer seasonal use of forested and agricultural portions of a human-dominated landscape by Asian elephants in Nepal: Ethology Ecology and Evolution, v. 30, no. 4, p. 331-347, https://doi.org/10.1080/03949370.2017.1405847.","productDescription":"17 p.","startPage":"331","endPage":"347","ipdsId":"IP-082625","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":351344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Nepal","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[88.12044,27.87654],[88.04313,27.44582],[88.1748,26.81041],[88.06024,26.41462],[87.22747,26.3979],[86.02439,26.63098],[85.25178,26.7262],[84.67502,27.2349],[83.30425,27.36451],[81.99999,27.92548],[81.0572,28.4161],[80.08842,28.79447],[80.47672,29.72987],[81.11126,30.18348],[81.5258,30.42272],[82.32751,30.11527],[83.33712,29.46373],[83.89899,29.32023],[84.23458,28.83989],[85.01164,28.64277],[85.82332,28.20358],[86.95452,27.97426],[88.12044,27.87654]]]},\"properties\":{\"name\":\"Nepal\"}}]}","volume":"30","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-18","publicationStatus":"PW","scienceBaseUri":"5a7d6ffae4b00f54eb24418e","contributors":{"authors":[{"text":"Lamichhane, Babu Ram","contributorId":201694,"corporation":false,"usgs":false,"family":"Lamichhane","given":"Babu","email":"","middleInitial":"Ram","affiliations":[{"id":36232,"text":"National Trust for Nature Conservation, Khumaltar, POB 3712, Lalitpur, Nepal","active":true,"usgs":false}],"preferred":false,"id":726793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Subedi, Naresh","contributorId":201695,"corporation":false,"usgs":false,"family":"Subedi","given":"Naresh","email":"","affiliations":[{"id":36232,"text":"National Trust for Nature Conservation, Khumaltar, POB 3712, Lalitpur, Nepal","active":true,"usgs":false}],"preferred":false,"id":726794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pokheral, Chiranjibi Prasad","contributorId":201696,"corporation":false,"usgs":false,"family":"Pokheral","given":"Chiranjibi","email":"","middleInitial":"Prasad","affiliations":[{"id":36232,"text":"National Trust for Nature Conservation, Khumaltar, POB 3712, Lalitpur, Nepal","active":true,"usgs":false}],"preferred":false,"id":726795,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dhakal, Maheshwar","contributorId":201698,"corporation":false,"usgs":false,"family":"Dhakal","given":"Maheshwar","email":"","affiliations":[{"id":36233,"text":"Department of National Parks and Wildlife Conservation, Babarmahal, Kathmandu, Nepal","active":true,"usgs":false}],"preferred":false,"id":726797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Acharya, Krishna Prasad","contributorId":201699,"corporation":false,"usgs":false,"family":"Acharya","given":"Krishna","email":"","middleInitial":"Prasad","affiliations":[{"id":36233,"text":"Department of National Parks and Wildlife Conservation, Babarmahal, Kathmandu, Nepal","active":true,"usgs":false}],"preferred":false,"id":726798,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pradhan, Narendra Man Babu","contributorId":201700,"corporation":false,"usgs":false,"family":"Pradhan","given":"Narendra","email":"","middleInitial":"Man Babu","affiliations":[{"id":36234,"text":"Bird Conservation Nepal, Lazimpat, Kathmandu, Nepal (Work was done when he was with WWF Nepal, Baluwatar, Kathmandu, Nepal)","active":true,"usgs":false}],"preferred":false,"id":726799,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, James L. David","contributorId":201701,"corporation":false,"usgs":false,"family":"Smith","given":"James","email":"","middleInitial":"L. David","affiliations":[{"id":36235,"text":"Department of Fisheries, Wildlife and Conservation Biology, Minnesota University, MN, USA","active":true,"usgs":false}],"preferred":false,"id":726800,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Malla, Sabita","contributorId":201702,"corporation":false,"usgs":false,"family":"Malla","given":"Sabita","email":"","affiliations":[{"id":36236,"text":"WWF Nepal, Baluwatar, Kathmandu","active":true,"usgs":false}],"preferred":false,"id":726801,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thakuri, Bishnu Singh","contributorId":201697,"corporation":false,"usgs":false,"family":"Thakuri","given":"Bishnu","email":"","middleInitial":"Singh","affiliations":[{"id":36232,"text":"National Trust for Nature Conservation, Khumaltar, POB 3712, Lalitpur, Nepal","active":true,"usgs":false}],"preferred":false,"id":726796,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":726792,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70212316,"text":"70212316 - 2018 - Development of a species status assessment process for decisions under the U.S. Endangered Species Act","interactions":[],"lastModifiedDate":"2020-08-17T12:36:08.764155","indexId":"70212316","displayToPublicDate":"2018-02-02T10:04:43","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Development of a species status assessment process for decisions under the U.S. Endangered Species Act","docAbstract":"Decisions under the U.S. Endangered Species Act (ESA) require scientific input on the risk that the species will become extinct. A series of critiques on the role of science in ESA decisions have called for improved consistency and transparency in species risk assessments and clear distinctions between science input and policy application. To address the critiques and document the emerging practice of the U.S. Fish and Wildlife Service (USFWS), we outline an assessment process based on principles and practices of risk and decision analyses that results in a scientific report on species status. The species status assessment (SSA) process has three successive stages: 1) document the life history and ecological relationships of the species in question to provide the foundation for the assessment, 2) describe and hypothesize causes for the current condition of the species, and 3) forecast the species' future condition. The future condition refers to the ability of a species to sustain populations in the wild under plausible future scenarios. The scenarios help explore the species' response to future environmental stressors and to assess the potential for conservation to intervene to improve its status. The SSA process incorporates modeling and scenario planning for prediction of extinction risk and applies the conservation biology principles of representation, resiliency, and redundancy to evaluate the current and future condition. The SSA results in a scientific report distinct from policy application, which contributes to streamlined, transparent, and consistent decision-making and allows for greater technical participation by experts outside of the USFWS, for example, by state natural resource agencies. We present two case studies based on assessments of the eastern massasauga rattlesnake Sistrurus catenatus and the Sonoran Desert tortoise Gopherus morafkai to illustrate the process. The SSA builds upon the past threat-focused assessment by including systematic and explicit analyses of a species' future response to stressors and conservation, and as a result, we believe it provides an improved scientific analysis for ESA decisions.
","language":"English","publisher":"U.S. Fish & Wildlife Service","doi":"10.3996/052017-JFWM-041","usgsCitation":"Smith, D.R., Allan, N.L., McGowan, C.P., Szymankski, J.A., Oetker, S.R., and Bell, H.M., 2018, Development of a species status assessment process for decisions under the U.S. Endangered Species Act: Journal of Fish and Wildlife Management, v. 9, no. 1, p. 302-320, https://doi.org/10.3996/052017-JFWM-041.","productDescription":"19 p.","startPage":"302","endPage":"320","ipdsId":"IP-079068","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":469038,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/052017-jfwm-041","text":"Publisher Index Page"},{"id":377524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":796340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allan, Nathan L.","contributorId":193025,"corporation":false,"usgs":false,"family":"Allan","given":"Nathan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":796341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":167162,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor","email":"cmcgowan@usgs.gov","middleInitial":"P.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":796342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Szymankski, Jennifer A.","contributorId":238520,"corporation":false,"usgs":false,"family":"Szymankski","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796344,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oetker, Susan R.","contributorId":238519,"corporation":false,"usgs":false,"family":"Oetker","given":"Susan","email":"","middleInitial":"R.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bell, Heather M.","contributorId":238521,"corporation":false,"usgs":false,"family":"Bell","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796345,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70209266,"text":"70209266 - 2018 - Effects of feral horse herds on plant communities across a precipitation gradient","interactions":[],"lastModifiedDate":"2020-03-26T12:58:07","indexId":"70209266","displayToPublicDate":"2018-01-30T12:36:33","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":"Effects of feral horse herds on plant communities across a precipitation gradient","docAbstract":"Feral horses are widespread in the western United States, with the majority of feral horse herds found in the Great Basin. There is a federal mandate to manage these herds in order to maintain “ecological balance”; however, understanding of the specific effects of feral horse grazing on rangeland plant communities in this region is incomplete. To address this research gap, we utilized long-term grazing exclosures and fenceline contrasts to evaluate the impacts of feral horses on several plant community variables (diversity, richness, dominance, and biomass) and species composition. Because the effects of grazing can vary with site precipitation and productivity, we selected 5 sites from 4 different rangeland types (Great Basin Desert, Colorado Plateau, Rocky Mountain grassland, and mixed grass prairie) that spanned a mean annual precipitation gradient of 229 to 413 mm. Our results did not reveal a significant effect of feral horse grazing on plant community composition, species richness, diversity, evenness, or dominance. In contrast, total aboveground herbaceous biomass and grass biomass were significantly reduced with feral horse grazing, but these effects did not vary with mean annual precipitation. Our results suggest that, at least at the sites we studied, feral horses have affected the plant community by reducing herbaceous biomass but have not caused plant community shifts. Additional multisite studies, preferably with standardized exclosures and larger sample sizes, would increase our understanding of feral horse grazing effects and inform management of feral horse herds in the western United States.
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","language":"English","publisher":"Steelhead Committee Fly Fishers International","usgsCitation":"Williams, T.H., East, A.E., Smith, D.P., Boughton, D.A., Mantua, N., and Harrison, L.R., 2018, Removal of San Clemente Dam did more than restore fish passage: The Osprey, v. 89, p. 1, 4-9.","productDescription":"7 p.","startPage":"1, 4","endPage":"9","ipdsId":"IP-093722","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":352427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":352420,"type":{"id":15,"text":"Index Page"},"url":"https://www.ospreysteelhead.org/"}],"volume":"89","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee753e4b0da30c1bfc253","contributors":{"authors":[{"text":"Williams, Thomas H.","contributorId":203283,"corporation":false,"usgs":false,"family":"Williams","given":"Thomas","email":"","middleInitial":"H.","affiliations":[{"id":18933,"text":"NOAA Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":730841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":730840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Douglas P.","contributorId":201716,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas","email":"","middleInitial":"P.","affiliations":[{"id":35924,"text":"California State University, Monterey Bay","active":true,"usgs":false}],"preferred":false,"id":730842,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boughton, David A.","contributorId":172477,"corporation":false,"usgs":false,"family":"Boughton","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":730843,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mantua, Nate","contributorId":203284,"corporation":false,"usgs":false,"family":"Mantua","given":"Nate","affiliations":[{"id":18933,"text":"NOAA Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":730844,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harrison, Lee R.","contributorId":174322,"corporation":false,"usgs":false,"family":"Harrison","given":"Lee","email":"","middleInitial":"R.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":730845,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196522,"text":"70196522 - 2018 - Diel predator activity drives a dynamic landscape of fear","interactions":[],"lastModifiedDate":"2018-11-14T10:00:50","indexId":"70196522","displayToPublicDate":"2018-01-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"Diel predator activity drives a dynamic landscape of fear","docAbstract":"A “landscape of fear” (LOF) is a map that describes continuous spatial variation in an animal's perception of predation risk. The relief on this map reflects, for example, places that an animal avoids to minimize risk. Although the LOF concept is a potentially unifying theme in ecology that is often invoked to explain the ecological and conservation significance of fear, little is known about the daily dynamics of an LOF. Despite theory and data to the contrary, investigators often assume, implicitly or explicitly, that an LOF is a static consequence of a predator's mere presence within an ecosystem. We tested the prediction that an LOF in a large‐scale, free‐living system is a highly dynamic map with “peaks” and “valleys” that alternate across the diel (24‐h) cycle in response to daily lulls in predator activity. We did so with extensive data from the case study of Yellowstone elk (Cervus elaphus) and wolves (Canis lupus) that was the original basis for the LOF concept. We quantified the elk LOF, defined here as spatial allocation of time away from risky places and times, across nearly 1,000‐km2 of northern Yellowstone National Park and found that it fluctuated with the crepuscular activity pattern of wolves, enabling elk to use risky places during wolf downtimes. This may help explain evidence that wolf predation risk has no effect on elk stress levels, body condition, pregnancy, or herbivory. The ability of free‐living animals to adaptively allocate habitat use across periods of high and low predator activity within the diel cycle is an underappreciated aspect of animal behavior that helps explain why strong antipredator responses may trigger weak ecological effects, and why an LOF may have less conceptual and practical importance than direct killing.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecm.1313","usgsCitation":"Kohl, M.T., Stahler, D.R., Metz, M.C., Forester, J.D., Kauffman, M., Varley, N., White, P., Smith, D.W., and MacNulty, D.R., 2018, Diel predator activity drives a dynamic landscape of fear: Ecological Monographs, v. 88, no. 4, p. 638-652, https://doi.org/10.1002/ecm.1313.","productDescription":"15 p.","startPage":"638","endPage":"652","ipdsId":"IP-065975","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469124,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecm.1313","text":"Publisher Index Page"},{"id":353404,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Yellowstone National Park","volume":"88","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-22","publicationStatus":"PW","scienceBaseUri":"5afee788e4b0da30c1bfc2c0","contributors":{"authors":[{"text":"Kohl, Michel T.","contributorId":204214,"corporation":false,"usgs":false,"family":"Kohl","given":"Michel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":733394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stahler, Daniel R.","contributorId":179180,"corporation":false,"usgs":false,"family":"Stahler","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":733395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Metz, Matthew C.","contributorId":172854,"corporation":false,"usgs":false,"family":"Metz","given":"Matthew","email":"","middleInitial":"C.","affiliations":[{"id":27103,"text":"Yellowston Wolf Project","active":true,"usgs":false}],"preferred":false,"id":733396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forester, James D.","contributorId":194334,"corporation":false,"usgs":false,"family":"Forester","given":"James","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":733397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900 mkauffman@usgs.gov","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":189179,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew J.","email":"mkauffman@usgs.gov","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":733387,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Varley, Nathan","contributorId":204215,"corporation":false,"usgs":false,"family":"Varley","given":"Nathan","email":"","affiliations":[],"preferred":false,"id":733398,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"White, P.J.","contributorId":91436,"corporation":false,"usgs":true,"family":"White","given":"P.J.","affiliations":[],"preferred":false,"id":733399,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smith, Douglas W.","contributorId":95727,"corporation":false,"usgs":true,"family":"Smith","given":"Douglas","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":733400,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"MacNulty, Daniel R.","contributorId":64069,"corporation":false,"usgs":true,"family":"MacNulty","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":733401,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70191810,"text":"70191810 - 2018 - 2.3. Global-scale atmospheric dispersion of microorganisms","interactions":[],"lastModifiedDate":"2017-12-01T13:38:26","indexId":"70191810","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"2.3. Global-scale atmospheric dispersion of microorganisms","docAbstract":"This chapter addresses long-range dispersion and the survival of microorganisms across a wide range of altitudes in Earth's atmosphere. Topics include mechanisms of dispersion, survivability of microorganisms known to be associated with long-range transport, natural and artificial sources of bioaerosols, residence time estimation through the use of proxy aerosols, transport and emission models, and monitoring assays (both culture and molecular based). We conclude with a discussion of the known limits for Earth's biosphere boundary, relating aerobiology studies to planetary exploration given the large degree of overlapping requirements for in situ studies (including low biomass life detection and contamination control).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Microbiology of aerosols","language":"English","publisher":"Wiley","doi":"10.1002/9781119132318.ch2c","usgsCitation":"Griffin, D.W., Gonzalez-Martin, C., Hoose, C., and Smith, D., 2018, 2.3. Global-scale atmospheric dispersion of microorganisms, chap. of Microbiology of aerosols, https://doi.org/10.1002/9781119132318.ch2c.","ipdsId":"IP-074805","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":349637,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-22","publicationStatus":"PW","scienceBaseUri":"5a60fad8e4b06e28e9c227db","contributors":{"editors":[{"text":"Delort, Anne-Marie","contributorId":201091,"corporation":false,"usgs":false,"family":"Delort","given":"Anne-Marie","email":"","affiliations":[],"preferred":false,"id":724307,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Amato, Pierre","contributorId":201092,"corporation":false,"usgs":false,"family":"Amato","given":"Pierre","email":"","affiliations":[],"preferred":false,"id":724308,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Griffin, Dale W. 0000-0003-1719-5812 dgriffin@usgs.gov","orcid":"https://orcid.org/0000-0003-1719-5812","contributorId":2178,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale","email":"dgriffin@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gonzalez-Martin, Cristina","contributorId":30084,"corporation":false,"usgs":true,"family":"Gonzalez-Martin","given":"Cristina","email":"","affiliations":[],"preferred":false,"id":724304,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoose, C.","contributorId":201090,"corporation":false,"usgs":false,"family":"Hoose","given":"C.","email":"","affiliations":[],"preferred":false,"id":724305,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, D.J.","contributorId":48417,"corporation":false,"usgs":true,"family":"Smith","given":"D.J.","email":"","affiliations":[],"preferred":false,"id":724306,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194561,"text":"70194561 - 2017 - Chemical elements in the environment: multi-element geochemical datasets from continental to national scale surveys on four continents","interactions":[],"lastModifiedDate":"2025-05-14T19:00:58.320661","indexId":"70194561","displayToPublicDate":"2017-12-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Chemical elements in the environment: multi-element geochemical datasets from continental to national scale surveys on four continents","docAbstract":"During the last 10-20 years, Geological Surveys around the world have undertaken a major effort towards delivering fully harmonized and tightly quality-controlled low-density multi-element soil geochemical maps and datasets of vast regions including up to whole continents. Concentrations of between 45 and 60 elements commonly have been determined in a variety of different regolith types (e.g., sediment, soil). The multi-element datasets are published as complete geochemical atlases and made available to the general public. Several other geochemical datasets covering smaller areas but generally at a higher spatial density are also available. These datasets may, however, not be found by superficial internet-based searches because the elements are not mentioned individually either in the title or in the keyword lists of the original references. This publication attempts to increase the visibility and discoverability of these fundamental background datasets covering large areas up to whole continents.","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2017.11.010","usgsCitation":"Caritat, P.D., Reimann, C., Smith, D.B., and Wang, X., 2017, Chemical elements in the environment: multi-element geochemical datasets from continental to national scale surveys on four continents: Applied Geochemistry, v. 89, p. 150-159, https://doi.org/10.1016/j.apgeochem.2017.11.010.","productDescription":"10 p.","startPage":"150","endPage":"159","ipdsId":"IP-092659","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":349740,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":469243,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2017.11.010","text":"Publisher Index Page"}],"volume":"89","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faede4b06e28e9c229b3","contributors":{"authors":[{"text":"Caritat, Patrice de","contributorId":201164,"corporation":false,"usgs":false,"family":"Caritat","given":"Patrice","email":"","middleInitial":"de","affiliations":[],"preferred":false,"id":724483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reimann, Clemens","contributorId":201165,"corporation":false,"usgs":false,"family":"Reimann","given":"Clemens","email":"","affiliations":[],"preferred":false,"id":724484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, David B. 0000-0001-8396-9105 dsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-8396-9105","contributorId":138565,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"dsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Xueqiu","contributorId":201166,"corporation":false,"usgs":false,"family":"Wang","given":"Xueqiu","email":"","affiliations":[],"preferred":false,"id":724485,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195142,"text":"70195142 - 2017 - Earthquake Early Warning ShakeAlert System: Testing and certification platform","interactions":[],"lastModifiedDate":"2018-02-08T13:34:56","indexId":"70195142","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Earthquake Early Warning ShakeAlert System: Testing and certification platform","docAbstract":"Earthquake early warning systems provide warnings to end users of incoming moderate to strong ground shaking from earthquakes. An earthquake early warning system, ShakeAlert, is providing alerts to beta end users in the western United States, specifically California, Oregon, and Washington. An essential aspect of the earthquake early warning system is the development of a framework to test modifications to code to ensure functionality and assess performance. In 2016, a Testing and Certification Platform (TCP) was included in the development of the Production Prototype version of ShakeAlert. The purpose of the TCP is to evaluate the robustness of candidate code that is proposed for deployment on ShakeAlert Production Prototype servers. TCP consists of two main components: a real‐time in situ test that replicates the real‐time production system and an offline playback system to replay test suites. The real‐time tests of system performance assess code optimization and stability. The offline tests comprise a stress test of candidate code to assess if the code is production ready. The test suite includes over 120 events including local, regional, and teleseismic historic earthquakes, recentering and calibration events, and other anomalous and potentially problematic signals. Two assessments of alert performance are conducted. First, point‐source assessments are undertaken to compare magnitude, epicentral location, and origin time with the Advanced National Seismic System Comprehensive Catalog, as well as to evaluate alert latency. Second, we describe assessment of the quality of ground‐motion predictions at end‐user sites by comparing predicted shaking intensities to ShakeMaps for historic events and implement a threshold‐based approach that assesses how often end users initiate the appropriate action, based on their ground‐shaking threshold. TCP has been developed to be a convenient streamlined procedure for objectively testing algorithms, and it has been designed with flexibility to accommodate significant changes in development of new or modified system code. It is expected that the TCP will continue to evolve along with the ShakeAlert system, and the framework we describe here provides one example of how earthquake early warning systems can be evaluated.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220170138","usgsCitation":"Cochran, E.S., Kohler, M.D., Given, D.D., Guiwits, S., Andrews, J., Meier, M., Ahmad, M., Henson, I., Hartog, J.R., and Smith, D., 2017, Earthquake Early Warning ShakeAlert System: Testing and certification platform: Seismological Research Letters, v. 89, no. 1, p. 108-117, https://doi.org/10.1785/0220170138.","productDescription":"10 p.","startPage":"108","endPage":"117","ipdsId":"IP-087135","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469263,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://resolver.caltech.edu/CaltechAUTHORS:20171208-083947727","text":"External Repository"},{"id":351359,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, 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Renate","contributorId":171724,"corporation":false,"usgs":false,"family":"Hartog","given":"J.","email":"","middleInitial":"Renate","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":727144,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Deborah 0000-0002-8317-7762","orcid":"https://orcid.org/0000-0002-8317-7762","contributorId":201885,"corporation":false,"usgs":true,"family":"Smith","given":"Deborah","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":727146,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70263401,"text":"70263401 - 2017 - FinDer v.2: Improved real-time ground-motion predictions for M2-M9 with seismic finite-source characterization","interactions":[],"lastModifiedDate":"2025-02-10T15:32:10.488528","indexId":"70263401","displayToPublicDate":"2017-10-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"FinDer v.2: Improved real-time ground-motion predictions for M2-M9 with seismic finite-source characterization","docAbstract":"Recent studies suggest that small and large earthquakes nucleate similarly, and that they often have indistinguishable seismic waveform onsets. The characterization of earthquakes in real time, such as for earthquake early warning, therefore requires a flexible modeling approach that allows a small earthquake to become large as fault rupture evolves over time. Here, we present a modeling approach that generates a set of output parameters and uncertainty estimates that are consistent with both small/moderate (≤M6.5) and large earthquakes (>M6.5) as is required for a robust parameter interpretation and shaking forecast. Our approach treats earthquakes over the entire range of magnitudes (>M2) as finite line-source ruptures, with the dimensions of small earthquakes being very small (<100 m) and those of large earthquakes exceeding several tens to hundreds of kilometres in length. The extent of the assumed line source is estimated from the level and distribution of high-frequency peak acceleration amplitudes observed in a local seismic network. High-frequency motions are well suited for this approach, because they are mainly controlled by the distance to the rupturing fault. Observed ground-motion patterns are compared with theoretical templates modeled from empirical ground-motion prediction equations to determine the best line source and uncertainties. Our algorithm extends earlier work by Böse et al. for large finite-fault ruptures. This paper gives a detailed summary of the new algorithm and its offline performance for the 2016 M7.0 Kumamoto, Japan and 2014 M6.0 South Napa, California earthquakes, as well as its performance for about 100 real-time detected local earthquakes (2.2 ≤ M ≤ 5.1) in California. For most events, both the rupture length and the strike are well constrained within a few seconds (<10 s) of the event origin. In large earthquakes, this could allow for providing warnings of up to several tens of seconds. The algorithm could also be useful for resolving fault plane ambiguities of focal mechanisms and identification of rupturing faults for earthquakes as small as M2.5.
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Maren","contributorId":350745,"corporation":false,"usgs":false,"family":"Boese","given":"Maren","affiliations":[{"id":80868,"text":"ETH","active":true,"usgs":false}],"preferred":false,"id":926851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Deborah 0000-0002-8317-7762","orcid":"https://orcid.org/0000-0002-8317-7762","contributorId":201885,"corporation":false,"usgs":true,"family":"Smith","given":"Deborah","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Felizardo, Claude","contributorId":201876,"corporation":false,"usgs":false,"family":"Felizardo","given":"Claude","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":926853,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meier, Men-Andrin 0000-0002-2949-8602","orcid":"https://orcid.org/0000-0002-2949-8602","contributorId":293577,"corporation":false,"usgs":false,"family":"Meier","given":"Men-Andrin","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":926854,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heaton, Thomas H.","contributorId":187505,"corporation":false,"usgs":false,"family":"Heaton","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":926855,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clinton, J.F.","contributorId":350746,"corporation":false,"usgs":false,"family":"Clinton","given":"J.F.","affiliations":[{"id":80868,"text":"ETH","active":true,"usgs":false}],"preferred":false,"id":926856,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191488,"text":"70191488 - 2017 - Productivity and CO2 exchange of Great Plains ecoregions. I. Shortgrass steppe: Flux tower estimates","interactions":[],"lastModifiedDate":"2017-10-18T17:09:03","indexId":"70191488","displayToPublicDate":"2017-10-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Productivity and CO2 exchange of Great Plains ecoregions. I. Shortgrass steppe: Flux tower estimates","docAbstract":"The shortgrass steppe (SGS) occupies the southwestern part of the Great Plains. Half of the land is cultivated, but significant areas remain under natural vegetation. Despite previous studies of the SGS carbon cycle, not all aspects have been completely addressed, including gross productivity, ecosystem respiration, and ecophysiological parameters. Our analysis of 1998 − 2007 flux tower measurements at five Bowen ratio–energy balance (BREB) and three eddy covariance (EC) sites characterized seasonal and interannual variability of gross photosynthesis and ecosystem respiration. Identification of the nonrectangular hyperbolic equation for the diurnal CO2 exchange, with vapor pressure deficit (VPD) limitation and exponential temperature response, quantified quantum yield α, photosynthetic capacity Amax, and respiration rate rd with variation ranges (19 \\< α \\< 51 mmol mol− 1, 0.48 \\< Amax \\< 2.1 mg CO2 m− 2 s− 1, 0.15 \\< rd \\< 0.49 mg CO2 m− 2 s− 1). Gross photosynthesis varied from 1 100 to 2 700 g CO2 m− 2 yr− 1, respiration from 900 to 3,000 g CO2 m− 2 yr− 1, and net ecosystem production from − 900 to + 700 g CO2 m− 2 yr− 1, indicating that SGS may switch from a sink to a source depending on weather. Comparison of the 2004 − 2006 measurements at two BREB and two parallel EC flux towers located at comparable SGS sites showed moderately higher photosynthesis, lower respiration, and higher net production at the BREB than EC sites. However, the difference was not related only to methodologies, as the normalized difference vegetation index at the BREB sites was higher than at the EC sites. Overall magnitudes and seasonal patterns at the BREB and the EC sites during the 3-yr period were similar, with trajectories within the ± 1.5 standard deviation around the mean of the four sites and mostly reflecting the effects of meteorology.
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