Partitioning total variability into its component temporal and spatial sources is a powerful way to better understand time series and elucidate trends. The data available for such analyses of fish and other populations are usually nonnegative integer counts of the number of organisms, often dominated by many low values with few observations of relatively high abundance. These characteristics are not well approximated by the Gaussian distribution. We present a detailed description of a negative binomial mixed-model framework that can be used to model count data and quantify temporal and spatial variability. We applied these models to data from four fishery-independent surveys of Walleyes Sander vitreus across the Great Lakes basin. Specifically, we fitted models to gill-net catches from Wisconsin waters of Lake Superior; Oneida Lake, New York; Saginaw Bay in Lake Huron, Michigan; and Ohio waters of Lake Erie. These long-term monitoring surveys varied in overall sampling intensity, the total catch of Walleyes, and the proportion of zero catches. Parameter estimation included the negative binomial scaling parameter, and we quantified the random effects as the variations among gill-net sampling sites, the variations among sampled years, and site × year interactions. This framework (i.e., the application of a mixed model appropriate for count data in a variance-partitioning context) represents a flexible approach that has implications for monitoring programs (e.g., trend detection) and for examining the potential of individual variance components to serve as response metrics to large-scale anthropogenic perturbations or ecological changes.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2012.728163","usgsCitation":"Irwin, B.J., Wagner, T., Bence, J., Kepler, M.V., Liu, W., and Hayes, D.B., 2013, Estimating spatial and temporal components of variation in count data using negative binomial mixed models: Transactions of the American Fisheries Society, v. 142, no. 1, p. 171-183, https://doi.org/10.1080/00028487.2012.728163.","productDescription":"12 p.","startPage":"171","endPage":"183","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-031058","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Maine, Michigan, Ohio, 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\"}}]}","volume":"142","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2012-12-12","publicationStatus":"PW","scienceBaseUri":"57651f33e4b07657d19c7894","contributors":{"authors":[{"text":"Irwin, Brian J. 0000-0002-0666-2641 bjirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":4037,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian","email":"bjirwin@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":639609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":637162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bence, James R.","contributorId":95026,"corporation":false,"usgs":false,"family":"Bence","given":"James R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":639610,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kepler, Megan V.","contributorId":172106,"corporation":false,"usgs":false,"family":"Kepler","given":"Megan","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":639611,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liu, Weihai","contributorId":104786,"corporation":false,"usgs":true,"family":"Liu","given":"Weihai","email":"","affiliations":[],"preferred":false,"id":639612,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hayes, Daniel B.","contributorId":16799,"corporation":false,"usgs":true,"family":"Hayes","given":"Daniel","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":639613,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70004461,"text":"70004461 - 2013 - The issue of scale in wildlife management: The difficulty with extrapolation","interactions":[],"lastModifiedDate":"2022-12-12T17:51:12.048429","indexId":"70004461","displayToPublicDate":"2015-06-15T08:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"6","title":"The issue of scale in wildlife management: The difficulty with extrapolation","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Wildlife Management and Conservation","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Johns Hopkins University Press","usgsCitation":"Bissonette, J., 2013, The issue of scale in wildlife management: The difficulty with extrapolation, chap. 6 of Wildlife Management and Conservation, p. 73-83.","productDescription":"11 p.","startPage":"73","endPage":"83","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-030012","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":310937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5638976ee4b0d6133fe7300f","contributors":{"editors":[{"text":"Krausman, Paul R.","contributorId":31467,"corporation":false,"usgs":true,"family":"Krausman","given":"Paul","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":579053,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cain, James W. III","contributorId":113461,"corporation":false,"usgs":true,"family":"Cain","given":"James W. III","affiliations":[],"preferred":false,"id":579054,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Bissonette, John","contributorId":62914,"corporation":false,"usgs":true,"family":"Bissonette","given":"John","affiliations":[],"preferred":false,"id":579052,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70048359,"text":"70048359 - 2013 - National Park Service Vegetation Inventory Program, Cuyahoga Valley National Park, Ohio","interactions":[],"lastModifiedDate":"2017-04-25T13:35:53","indexId":"70048359","displayToPublicDate":"2015-05-29T13:51:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":54,"text":"Natural Resource Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/HTLN/NRTR—2013/792","title":"National Park Service Vegetation Inventory Program, Cuyahoga Valley National Park, Ohio","docAbstract":"The National Park Service (NPS) Vegetation Inventory Program (VIP) is an effort to classify, describe, and map existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VIP is managed by the NPS Biological Resources Management Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey (USGS) Vegetation Characterization Program lends a cooperative role in the NPS VIP. The USGS Upper Midwest Environmental Sciences Center, NatureServe, and NPS Cuyahoga Valley National Park (CUVA) have completed vegetation classification and mapping of CUVA.
Mappers, ecologists, and botanists collaborated to identify and describe vegetation types within the National Vegetation Classification Standard (NVCS) and to determine how best to map them by using aerial imagery. The team collected data from 221 vegetation plots within CUVA to develop detailed descriptions of vegetation types. Data from 50 verification sites were also collected to test both the key to vegetation types and the application of vegetation types to a sample set of map polygons. Furthermore, data from 647 accuracy assessment (AA) sites were collected (of which 643 were used to test accuracy of the vegetation map layer). These data sets led to the identification of 45 vegetation types at the association level in the NVCS at CUVA.
A total of 44 map classes were developed to map the vegetation and general land cover of CUVA, including the following: 29 map classes represent natural/semi-natural vegetation types in the NVCS, 12 map classes represent cultural vegetation (agricultural and developed) in the NVCS, and 3 map classes represent non-vegetation features (open-water bodies). Features were interpreted from viewing color-infrared digital aerial imagery dated October 2010 (during peak leaf-phenology change of trees) via digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). The interpreted data were digitally and spatially referenced, thus making the spatial database layers usable in GIS. Polygon units were mapped to either a 0.5 ha or 0.25 ha minimum mapping unit, depending on vegetation type.
A geodatabase containing various feature-class layers and tables shows the locations of vegetation types and general land cover (vegetation map), vegetation plot samples, verification sites, AA sites, project boundary extent, and aerial photographic centers. The feature-class layer and relate tables for the CUVA vegetation map provides 4,640 polygons of detailed attribute data covering 13,288.4 ha, with an average polygon size of 2.9 ha.
Summary reports generated from the vegetation map layer show map classes representing natural/semi-natural types in the NVCS apply to 4,151 polygons (89.4% of polygons) and cover 11,225.0 ha (84.5%) of the map extent. Of these polygons, the map layer shows CUVA to be 74.4% forest (9,888.8 ha), 2.5% shrubland (329.7 ha), and 7.6% herbaceous vegetation cover (1,006.5 ha). Map classes representing cultural types in the NVCS apply to 435 polygons (9.4% of polygons) and cover 1,825.7 ha (13.7%) of the map extent. Map classes representing non-NVCS units (open water) apply to 54 polygons (1.2% of polygons) and cover 237.7 ha (1.8%) of the map extent.
A thematic AA study was conducted of map classes representing natural/semi-natural types in the NVCS. Results present an overall accuracy of 80.7% (kappa index of 79.5%) based on data from 643 of the 647 AA sites. Most individual map-class themes exceed the NPS VIP standard of 80% with a 90% confidence interval.
The CUVA vegetation mapping project delivers many geospatial and vegetation data products in hardcopy and/or digital formats. These products consist of an in-depth project report discussing methods and results, which include descriptions and a dichotomous key to vegetation types, map classification and map-class descriptions, and a contingency table showing AA results. The suite of products also includes a database of vegetation plots, verification sites, and AA sites; digital pictures of field sites; field data sheets; aerial photographic imagery; hardcopy and digital maps; and a geodatabase of vegetation types and land cover (map layer), fieldwork locations (vegetation plots, verification sites, and AA sites), aerial photographic index, project boundary, and metadata. All geospatial products are projected in Universal Transverse Mercator, Zone 17, by using the North American Datum of 1983. Information on the NPS VIP and completed park mapping projects are located on the Internet at <http://science.nature.nps.gov/im/inventory/veg> and <http://www.usgs.gov/core_science_systems/csas/vip/index.html>.
","language":"English","publisher":"National Park Service","publisherLocation":"Fort Collins, CO","usgsCitation":"Hop, K.D., Drake, J., Strassman, A.C., Hoy, E.E., Menard, S., Jakusz, J., and Dieck, J., 2013, National Park Service Vegetation Inventory Program, Cuyahoga Valley National Park, Ohio: Natural Resource Technical Report NPS/HTLN/NRTR—2013/792, xv, 66 p.","productDescription":"xv, 66 p.","numberOfPages":"302","ipdsId":"IP-045709","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":340274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340273,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2198743"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59006066e4b0e85db3a5ddfb","contributors":{"authors":[{"text":"Hop, Kevin D. 0000-0002-9928-4773 khop@usgs.gov","orcid":"https://orcid.org/0000-0002-9928-4773","contributorId":1438,"corporation":false,"usgs":true,"family":"Hop","given":"Kevin","email":"khop@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":518202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drake, J.","contributorId":101003,"corporation":false,"usgs":true,"family":"Drake","given":"J.","email":"","affiliations":[],"preferred":false,"id":692860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Strassman, Andrew C. 0000-0002-9792-7181 astrassman@usgs.gov","orcid":"https://orcid.org/0000-0002-9792-7181","contributorId":4575,"corporation":false,"usgs":true,"family":"Strassman","given":"Andrew","email":"astrassman@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":518205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoy, Erin E. 0000-0002-2853-3242 ehoy@usgs.gov","orcid":"https://orcid.org/0000-0002-2853-3242","contributorId":4523,"corporation":false,"usgs":true,"family":"Hoy","given":"Erin","email":"ehoy@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":518204,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Menard, Shannon","contributorId":167864,"corporation":false,"usgs":false,"family":"Menard","given":"Shannon","email":"","affiliations":[{"id":17658,"text":"NatureServe","active":true,"usgs":false}],"preferred":false,"id":692861,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dieck, J.J. jdieck@usgs.gov","contributorId":1699,"corporation":false,"usgs":true,"family":"Dieck","given":"J.J.","email":"jdieck@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":518203,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jakusz, J.W. jjakusz@usgs.gov","contributorId":4835,"corporation":false,"usgs":true,"family":"Jakusz","given":"J.W.","email":"jjakusz@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":518206,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70047996,"text":"70047996 - 2013 - Evaluation of National Atmospheric Deposition Program measurements for co-located Sites CO89 and CO98 at Rocky Mountain National Park, 2012","interactions":[],"lastModifiedDate":"2016-07-12T14:11:22","indexId":"70047996","displayToPublicDate":"2015-05-28T10:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Evaluation of National Atmospheric Deposition Program measurements for co-located Sites CO89 and CO98 at Rocky Mountain National Park, 2012","docAbstract":"Atmospheric wet-deposition monitoring in Rocky Mountain National Park included precipitation depth and aqueous chemical measurements at co-located National Atmospheric Deposition Program (NADP) sites CO89 and CO98 (Loch Vale) during 2012. The co-located sites are separated by approximately 6.5 meters horizontally and 0.5 meters in altitude, which meets NADP siting criteria.
\nMedian weekly absolute percent differences for selected parameters including: sample volume, 8.0 percent; ammonium concentration, 9.1 percent; nitrate concentration, 8.5 percent; sulfate concentration, 10.2 percent. Annual precipitation-weighted mean concentrations were higher for CO98 compared to CO89 for all analytes. The chemical concentration record for CO98 contains more valid samples than the CO89 record. Therefore, the CO98 record is more representative of 2012 total annual deposition at Loch Vale. Daily precipitation-depth records for the co-located precipitation gages were 100 percent complete, and the total annual precipitation depths between the sites differed by 0.1 percent for the year (91.5 and 91.4 cm).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","usgsCitation":"USGS Branch of Quality Systems, 2013, Evaluation of National Atmospheric Deposition Program measurements for co-located Sites CO89 and CO98 at Rocky Mountain National Park, 2012, 25 p.","productDescription":"25 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050225","costCenters":[{"id":143,"text":"Branch of Quality Systems","active":true,"usgs":true}],"links":[{"id":325110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":325109,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://nature.nps.gov/air/pubs/pdf/USGS_2013Co-located_sites-at-RMNP.pdf"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountain National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.83953857421874,\n 40.20614809577503\n ],\n [\n -105.83953857421874,\n 40.490826256468054\n ],\n [\n -105.54290771484374,\n 40.490826256468054\n ],\n [\n -105.54290771484374,\n 40.20614809577503\n ],\n [\n -105.83953857421874,\n 40.20614809577503\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"579dcfdfe4b0589fa1cbd822","contributors":{"authors":[{"text":"USGS Branch of Quality Systems","contributorId":172840,"corporation":true,"usgs":false,"organization":"USGS Branch of Quality Systems","id":642243,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70101130,"text":"70101130 - 2013 - A survey of methods for implementing and documenting water conservation in New York","interactions":[],"lastModifiedDate":"2015-05-06T08:49:41","indexId":"70101130","displayToPublicDate":"2015-05-01T11:40:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"title":"A survey of methods for implementing and documenting water conservation in New York","docAbstract":"Water conservation methods and best management practices (BMPs) for water conservation are described for major categories of non-drinking-water users, including—but not limited to—industrial, commercial, power-generation, agricultural, and institutional categories. The BMPs were drawn from a literature search of reports published by state agencies, Federal agencies, the U.S. military, colleges and universities, and water-related organizations that have studied and evaluated various water conservation methods in the municipal supply, industrial, commercial, institutional, and agricultural water-use sectors. An annotated bibliography of references pertinent to water conservation and (or) best management practices in water conservation is included.
","language":"English","publisher":"New York State Department of Environmental Conservation","usgsCitation":"Linsey, K.S., and Reynolds, R.J., 2013, A survey of methods for implementing and documenting water conservation in New York, ii, 48 p.","productDescription":"ii, 48 p.","numberOfPages":"51","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040710","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":289343,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":300123,"type":{"id":11,"text":"Document"},"url":"https://www.dec.ny.gov/docs/water_pdf/waterconnon.pdf","size":"2.92 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":300124,"type":{"id":15,"text":"Index Page"},"url":"https://www.dec.ny.gov/lands/86945.html"}],"country":"United States","state":"New York","city":"New York","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.259088,40.495996 ], [ -74.259088,40.915256 ], [ -73.700272,40.915256 ], [ -73.700272,40.495996 ], [ -74.259088,40.495996 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"554495a8e4b0a658d7947883","contributors":{"authors":[{"text":"Linsey, Kristin S. 0000-0001-6492-7639 kslinsey@usgs.gov","orcid":"https://orcid.org/0000-0001-6492-7639","contributorId":3678,"corporation":false,"usgs":true,"family":"Linsey","given":"Kristin","email":"kslinsey@usgs.gov","middleInitial":"S.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":523184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reynolds, Richard J. 0000-0001-5032-6613 rjreynol@usgs.gov","orcid":"https://orcid.org/0000-0001-5032-6613","contributorId":1082,"corporation":false,"usgs":true,"family":"Reynolds","given":"Richard","email":"rjreynol@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":523185,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156156,"text":"70156156 - 2013 - New distribution record for the rare limpet Acroloxus coloradensis (Henderson, 1930) (Gastropoda: Acroloxidae) from Montana","interactions":[],"lastModifiedDate":"2022-11-10T17:41:08.323149","indexId":"70156156","displayToPublicDate":"2015-04-30T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2849,"text":"Nautilus","active":true,"publicationSubtype":{"id":10}},"displayTitle":"New distribution record for the rare limpet Acroloxus coloradensis (Henderson, 1930) (Gastropoda: Acroloxidae) from Montana","title":"New distribution record for the rare limpet Acroloxus coloradensis (Henderson, 1930) (Gastropoda: Acroloxidae) from Montana","docAbstract":"The Rocky Mountain Capshell, Acroloxus coloradensis (Henderson, 1930), the only North American member of the basommatophoran family Acroloxidae, is broadly distributed across southern Canada and south into the Rocky Mountains in the USA (Turgeon et al., 1998; Lee and Ackerman, 2000). Despite its wide geographic range, A. coloradensis has been documented from < 30 locations, mostly in British Columbia, Alberta, Ontario, and Quebec (Lee and Ackerman, 2000; Anderson, 2005). Relict populations of A. coloradensis in the USA have been documented from only 6 sites in Colorado and 2 sites in Glacier National Park (Glacier NP), Montana (Anderson, 2005; Ellis et al., 2004). In Glacier NP, A. coloradensis was first reported from Lost Lake (Figure 1; Russell and Brunson, 1967). A second population in the park was discovered in Trout Lake in 2001 (Ellis et al., 2004). In both lakes, A. coloradensis was found primarily under rocks and other cover objects.
","language":"English","publisher":"The Nautilus","usgsCitation":"Hossack, B.R., and Newell, R., 2013, New distribution record for the rare limpet Acroloxus coloradensis (Henderson, 1930) (Gastropoda: Acroloxidae) from Montana: Nautilus, v. 127, no. 1, p. 40-41.","productDescription":"2 p.","startPage":"40","endPage":"41","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041053","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":306836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":306833,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.biodiversitylibrary.org/itemdetails/203167"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.23354557411693,\n 48.40400757076276\n ],\n [\n -113.39720778937023,\n 48.689405550968985\n ],\n [\n -113.42914188977605,\n 48.765766178519925\n ],\n [\n -113.50498537824026,\n 48.83412886531235\n ],\n [\n -113.59401775628623,\n 48.92401108435317\n ],\n [\n -113.59678608575092,\n 49.0061706189355\n ],\n [\n -113.98399688432988,\n 49.00277590262988\n ],\n [\n -114.0990659159349,\n 49.0026611105327\n ],\n [\n -114.48072044259979,\n 49.001695525846856\n ],\n [\n -114.38169636923216,\n 48.87763573956872\n ],\n [\n -114.63864599198041,\n 48.83938370388864\n ],\n [\n -114.69453066769094,\n 48.778920114797415\n ],\n [\n -114.64263775453097,\n 48.72101714499948\n ],\n [\n -114.59872836647303,\n 48.69731033311706\n ],\n [\n -114.51490135290722,\n 48.60501098543017\n ],\n [\n -114.39115671383402,\n 48.47286160903545\n ],\n [\n -114.20753563649974,\n 48.38015173571776\n ],\n [\n -114.12770038548499,\n 48.38015173571776\n ],\n [\n -114.04387337191919,\n 48.374848920144416\n ],\n [\n -114.03988160936768,\n 48.441094418419\n ],\n [\n -113.99198045875873,\n 48.472861609034766\n ],\n [\n -113.98000517110661,\n 48.50460892313461\n ],\n [\n -113.86025229458444,\n 48.475507977678745\n ],\n [\n -113.8123511439755,\n 48.41990524751307\n ],\n [\n -113.72852413040968,\n 48.40135747473059\n ],\n [\n -113.66465592959759,\n 48.345673560866345\n ],\n [\n -113.56885362837967,\n 48.231464071208535\n ],\n [\n -113.50897719011857,\n 48.223486435023545\n ],\n [\n -113.28943024982748,\n 48.345673560866345\n ],\n [\n -113.23354557411693,\n 48.40400757076276\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"127","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d45732e4b0518e354694d6","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":567931,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newell, Robert L.","contributorId":58109,"corporation":false,"usgs":true,"family":"Newell","given":"Robert L.","affiliations":[],"preferred":false,"id":567932,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70146869,"text":"70146869 - 2013 - Post-fire wood management alters water stress, growth, and performance of pine regeneration in a Mediterranean ecosystem","interactions":[],"lastModifiedDate":"2015-04-23T11:09:24","indexId":"70146869","displayToPublicDate":"2015-04-23T12:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Post-fire wood management alters water stress, growth, and performance of pine regeneration in a Mediterranean ecosystem","docAbstract":"Extensive research has focused on comparing the impacts of post-fire salvage logging versus those of less aggressive management practices on forest regeneration. However, few studies have addressed the effects of different burnt-wood management options on seedling/sapling performance, or the ecophysiological mechanisms underlying differences among treatments. In this study, we experimentally assess the effects of post-fire management of the burnt wood on the growth and performance of naturally regenerating pine seedlings (Pinus pinaster). Three post-fire management treatments varying in degree of intervention were implemented seven months after a high-severity wildfire burned Mediterranean pine forests in the Sierra Nevada, southeast Spain: (a) “No Intervention” (NI, all burnt trees left standing); (b) “Partial Cut plus Lopping” (PCL, felling most of the burnt trees, cutting off branches, and leaving all the biomass on site without mastication); and (c) “Salvage Logging” (SL, felling the burnt trees, piling up the logs and masticating the fine woody debris). Three years after the fire, the growth, foliar nutrient concentrations, and leaf carbon, nitrogen and oxygen isotopic composition (δ13C, δ18O and δ15N) of naturally regenerating seedlings were measured in all the treatments. Pine seedlings showed greatest vigor and size in the PCL treatment, whereas growth was poorest in SL. The nutrient concentrations were similar among treatments, although greater growth in the two treatments with residual wood present indicated higher plant uptake. Seedlings in the SL treatment showed high leaf δ13C and δ18O values indicating severe water stress, in contrast to significantly alleviated water stress indications in the PCL treatment. Seedling growth and physiological performance in NI was intermediate between that of PCL and SL. After six growing seasons, P. pinaster saplings in PCL showed greater growth and cone production than SL saplings. In summary, salvage logging has a detrimental effect on the ecophysiological performance and growth of naturally regenerating pine seedlings, compared to alternative post-fire management practices in which burnt logs and branches are left in situ. Improved seedling growth and performance is associated with the amelioration of microsite/microclimate conditions by the presence of residual burnt wood, which alleviates seedling drought stress and improves nutrient availability through the decomposition of woody debris.
\nHydrogeomorphic, vegetative, and biogeochemical processes interact in floodplains resulting in great complexity that provides opportunities to better understand linkages among physical and biological processes in ecosystems. Floodplains and their associated river systems are structured by four dimensional gradients of hydrogeomorphology: longitudinal, lateral, vertical, and temporal components. These four dimensions create dynamic hydrologic and geomorphologic mosaics that have a large imprint on the vegetation and nutrient biogeochemistry of floodplains. Plant physiology, population dynamics, community structure, and productivity are all very responsive to floodplain hydrogeomorphology. The strength of this relationship between vegetation and hydrogeomorphology is evident in the use of vegetation as an indicator of hydrogeomorphic processes. However, vegetation also influences hydrogeomorphology by modifying hydraulics and sediment entrainment and deposition that typically stabilize geomorphic patterns. Nitrogen and phosphorus biogeochemistry commonly influence plant productivity and community composition, although productivity is not limited by nutrient availability in all floodplains. Conversely, vegetation influences nutrient biogeochemistry through direct uptake and storage as well as production of organic matter that regulates microbial biogeochemical processes. The biogeochemistries of nitrogen and phosphorus cycling are very sensitive to spatial and temporal variation in hydrogeomorphology, in particular floodplain wetness and sedimentation. The least studied interaction is the direct effect of biogeochemistry on hydrogeomorphology, but the control of nutrient availability over organic matter decomposition and thus soil permeability and elevation is likely important. Biogeochemistry also has the more documented but indirect control of hydrogeomorphology through regulation of plant biomass. In summary, the defining characteristics of floodplain ecosystems are determined by the many interactions among physical and biological processes. Conservation and restoration of the valuable ecosystem services that floodplains provide depends on improved understanding and predictive models of interactive system controls and behavior.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecogeomorphology","language":"English","publisher":"Elsevier","publisherLocation":"Reston, VA","doi":"10.1016/B978-0-12-374739-6.00338-9","usgsCitation":"Noe, G.B., 2013, Interactions among hydrogeomorphology, vegetation, and nutrient biogeochemistry in floodplain ecosystems, chap. of Ecogeomorphology, v. 12, p. 307-321, https://doi.org/10.1016/B978-0-12-374739-6.00338-9.","productDescription":"15 p.","startPage":"307","endPage":"321","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026520","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":324307,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"UNITED STATES","volume":"12","edition":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576d0832e4b07657d1a3756d","contributors":{"authors":[{"text":"Noe, G. B.","contributorId":146903,"corporation":false,"usgs":true,"family":"Noe","given":"G.","email":"","middleInitial":"B.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":640576,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70150445,"text":"70150445 - 2013 - Effects of dietary exposure to brominated flame retardant BDE-47 on thyroid condition, gonadal development and growth of zebrafish","interactions":[],"lastModifiedDate":"2015-07-15T11:28:34","indexId":"70150445","displayToPublicDate":"2015-01-01T12:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1651,"text":"Fish Physiology and Biochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Effects of dietary exposure to brominated flame retardant BDE-47 on thyroid condition, gonadal development and growth of zebrafish","docAbstract":"Little is known about the effects of brominated flame retardants in teleosts and some of the information currently available is inconsistent. This study examined effects of dietary exposure to 2,2′,4,4′-tetrabromodiphenyl ether (BDE-47) on thyroid condition, body mass and size, and gonadal development of zebrafish. Pubertal, 49-day-old (posthatch) fish were fed diets without BDE-47 (control) or with 1, 5 or 25 μg/g BDE-47/diet. Treatments were conducted in triplicate 30-L tanks each containing 50 zebrafish, and 15 fish per treatment (5 per tank) were sampled at days 40, 80 and 120 of exposure. Measurements were taken of body mass, standard length, head depth and head length. Sex (at 40–120 days of exposure), germ cell stage (at 40 days) and thyroid condition (at 120 days; follicular cell height, colloid depletion, angiogenesis) were histologically determined. Whole-body BDE-47 levels at study completion were within the high end of levels reported in environmentally exposed (wild) fishes. Analysis of variance was used to determine differences among treatments at each sampling time. No effects were observed on thyroid condition or germ cell stage in either sex. Reduced head length was observed in females exposed to BDE-47 at 80 days but not at 40 or 120 days. In males, no apparent effects of BDE-47 were observed at 40 and 80 days, but fish exposed to 25 μg/g had lower body mass at 120 days compared to control fish. These observations suggest that BDE-47 at environmentally relevant whole-body concentrations does not affect thyroid condition or pubertal development of zebrafish but does affect growth during the juvenile-to-adult transition, especially in males.
","language":"English","publisher":"Springer Netherlands","doi":"10.1007/s10695-012-9768-0","usgsCitation":"Torres, L., Orazio, C.E., Peterman, P.H., and Patino, R., 2013, Effects of dietary exposure to brominated flame retardant BDE-47 on thyroid condition, gonadal development and growth of zebrafish: Fish Physiology and Biochemistry, v. 39, no. 5, p. 1115-1128, https://doi.org/10.1007/s10695-012-9768-0.","productDescription":"14 p.","startPage":"1115","endPage":"1128","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040931","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"5","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2013-01-19","publicationStatus":"PW","scienceBaseUri":"55a78436e4b0183d66e45e86","contributors":{"authors":[{"text":"Torres, Leticia","contributorId":143738,"corporation":false,"usgs":false,"family":"Torres","given":"Leticia","email":"","affiliations":[],"preferred":false,"id":564850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orazio, Carl E. 0000-0002-2532-9668 corazio@usgs.gov","orcid":"https://orcid.org/0000-0002-2532-9668","contributorId":1366,"corporation":false,"usgs":true,"family":"Orazio","given":"Carl","email":"corazio@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":564851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterman, Paul H. ppeterman@usgs.gov","contributorId":2872,"corporation":false,"usgs":true,"family":"Peterman","given":"Paul","email":"ppeterman@usgs.gov","middleInitial":"H.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":564852,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patino, Reynaldo 0000-0002-4831-8400 r.patino@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-8400","contributorId":2311,"corporation":false,"usgs":true,"family":"Patino","given":"Reynaldo","email":"r.patino@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":556892,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159836,"text":"70159836 - 2013 - Mapping monkeypox transmission risk through time and space in the Congo Basin","interactions":[],"lastModifiedDate":"2015-12-01T11:49:37","indexId":"70159836","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Mapping monkeypox transmission risk through time and space in the Congo Basin","docAbstract":"Monkeypox is a major public health concern in the Congo Basin area, with changing patterns of human case occurrences reported in recent years. Whether this trend results from better surveillance and detection methods, reduced proportions of vaccinated vs. non-vaccinated human populations, or changing environmental conditions remains unclear. Our objective is to examine potential correlations between environment and transmission of monkeypox events in the Congo Basin. We created ecological niche models based on human cases reported in the Congo Basin by the World Health Organization at the end of the smallpox eradication campaign, in relation to remotely-sensed Normalized Difference Vegetation Index datasets from the same time period. These models predicted independent spatial subsets of monkeypox occurrences with high confidence; models were then projected onto parallel environmental datasets for the 2000s to create present-day monkeypox suitability maps. Recent trends in human monkeypox infection are associated with broad environmental changes across the Congo Basin. Our results demonstrate that ecological niche models provide useful tools for identification of areas suitable for transmission, even for poorly-known diseases like monkeypox.
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","language":"English","publisher":"Environmental Law Institute","usgsCitation":"Middleton, B., 2013, Conservation in an age of climate change: National Wetlands Newsletter, v. 35, no. 3, p. 25-26.","productDescription":"2 p.","startPage":"25","endPage":"26","ipdsId":"IP-043227","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":365246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"UNITED STATES","volume":"35","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":206609,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":765298,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70101982,"text":"70101982 - 2013 - Weakening of ice by magnesium perchlorate hydrate","interactions":[],"lastModifiedDate":"2014-04-16T10:08:35","indexId":"70101982","displayToPublicDate":"2014-11-05T10:00:06","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Weakening of ice by magnesium perchlorate hydrate","docAbstract":"We show that perchlorate hydrates, which have been detected at high circumpolar martian latitudes, have a dramatic effect upon the rheological behavior of polycrystalline water ice under conditions applicable to the North Polar Layered Deposits (NPLD). 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To explore the role of hydrogeologic heterogeneity and poorly constrained mountain hydrologic conditions on regional groundwater flow in contracted intermountain basins, a series of 3-D numerical groundwater flow models were developed using the South Park basin, Colorado, USA as a proxy. The models were used to identify the relative importance of different recharge processes to major aquifers, to estimate typical groundwater circulation depths, and to explore hydrogeologic communication between mountain and valley hydrogeologic landscapes. Modeling results show that mountain landscapes develop topographically controlled and predominantly local-scale to intermediate-scale flow systems. Permeability heterogeneity of the fold and fault belt and decreased topographic roughness led to permeability controlled flow systems in the valley. The structural position of major aquifers in the valley fold and fault belt was found to control the relative importance of different recharge mechanisms. Alternative mountain recharge model scenarios showed that higher mountain recharge rates led to higher mountain water table elevations and increasingly prominent local flow systems, primarily resulting in increased seepage within the mountain landscape and nonlinear increases in mountain block recharge to the valley. Valley aquifers were found to be relatively insensitive to changing mountain water tables, particularly in structurally isolated aquifers inside the fold and fault belt.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Resources Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/2013WR014451","usgsCitation":"Ball, L.B., Caine, J.S., and Ge, S., 2013, Control on groundwater flow in a semiarid folded and faulted intermountain basin: Water Resources Research, v. 50, no. 8, p. 6788-6809, https://doi.org/10.1002/2013WR014451.","productDescription":"22 p.","startPage":"6788","endPage":"6809","ipdsId":"IP-049504","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":473350,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013wr014451","text":"Publisher Index Page"},{"id":293573,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1002/2013WR014451/pdf"},{"id":293583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293572,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2013WR014451"}],"country":"United States","state":"Colorado","otherGeospatial":"South Park Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.0108,38.7556 ], [ -106.0108,39.3886 ], [ -105.4682,39.3886 ], [ -105.4682,38.7556 ], [ -106.0108,38.7556 ] ] ] } } ] }","volume":"50","issue":"8","noUsgsAuthors":false,"publicationDate":"2014-08-22","publicationStatus":"PW","scienceBaseUri":"541157b2e4b0fe7e184a5535","contributors":{"authors":[{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":500468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caine, Jonathan S. 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":1272,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan","email":"jscaine@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":500470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ge, Shemin","contributorId":37366,"corporation":false,"usgs":true,"family":"Ge","given":"Shemin","affiliations":[],"preferred":false,"id":500469,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70125303,"text":"70125303 - 2013 - Notable decomposition products of senescing Lake Michigan Cladophora glomerata","interactions":[],"lastModifiedDate":"2014-09-16T10:44:05","indexId":"70125303","displayToPublicDate":"2014-09-01T10:42:04","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Notable decomposition products of senescing Lake Michigan Cladophora glomerata","docAbstract":"Massive accumulations of Cladophora, a ubiquitous, filamentous green alga, have been increasingly reported along Great Lakes shorelines, negatively affecting beach aesthetics, recreational activities, public health and beachfront property values. Previously, the decomposition byproducts of decaying algae have not been thoroughly examined. To better understand the negative consequences and potential merit of the stranded Cladophora, a three month mesocosm study of the dynamic chemical environment of the alga was conducted using fresh samples collected from southern Lake Michigan beaches. Typical fermentation products, such as organic acids, sulfide compounds, and alcohols were detected in the oxygen–deprived algae. Short chain carboxylic acids peaked on day seven, in correspondence with the lowest pH value. Most low molecular mass carbon compounds were eventually consumed, but 4-methylphenol, indole, and 3-methylindole were detected throughout the incubation period. Natural oils were detected in fresh and decomposing algae, indicating the stable nature of these compounds. The mesocosm experiment was validated by directly sampling the fluid within decomposing Cladophora mats in the field; many of the same compounds were found. This study suggests that the problematic Cladophora accumulations may be harvested for useful byproducts, thereby reducing the odiferous and potentially harmful mats stranded along the shorelines.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"International Association for Great Lakes Research","publisherLocation":"Toronto","doi":"10.1016/j.jglr.2014.04.012","usgsCitation":"Peller, J.R., Byappanahalli, M., Shively, D.A., Sadowsky, M.J., Chun, C.L., and Whitman, R.L., 2013, Notable decomposition products of senescing Lake Michigan Cladophora glomerata: Journal of Great Lakes Research, v. 40, no. 3, p. 800-806, https://doi.org/10.1016/j.jglr.2014.04.012.","productDescription":"7 p.","startPage":"800","endPage":"806","numberOfPages":"7","ipdsId":"IP-049153","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":293917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293877,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2014.04.012"},{"id":293878,"type":{"id":15,"text":"Index Page"},"url":"https://www.iaglr.org/journal/"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.0434,41.6089 ], [ -88.0434,46.1024 ], [ -84.7385,46.1024 ], [ -84.7385,41.6089 ], [ -88.0434,41.6089 ] ] ] } } ] }","volume":"40","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54195149e4b091c7ffc8e79e","contributors":{"authors":[{"text":"Peller, Julie R.","contributorId":48889,"corporation":false,"usgs":false,"family":"Peller","given":"Julie","email":"","middleInitial":"R.","affiliations":[{"id":12645,"text":"Indiana University - Northwest","active":true,"usgs":false}],"preferred":false,"id":501197,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byappanahalli, Muruleedhara N.","contributorId":47335,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara N.","affiliations":[],"preferred":false,"id":501196,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shively, Dawn A. dshively@usgs.gov","contributorId":2051,"corporation":false,"usgs":true,"family":"Shively","given":"Dawn","email":"dshively@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":501193,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sadowsky, Michael J.","contributorId":34003,"corporation":false,"usgs":false,"family":"Sadowsky","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":12644,"text":"University of Minnesota, St. Paul","active":true,"usgs":false}],"preferred":false,"id":501194,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chun, Chan Lan","contributorId":43251,"corporation":false,"usgs":false,"family":"Chun","given":"Chan","email":"","middleInitial":"Lan","affiliations":[{"id":12644,"text":"University of Minnesota, St. Paul","active":true,"usgs":false}],"preferred":false,"id":501195,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitman, Richard L. rwhitman@usgs.gov","contributorId":542,"corporation":false,"usgs":true,"family":"Whitman","given":"Richard","email":"rwhitman@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":501192,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70116460,"text":"70116460 - 2013 - Geomorphic characterization of four shelf-sourced submarine canyons along the U.S. Mid-Atlantic continental margin","interactions":[],"lastModifiedDate":"2017-11-18T10:19:35","indexId":"70116460","displayToPublicDate":"2014-06-01T16:03:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1371,"text":"Deep-Sea Research Part II: Topical Studies in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphic characterization of four shelf-sourced submarine canyons along the U.S. Mid-Atlantic continental margin","docAbstract":"Shelf-sourced submarine canyons are common features of continental margins and are fundamental to deep-sea sedimentary systems. Despite their geomorphic and geologic significance, relatively few passive margin shelf-breaching canyons worldwide have been mapped using modern geophysical methods. Between 2007 and 2012 a series of geophysical surveys was conducted across four major canyons of the US Mid-Atlantic margin: Wilmington, Baltimore, Washington, and Norfolk canyons. More than 5700 km2 of high-resolution multibeam bathymetry and 890 line-km of sub-bottom CHIRP profiles were collected along the outer shelf and uppermost slope (depths of 80-1200 m). The data allowed us to compare and contrast the fine-scale morphology of each canyon system. The canyons have marked differences in the morphology and orientation of canyon heads, steepness and density of sidewall gullies, and the character of the continental shelf surrounding canyon rims. Down-canyon axial profiles for Washington, Baltimore and Wilmington canyons have linear shapes, and each canyon thalweg exhibits morphological evidence for recent, relatively small-scale sediment transport. For example, Washington Canyon displays extremely steep wall gradients and contains ~100 m wide, 5–10 m deep, v-shaped incisions down the canyon axis, suggesting modern or recent sediment transport. In contrast, the convex axial thalweg profile, the absence of thalweg incision, and evidence for sediment infilling at the canyon head, suggest that depositional processes strongly influence Norfolk Canyon during the current sea-level high-stand. The north walls of Wilmington, Washington and Norfolk canyons are steeper than the south walls due to differential erosion, though the underlying cause for this asymmetry is not clear. Furthermore, we speculate that most of the geomorphic features observed within the canyons (e.g., terraces, tributary canyons, gullies, and hanging valleys) were formed during the Pleistocene, and show only subtle modification by Holocene processes active during the present sea-level high-stand.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Deep-Sea Research Part II: Topical Studies in Oceanography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2013.09.013","usgsCitation":"Obelcz, J., Brothers, D., Chaytor, J., ten Brink, U., Ross, S., and Brooke, S., 2013, Geomorphic characterization of four shelf-sourced submarine canyons along the U.S. Mid-Atlantic continental margin: Deep-Sea Research Part II: Topical Studies in Oceanography, v. 104, p. 106-119, https://doi.org/10.1016/j.dsr2.2013.09.013.","productDescription":"14 p.","startPage":"106","endPage":"119","numberOfPages":"14","ipdsId":"IP-051303","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":289824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":289822,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.dsr2.2013.09.013"}],"country":"United States","otherGeospatial":"Cape Hatteras;Georges Bank;Hudson Canyon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -75.0,37.0 ], [ -75.0,38.0 ], [ -72.0,38.0 ], [ -72.0,37.0 ], [ -75.0,37.0 ] ] ] } } ] }","volume":"104","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53c0ebe7e4b065ccca5fe38f","contributors":{"authors":[{"text":"Obelcz, Jeffrey jobelcz@usgs.gov","contributorId":5430,"corporation":false,"usgs":true,"family":"Obelcz","given":"Jeffrey","email":"jobelcz@usgs.gov","affiliations":[],"preferred":true,"id":495806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Daniel S. dbrothers@usgs.gov","contributorId":3782,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","email":"dbrothers@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":495804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chaytor, Jason D. jchaytor@usgs.gov","contributorId":4961,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason D.","email":"jchaytor@usgs.gov","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":495805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"ten Brink, Uri S. 0000-0001-6858-3001 utenbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":127560,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri S.","email":"utenbrink@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":495808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ross, Steve W.","contributorId":41134,"corporation":false,"usgs":false,"family":"Ross","given":"Steve W.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":495807,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brooke, Sandra","contributorId":101570,"corporation":false,"usgs":true,"family":"Brooke","given":"Sandra","affiliations":[],"preferred":false,"id":495809,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70048851,"text":"70048851 - 2013 - Dust and human health","interactions":[],"lastModifiedDate":"2022-12-12T17:53:35.631062","indexId":"70048851","displayToPublicDate":"2014-06-01T14:40:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"15","title":"Dust and human health","docAbstract":"It is generally accepted that exposure to fine particulate matter may increase risk for human morbidity and mortality. Until recently, population health related studies examining the effects of particulate matter on human health generally examined anthropogenic (industry and combustion by-products) sources with few studies considering contributions from natural sources. This chapter provides an overview of naturally occurring inorganic mineral dust research and associated human health ailments and some of the challenges in elucidating the etiological mechanisms responsible.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Mineral dust: A key player in the Earth system","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-94-017-8978-3_15","usgsCitation":"Morman, S.A., and Plumlee, G.S., 2013, Dust and human health, chap. 15 of Mineral dust: A key player in the Earth system, p. 385-409, https://doi.org/10.1007/978-94-017-8978-3_15.","productDescription":"25 p.","startPage":"385","endPage":"409","ipdsId":"IP-045014","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":294731,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2014-06-28","publicationStatus":"PW","scienceBaseUri":"542d1799e4b092f17defc5a3","contributors":{"editors":[{"text":"Knippertz, Peter","contributorId":112196,"corporation":false,"usgs":true,"family":"Knippertz","given":"Peter","email":"","affiliations":[],"preferred":false,"id":509629,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Stuut, Jan-Berend W.","contributorId":111791,"corporation":false,"usgs":true,"family":"Stuut","given":"Jan-Berend","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":509628,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Morman, Suzette A. 0000-0002-2532-1033 smorman@usgs.gov","orcid":"https://orcid.org/0000-0002-2532-1033","contributorId":996,"corporation":false,"usgs":true,"family":"Morman","given":"Suzette","email":"smorman@usgs.gov","middleInitial":"A.","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":485738,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumlee, Geoffrey S. 0000-0002-9607-5626 gplumlee@usgs.gov","orcid":"https://orcid.org/0000-0002-9607-5626","contributorId":960,"corporation":false,"usgs":true,"family":"Plumlee","given":"Geoffrey","email":"gplumlee@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":485737,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70128155,"text":"70128155 - 2013 - Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation","interactions":[],"lastModifiedDate":"2014-10-07T08:56:56","indexId":"70128155","displayToPublicDate":"2014-06-01T08:55:53","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation","docAbstract":"Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32° to 49° latitude and −124.7° to −112.9° longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra Nevada Mountains.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Climatology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Royal Meteorological Society","publisherLocation":"Chichester","doi":"10.1002/joc.3835","usgsCitation":"Alvarez, O., Guo, Q., Klinger, R.C., Li, W., and Doherty, P., 2013, Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation: International Journal of Climatology, v. 34, no. 7, p. 2258-2268, https://doi.org/10.1002/joc.3835.","productDescription":"11 p.","startPage":"2258","endPage":"2268","numberOfPages":"11","ipdsId":"IP-050933","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":294969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294953,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/joc.3835"}],"volume":"34","issue":"7","noUsgsAuthors":false,"publicationDate":"2013-10-18","publicationStatus":"PW","scienceBaseUri":"543500a1e4b0a4f4b46a237e","contributors":{"authors":[{"text":"Alvarez, Otto","contributorId":86284,"corporation":false,"usgs":true,"family":"Alvarez","given":"Otto","affiliations":[],"preferred":false,"id":502779,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guo, Qinghua","contributorId":32855,"corporation":false,"usgs":true,"family":"Guo","given":"Qinghua","affiliations":[],"preferred":false,"id":502777,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klinger, Robert C. 0000-0003-3193-3199 rcklinger@usgs.gov","orcid":"https://orcid.org/0000-0003-3193-3199","contributorId":5395,"corporation":false,"usgs":true,"family":"Klinger","given":"Robert","email":"rcklinger@usgs.gov","middleInitial":"C.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":502776,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, Wenkai","contributorId":108044,"corporation":false,"usgs":true,"family":"Li","given":"Wenkai","affiliations":[],"preferred":false,"id":502780,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doherty, Paul","contributorId":38494,"corporation":false,"usgs":true,"family":"Doherty","given":"Paul","affiliations":[],"preferred":false,"id":502778,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70116725,"text":"70116725 - 2013 - Modeling erosion of ice-rich permafrost bluffs along the Alaskan Beaufort Sea coast","interactions":[],"lastModifiedDate":"2014-07-16T09:23:42","indexId":"70116725","displayToPublicDate":"2014-05-28T09:20:05","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Modeling erosion of ice-rich permafrost bluffs along the Alaskan Beaufort Sea coast","docAbstract":"The Arctic climate is changing, inducing accelerating retreat of ice-rich permafrost coastal\nbluffs. Along Alaska’s Beaufort Sea coast, erosion rates have increased roughly threefold from 6.8 to\n19 m yr−1 since 1955 while the sea ice-free season has increased roughly twofold from 45 to 100 days since\n1979. We develop a numerical model of bluff retreat to assess the relative roles of the length of sea ice-free\nseason, sea level, water temperature, nearshore wavefield, and permafrost temperature in controlling\nerosion rates in this setting. The model captures the processes of erosion observed in short-term\nmonitoring experiments along the Beaufort Sea coast, including evolution of melt notches, topple of ice\nwedge-bounded blocks, and degradation of these blocks. Model results agree with time-lapse imagery\nof bluff evolution and time series of ocean-based instrumentation. Erosion is highly episodic with 40% of\nerosion is accomplished during less than 5% of the sea ice-free season. Among the formulations of the\nsubmarine erosion rate we assessed, we advocate those that employ both water temperature and nearshore\nwavefield. As high water levels are a prerequisite for erosion, any future changes that increase the frequency\nwith which water levels exceed the base of the bluffs will increase rates of coastal erosion. The certain\nincreases in sea level and potential changes in storminess will both contribute to this effect. As water\ntemperature also influences erosion rates, any further expansion of the sea ice-free season into the\nmidsummer period of greatest insolation is likely to result in an additional increase in coastal retreat rates.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research F: Earth Surface","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/2013JF002845","usgsCitation":"Barnhart, K.R., Anderson, R., Overeem, I., Wobus, C., Clow, G.D., and Urban, F., 2013, Modeling erosion of ice-rich permafrost bluffs along the Alaskan Beaufort Sea coast: Journal of Geophysical Research F: Earth Surface, v. 119, no. 5, p. 1155-1179, https://doi.org/10.1002/2013JF002845.","productDescription":"25 p.","startPage":"1155","endPage":"1179","numberOfPages":"25","ipdsId":"IP-052403","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":473351,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013jf002845","text":"Publisher Index Page"},{"id":290194,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2013JF002845"},{"id":290242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea Coast","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -156.11,68.68 ], [ -156.11,74.68 ], [ -105.1,74.68 ], [ -105.1,68.68 ], [ -156.11,68.68 ] ] ] } } ] }","volume":"119","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-05-28","publicationStatus":"PW","scienceBaseUri":"53c79f05e4b0194841642477","contributors":{"authors":[{"text":"Barnhart, Katherine R.","contributorId":42142,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":495837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Robert S.","contributorId":102396,"corporation":false,"usgs":true,"family":"Anderson","given":"Robert S.","affiliations":[],"preferred":false,"id":495839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overeem, Irina","contributorId":29320,"corporation":false,"usgs":true,"family":"Overeem","given":"Irina","affiliations":[],"preferred":false,"id":495836,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wobus, Cameron","contributorId":26978,"corporation":false,"usgs":true,"family":"Wobus","given":"Cameron","email":"","affiliations":[],"preferred":false,"id":495835,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clow, Gary D. 0000-0002-2262-3853 clow@usgs.gov","orcid":"https://orcid.org/0000-0002-2262-3853","contributorId":2066,"corporation":false,"usgs":true,"family":"Clow","given":"Gary","email":"clow@usgs.gov","middleInitial":"D.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":495834,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Urban, Frank E. 0000-0002-1329-1703","orcid":"https://orcid.org/0000-0002-1329-1703","contributorId":80918,"corporation":false,"usgs":true,"family":"Urban","given":"Frank E.","affiliations":[],"preferred":false,"id":495838,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70095241,"text":"70095241 - 2013 - Desert shrub responses to experimental modification of precipitation seasonality and soil depth: relationship to the two-layer model and ecohydrological niche","interactions":[],"lastModifiedDate":"2014-06-27T13:50:25","indexId":"70095241","displayToPublicDate":"2014-05-14T13:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Desert shrub responses to experimental modification of precipitation seasonality and soil depth: relationship to the two-layer model and ecohydrological niche","docAbstract":"1. Ecohydrological niches are important for understanding plant community responses to climate shifts, particularly in dry lands. According to the two-layer hypothesis, selective use of deep-soil water increases growth or persistence of woody species during warm and dry summer periods and thereby contributes to their coexistence with shallow-rooted herbs in dry ecosystems. The resource-pool hypothesis further suggests that shallow-soil water benefits growth of all plants while deep-soil water primarily enhances physiological maintenance and survival of woody species. Few studies have directly tested these by manipulating deep-soil water availability and observing the long-term outcomes.
\n2. We predicted that factors promoting infiltration and storage of water in deep soils, specifically greater winter precipitation and soil depth, would enhance Artemisia tridentata (big sagebrush) in cold, winter-wet/summer-dry desert. Sagebrush responses to 20 years of winter irrigation were compared to summer- or no irrigation, on plots having relatively deep or shallow soils (2 m vs. 1 m depths).
\n3. Winter irrigation increased sagebrush cover, and crown and canopy volumes, but not density (individuals/plot) compared to summer or no irrigation, on deep-soil plots. On shallow-soil plots, winter irrigation surprisingly decreased shrub cover and size, and summer irrigation had no effect. Furthermore, multiple regression suggested that the variations in growth were related (i) firstly to water in shallow soils (0-0.2 m) and secondly to deeper soils (> 1 m deep) and (ii) more by springtime than by midsummer soil water. Water-use efficiency increased considerably on shallow soils without irrigation and was lowest with winter irrigation.
\n4. Synthesis. Sagebrush was more responsive to the seasonal timing of precipitation than to total annual precipitation. Factors that enhanced deep-water storage (deeper soils plus more winter precipitation) led to increases in Artemisia tridentata that were consistent with the two-layer hypothesis, and the contribution of shallow water to growth on these plots was consistent with the resource-pool hypothesis. However, shallow-soil water also had negative effects on sagebrush, suggesting an ecohydrological trade-off not considered in these or related theories. The interaction between precipitation timing and soil depth indicates that increased winter precipitation could lead to a mosaic of increases and decreases in A. tridentata across landscapes having variable soil depth.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/1365-2745.12266","usgsCitation":"Germino, M., and Reinhardt, K., 2013, Desert shrub responses to experimental modification of precipitation seasonality and soil depth: relationship to the two-layer model and ecohydrological niche: Journal of Ecology, v. 102, no. 4, p. 989-997, https://doi.org/10.1111/1365-2745.12266.","productDescription":"9 p.","startPage":"989","endPage":"997","numberOfPages":"9","ipdsId":"IP-052846","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473352,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2745.12266","text":"Publisher Index Page"},{"id":288083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288081,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1365-2745.12266"}],"country":"United States","state":"Idaho","otherGeospatial":"Snake River Plain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.8726,42.4829 ], [ -116.8726,44.3356 ], [ -111.3496,44.3356 ], [ -111.3496,42.4829 ], [ -116.8726,42.4829 ] ] ] } } ] }","volume":"102","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-05-14","publicationStatus":"PW","scienceBaseUri":"53903feae4b04eea98bf8509","contributors":{"authors":[{"text":"Germino, Matthew J.","contributorId":50029,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[],"preferred":false,"id":491149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reinhardt, Keith","contributorId":11949,"corporation":false,"usgs":true,"family":"Reinhardt","given":"Keith","affiliations":[],"preferred":false,"id":491148,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70058631,"text":"70058631 - 2013 - Monitoring gray wolf populations using multiple survey methods","interactions":[],"lastModifiedDate":"2014-05-06T15:55:20","indexId":"70058631","displayToPublicDate":"2014-05-06T15:28:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring gray wolf populations using multiple survey methods","docAbstract":"The behavioral patterns and large territories of large carnivores make them challenging to monitor. Occupancy modeling provides a framework for monitoring population dynamics and distribution of territorial carnivores. We combined data from hunter surveys, howling and sign surveys conducted at predicted wolf rendezvous sites, and locations of radiocollared wolves to model occupancy and estimate the number of gray wolf (Canis lupus) packs and individuals in Idaho during 2009 and 2010. We explicitly accounted for potential misidentification of occupied cells (i.e., false positives) using an extension of the multi-state occupancy framework. We found agreement between model predictions and distribution and estimates of number of wolf packs and individual wolves reported by Idaho Department of Fish and Game and Nez Perce Tribe from intensive radiotelemetry-based monitoring. Estimates of individual wolves from occupancy models that excluded data from radiocollared wolves were within an average of 12.0% (SD = 6.0) of existing statewide minimum counts. Models using only hunter survey data generally estimated the lowest abundance, whereas models using all data generally provided the highest estimates of abundance, although only marginally higher. Precision across approaches ranged from 14% to 28% of mean estimates and models that used all data streams generally provided the most precise estimates. We demonstrated that an occupancy model based on different survey methods can yield estimates of the number and distribution of wolf packs and individual wolf abundance with reasonable measures of precision. Assumptions of the approach including that average territory size is known, average pack size is known, and territories do not overlap, must be evaluated periodically using independent field data to ensure occupancy estimates remain reliable. Use of multiple survey methods helps to ensure that occupancy estimates are robust to weaknesses or changes in any 1 survey method. Occupancy modeling may be useful for standardizing estimates across large landscapes, even if survey methods differ across regions, allowing for inferences about broad-scale population dynamics of wolves.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.654","usgsCitation":"Ausband, D., Rich, L.N., Glenn, E., Mitchell, M.S., Zager, P., Miller, D.A., Waits, L.P., Ackerman, B.B., and Mack, C.M., 2013, Monitoring gray wolf populations using multiple survey methods: Journal of Wildlife Management, v. 78, no. 2, p. 335-346, https://doi.org/10.1002/jwmg.654.","productDescription":"12 p.","startPage":"335","endPage":"346","ipdsId":"IP-048939","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":286941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286940,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.654"}],"country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.24,41.99 ], [ -117.24,49.00 ], [ -111.04,49.00 ], [ -111.04,41.99 ], [ -117.24,41.99 ] ] ] } } ] }","volume":"78","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-02-13","publicationStatus":"PW","scienceBaseUri":"5369f651e4b063fb73c0a9e7","contributors":{"authors":[{"text":"Ausband, David E.","contributorId":51441,"corporation":false,"usgs":true,"family":"Ausband","given":"David E.","affiliations":[],"preferred":false,"id":487207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rich, Lindsey N.","contributorId":42119,"corporation":false,"usgs":true,"family":"Rich","given":"Lindsey","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":487206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, Elizabeth M.","contributorId":96568,"corporation":false,"usgs":true,"family":"Glenn","given":"Elizabeth M.","affiliations":[],"preferred":false,"id":487211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":487203,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zager, Pete","contributorId":90645,"corporation":false,"usgs":true,"family":"Zager","given":"Pete","affiliations":[],"preferred":false,"id":487210,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, David A.W. davidmiller@usgs.gov","contributorId":4043,"corporation":false,"usgs":true,"family":"Miller","given":"David","email":"davidmiller@usgs.gov","middleInitial":"A.W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":487204,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waits, Lisette P.","contributorId":87673,"corporation":false,"usgs":true,"family":"Waits","given":"Lisette","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":487209,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ackerman, Bruce B.","contributorId":6526,"corporation":false,"usgs":true,"family":"Ackerman","given":"Bruce","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":487205,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mack, Curt M.","contributorId":58948,"corporation":false,"usgs":true,"family":"Mack","given":"Curt","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":487208,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70150315,"text":"70150315 - 2013 - Effects of predators on fish and crayfish survival in intermittent streams","interactions":[],"lastModifiedDate":"2015-07-01T13:52:15","indexId":"70150315","displayToPublicDate":"2014-05-01T12:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Effects of predators on fish and crayfish survival in intermittent streams","docAbstract":"Predation from aquatic and terrestrial predators arc important factors structuring the size and depth distribution of aquatic prey. We conducted mesocosm and tethering experiments on Little Mulberry Creek in northwest Arkansas during low flows to examine the effects of predators on fish and crayfish survival in intermittent streams Using shallow artificial pools (10 cm deep) and predator exclusions, we tested the hypothesis that large-bodied fish are at greater risk from terrestrial predators in shallow habitats compared to small-bodied individuals. Twenty-four circular pools (12 open top. 12 closed top) were stocked with two size classes of Campostoma anomalum (Central Stonerller) and deployed systematically in a single stream pool. In addition, we used a crayfish tethering experiment to test the hypothesis that the survival of small and large crayfish is greater in shallow and deep habitats, respectively. We tethered two size classes of Orconectes meeki meeki (Meek's Crayfish) along shallow and deep transects in two adjacent stream pools and measured survival for 15 days. During both experiments, we monitored the presence or absence of predators by visual observation and from scat surveys. We demonstrated a negative effect of terrestrial predators on Central Stonerller survival in the artificial pools, and larger individuals were more susceptible to predation. In contrast, small crayfish experienced low survival at all depths and large crayfish were preyed upon much less intensively during the tethering study, particularly in the pool with larger substrate. More studies are needed to understand how stream drying and environmental heterogeneity influence the complex interactions between predator and prey populations in intermittent streams.
","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/058.012.0115","usgsCitation":"Dekar, M.P., and Magoulick, D.D., 2013, Effects of predators on fish and crayfish survival in intermittent streams: Southeastern Naturalist, v. 12, no. 1, p. 197-208, https://doi.org/10.1656/058.012.0115.","productDescription":"12 p.","startPage":"197","endPage":"208","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-030770","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Little Mulberry Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.515625,\n 35.84787403967154\n ],\n [\n -93.570556640625,\n 35.755428369259626\n ],\n [\n -93.61724853515625,\n 35.706377408871774\n ],\n [\n -93.64608764648438,\n 35.67068501330238\n ],\n [\n -93.68865966796875,\n 35.66399091134812\n ],\n [\n -93.69964599609374,\n 35.679609609368576\n ],\n [\n -93.515625,\n 35.84787403967154\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55950f2fe4b0b6d21dd6cbe0","contributors":{"authors":[{"text":"Dekar, Matthew P.","contributorId":139245,"corporation":false,"usgs":false,"family":"Dekar","given":"Matthew","email":"","middleInitial":"P.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":564071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":556697,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70103284,"text":"sim3024 - 2013 - Geodynamics map of northeast Asia","interactions":[],"lastModifiedDate":"2023-05-26T15:51:07.226277","indexId":"sim3024","displayToPublicDate":"2014-04-30T14:26:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3024","title":"Geodynamics map of northeast Asia","docAbstract":"This map portrays the geodynamics of Northeast Asia at a scale of 1:5,000,000 using the concepts of plate tectonics and analysis of terranes and overlap assemblages. The map is the result of a detailed compilation and synthesis at 5 million scale and is part of a major international collaborative study of the mineral resources, metallogenesis, and tectonics of northeast Asia conducted from 1997 through 2002 by geologists from earth science agencies and universities in Russia, Mongolia, northeastern China, South Korea, Japan, and the USA.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3024","collaboration":"Prepared in collaboration with Russian Academy of Sciences, Mongolian Academy of Sciences, Jilin University, Korean Institute of Geoscience and Minerals, Geological Survey of Japan/National Institute of Advanced Industrial Science and Technology","usgsCitation":"Parfenov, L., Khanchuk, A.I., Badarch, G., Miller, R.J., Naumova, V., Nokleberg, W.J., Ogasawara, M., Prokopiev, A.V., and Yan, H., 2013, Geodynamics map of northeast Asia: U.S. Geological Survey Scientific Investigations Map 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Leonid M.","contributorId":45385,"corporation":false,"usgs":true,"family":"Parfenov","given":"Leonid M.","affiliations":[],"preferred":false,"id":493247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Khanchuk, Alexander I.","contributorId":19585,"corporation":false,"usgs":true,"family":"Khanchuk","given":"Alexander","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":493245,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Badarch, Gombosuren","contributorId":6940,"corporation":false,"usgs":true,"family":"Badarch","given":"Gombosuren","email":"","affiliations":[],"preferred":false,"id":493243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Robert J. rjmiller@usgs.gov","contributorId":2516,"corporation":false,"usgs":true,"family":"Miller","given":"Robert","email":"rjmiller@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science 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Asia","interactions":[],"lastModifiedDate":"2023-05-26T15:56:06.537967","indexId":"sim3022","displayToPublicDate":"2014-04-30T14:11:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3022","title":"Metallogenic belt and mineral deposit maps of northeast Asia","docAbstract":"This report contains explanatory material and summary tables for lode mineral deposits and placer districts (Map A, sheet 1) and metallogenic belts of Northeast Asia (Maps B, C, and D on sheets 2, 3, and 4, respectively). The map region includes eastern Siberia, southeastern Russia, Mongolia, northeast China, and Japan. A large group of geologists—members of the joint international project, Major Mineral Deposits, Metallogenesis, and Tectonics of Northeast Asia—prepared the maps, tables, and introductory text. This is a cooperative project with the Russian Academy of Sciences, Mongolian Academy of Sciences, Mongolian National University, Ulaanbaatar, Mongolian Technical University, Mineral Resources Authority of Mongolia, Geological Research Institute, Jilin University, China Geological Survey, Korea Institute of Geoscience and Mineral Resources, Geological Survey of Japan, and U.S. Geological Survey. This report is one of a series of reports on the mineral resources, geodynamics, and metallogenesis of Northeast Asia. Companion studies include (1) a detailed geodynamics map of Northeast Asia (Parfenov and others, 2003); (2) a compilation of major mineral deposit models (Rodionov and Nokleberg, 2000; Rodionov and others, 2000); (3) a series of metallogenic belt maps (Obolenskiy and others, 2004); (4) location map of lode mineral deposits and placer districts of Northeast Asia (Ariunbileg and others, 2003b); (5) descriptions of metallogenic belts (Rodionov and others, 2004); (6) a database on significant metalliferous and selected nonmetalliferous lode deposits and selected placer districts (Ariunbileg and others, 2003a); and (7) a series of summary project publications (Ariunbileg and 74 others, 2003b).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3022","collaboration":"Prepared in collaboration with Russian Academy of Sciences, Mongolian Academy of Sciences, Jilin University, Korean Institute of Geoscience and Minerals, Geological Survey of Japan/National Institute of Advanced Industrial Science and Technology","usgsCitation":"Obolenskiy, A.A., Rodionov, S.M., Dejidmaa, G., Gerel, O., Hwang, D., Miller, R.J., Nokleberg, W.J., Ogasawara, M., Smelov, A., Yan, H., and Seminskiy, Z.V., 2013, Metallogenic belt and mineral deposit maps of northeast Asia: U.S. Geological Survey Scientific Investigations Map 3022, 4 Sheets: 46.35 x 39.53 inches and smaller; Pamphlet: i, 14 p.; Readme; Metadata; Database; 3 Tables, https://doi.org/10.3133/sim3022.","productDescription":"4 Sheets: 46.35 x 39.53 inches and smaller; Pamphlet: i, 14 p.; Readme; Metadata; Database; 3 Tables","numberOfPages":"16","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":286814,"rank":13,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3022.jpg"},{"id":286802,"rank":6,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3022/","linkFileType":{"id":5,"text":"html"}},{"id":286810,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_data.zip"},{"id":286807,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_pamphlet.pdf"},{"id":286811,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_Table%201.zip"},{"id":286812,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_Table%202.zip"},{"id":286813,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_Table%203.zip"},{"id":286808,"rank":12,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_readme.txt"},{"id":286804,"rank":11,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_sheet2.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":286805,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_sheet3.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":286806,"rank":9,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_sheet4.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":286803,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_sheet1.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":286809,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3022/downloads/metadata/"}],"scale":"7500000","projection":"Lambert Azimuthal equal-area projection","country":"China, Japan, Mongolia, Russia","otherGeospatial":"Asia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 75.0,32.0 ], [ 75.0,82.0 ], [ 144.0,82.0 ], [ 144.0,32.0 ], [ 75.0,32.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53620d52e4b0c409c6289a30","contributors":{"authors":[{"text":"Obolenskiy, Alexander A. 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