The summer of 2005 began with such promise for wolves in Yellowstone. The population had been at an all-time high the last few years, and the wolves appeared to be in good condition. Several packs had been particularly busy during the breeding season, and early summer pup counts suggested another healthy crop of new wolves rising through the ranks.
","language":"English","publisher":"National Park Service","usgsCitation":"Almberg, E., Cross, P.C., Hudson, P., Dobson, A.P., Smith, D.W., and Stahler, D.R., 2016, Infectious diseases of wolves in Yellowstone: Yellowstone Science, v. 24, no. 1, p. 47-49.","productDescription":"3 p.","startPage":"47","endPage":"49","numberOfPages":"3","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069334","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":325233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":325172,"type":{"id":15,"text":"Index Page"},"url":"https://www.nps.gov/yell/learn/yellowstone-science-24-1-celebrating-20-years-of-wolves.htm"}],"country":"United States","state":"Colorado","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.149169921875,\n 43.5843700152048\n ],\n [\n -109.149169921875,\n 44.99588261816546\n ],\n [\n -107.76489257812499,\n 44.99588261816546\n ],\n [\n -107.76489257812499,\n 43.5843700152048\n ],\n [\n -109.149169921875,\n 43.5843700152048\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5787662ee4b0d27deb36e186","contributors":{"authors":[{"text":"Almberg, Emily S.","contributorId":101111,"corporation":false,"usgs":true,"family":"Almberg","given":"Emily S.","affiliations":[],"preferred":false,"id":642326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":642325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hudson, Peter J.","contributorId":85056,"corporation":false,"usgs":true,"family":"Hudson","given":"Peter J.","affiliations":[],"preferred":false,"id":642327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dobson, Andrew P.","contributorId":63693,"corporation":false,"usgs":true,"family":"Dobson","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":642328,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Douglas W.","contributorId":95727,"corporation":false,"usgs":true,"family":"Smith","given":"Douglas","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":642329,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stahler, Daniel R.","contributorId":57703,"corporation":false,"usgs":true,"family":"Stahler","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":642330,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70170935,"text":"70170935 - 2016 - Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model","interactions":[],"lastModifiedDate":"2025-05-14T18:39:18.093972","indexId":"70170935","displayToPublicDate":"2016-06-29T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model","docAbstract":"Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. 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","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2016.05.016","usgsCitation":"Ellefsen, K.J., and Smith, D., 2016, Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model: Applied Geochemistry, v. 75, p. 200-210, https://doi.org/10.1016/j.apgeochem.2016.05.016.","productDescription":"11 p.","startPage":"200","endPage":"210","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073180","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":324600,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":470811,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2016.05.016","text":"Publisher Index Page"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107,\n 37\n ],\n [\n -107,\n 41\n ],\n [\n -102,\n 41\n ],\n [\n -102,\n 37\n ],\n [\n -107,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774e345e4b07dd077c5fcab","contributors":{"authors":[{"text":"Ellefsen, Karl J. 0000-0003-3075-4703 ellefsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3075-4703","contributorId":789,"corporation":false,"usgs":true,"family":"Ellefsen","given":"Karl","email":"ellefsen@usgs.gov","middleInitial":"J.","affiliations":[{"id":82803,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":false}],"preferred":true,"id":629166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David 0000-0002-9543-800X","orcid":"https://orcid.org/0000-0002-9543-800X","contributorId":169280,"corporation":false,"usgs":true,"family":"Smith","given":"David","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":629167,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70171109,"text":"sir20165067 - 2016 - Geologic and geophysical models for Osage County, Oklahoma, with implications for groundwater resources","interactions":[],"lastModifiedDate":"2025-05-14T18:51:50.000213","indexId":"sir20165067","displayToPublicDate":"2016-06-16T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5067","title":"Geologic and geophysical models for Osage County, Oklahoma, with implications for groundwater resources","docAbstract":"This report summarizes a three-dimensional (3-D) geologic model that was constructed to provide a framework to investigate groundwater resources of the Osage Nation in northeastern Oklahoma. This report also presents an analysis of an airborne electromagnetic (AEM) survey that assessed the spatial variation of electrical resistivity to depths as great as 300 meters in the subsurface. The report and model provide support for a countywide assessment of groundwater resources, emphasizing the Upper Pennsylvanian rock units in the shallow subsurface of central and eastern Osage County having electrical resistivity properties that may indicate aquifers.
\nSurface outcrops and subsurface stratigraphic picks on wire-line geophysical logs of Upper Pennsylvanian–Lower Permian sedimentary rock were used to construct a 3-D model of the geologic subsurface as an aid for evaluating groundwater resources in Osage County. Quaternary alluvium and terraces along major streams and the Arkansas River are included in the geologic framework model. Data from the AEM survey were subjected to quality-control procedures, truncated at depth of investigation (DOI), and then used to build a 3-D electrical resistivity model making use of secondary and tertiary interpolation profiles between primary data profiles. The AEM data highlight westward-inclined resistivity gradients that parallel the shallow dip of bedrock strata; bodies have resistivity >30 ohm-meters, and extend as much as 10 kilometers (km) down the dip of host geologic units. Volume analysis and internal imaging of an integrated 3-D geology and electrical resistivity model give a proxy for likely aquifer units with large relative volumes of high resistivity: Quaternary alluvium, Elgin Sandstone Lentil in the upper part of the Vamoosa Group, Tallant Formation, and parts of a combined Wann-Iola-Chanute Formation. Less voluminous, high-resistivity bodies correspond to intervals in the lower part of the Vamoosa Group in the east-central part of the county and probable limestone intervals in the upper part of the Vanoss Group in the northwest part of the county. Northwestern and eastern troughs of potable water previously defined for central Osage County generally correspond to down-dip projections of high-resistivity bodies associated with the Elgin Sandstone Lentil of the Vamoosa Group and Tallant Formation, respectively.
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Center Director, USGS Geosciences and Environmental Change Science Center
Box 25046, Mail Stop 980
Denver, CO 80225
Longitudinal gradients of fish assemblage and habitat structure were investigated in the Kootenai River of northern Idaho. A total of 43 500-m river reaches was sampled repeatedly with several techniques (boat-mounted electrofishing, hoop nets and benthic trawls) in the summers of 2012 and 2013. Differences in habitat and fish assemblage structure were apparent along the longitudinal gradient of the Kootenai River. Habitat characteristics (e.g. depth, substrate composition and water velocity) were related to fish assemblage structure in three different geomorphic river sections. Upper river sections were characterized by native salmonids (e.g. mountain whitefish Prosopium williamsoni), whereas native cyprinids (peamouth Mylocheilus caurinus, northern pikeminnow Ptychocheilus oregonensis) and non-native fishes (pumpkinseed Lepomis gibbosus, yellow perch Perca flavescens) were common in the downstream section. Overall, a general pattern of species addition from upstream to downstream sections was discovered and is likely related to increased habitat complexity and additions of non-native species in downstream sections. Assemblage structure of the upper sections were similar, but were both dissimilar to the lower section of the Kootenai River. Species-specific hurdle regressions indicated the relationships among habitat characteristics and the predicted probability of occurrence and relative abundance varied by species. Understanding fish assemblage structure in relation to habitat could improve conservation efforts of rare fishes and improve management of coldwater river systems.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/rra.2877","usgsCitation":"Smith, C.D., Quist, M.C., and Hardy, R.S., 2016, Fish assemblage structure and habitat associations in a large western river system: River Research and Applications, v. 32, no. 4, p. 622-638, https://doi.org/10.1002/rra.2877.","productDescription":"17 p.","startPage":"622","endPage":"638","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053516","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.13623046874999,\n 46.875213396722685\n ],\n [\n -116.01562499999999,\n 46.875213396722685\n ],\n [\n -116.01562499999999,\n 49.05227025601607\n ],\n [\n -117.13623046874999,\n 49.05227025601607\n ],\n [\n -117.13623046874999,\n 46.875213396722685\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-15","publicationStatus":"PW","scienceBaseUri":"575fcb1ee4b04f417c2b266f","contributors":{"authors":[{"text":"Smith, C. D.","contributorId":29785,"corporation":false,"usgs":true,"family":"Smith","given":"C.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":638618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839 mquist@usgs.gov","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":171392,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":637295,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hardy, R. S.","contributorId":171778,"corporation":false,"usgs":false,"family":"Hardy","given":"R.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":638619,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70169018,"text":"tm7C13 - 2016 - User’s guide for GcClust—An R package for clustering of regional geochemical data","interactions":[],"lastModifiedDate":"2025-05-14T19:06:32.9755","indexId":"tm7C13","displayToPublicDate":"2016-04-08T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-C13","title":"User’s guide for GcClust—An R package for clustering of regional geochemical data","docAbstract":"GcClust is a software package developed by the U.S. Geological Survey for statistical clustering of regional geochemical data, and similar data such as regional mineralogical data. Functions within the software package are written in the R statistical programming language. These functions, their documentation, and a copy of the user’s guide are bundled together in R’s unit of sharable code, which is called a “package.” The user’s guide includes step-by-step instructions showing how the functions are used to cluster data and to evaluate the clustering results. These functions are demonstrated in this report using test data, which are included in the package.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Computer Programs in Book 7: Automated Data Processing and Computations","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C13","usgsCitation":"Ellefsen, K.J, and Smith, D.B., 2016, User's guide for GcClust—An R package for clustering of regional geochemical data: U.S. Geological Survey report Techniques and Methods 7–C13, 21 p., https://dx.doi.org/10.3133/tm7c13.","productDescription":"Report: iv, 21 p.; Installation Instructions; Example R Scripts; GcClust; Read Me File","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072334","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":320329,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://github.com/USGS-R/GcClust","text":"GcClust Source Code","description":"TM 7-C13GcClust Source Code"},{"id":319810,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c13/GcClust_1.0.tar.gz","text":"GcClust","size":"1.74 MB","linkFileType":{"id":6,"text":"zip"},"description":"TM 7-C13 GcClust"},{"id":319809,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c13/ProcessScripts.R","text":"Example R scripts","size":"6.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"TM 7-C13 Example R scripts"},{"id":319808,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c13/InstallationInstructions.txt","text":"Installation Instructions","size":"2.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"TM 7-C13 Installation Instructions"},{"id":319807,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/tm/07/c13/00ReadMe.txt","text":"Read Me File","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"TM 7-C13 Read Me"},{"id":319806,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c13/tm7c13.pdf","text":"Report","size":"2.84 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 7-C13"},{"id":319805,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c13/coverthb.jpg"}],"publicComments":"This report is Chapter 13 of Section C: Computer Programs in Book 7: Automated Data Processing and Computations.","contact":"Center Director, USGS Central Mineral and Environmental Resources
Science Center
Box 25046, Mail Stop 973
Denver, CO 80225
A one-dimensional step-backwater model was developed by the U.S. Geological Survey (USGS) in cooperation with the U.S. Fish and Wildlife Service, Pee Dee National Wildlife Refuge, North Carolina, to provide a means for predicting flood-plain inundation. The model was developed for selected reaches of the Pee Dee River, Brown Creek, and Rocky River, using the U.S. Army Corps of Engineers Hydrologic Engineering Center River Analysis System (HEC-RAS) software. Multiple cross sections were defined on each modeled stream, and hydrologic data were collected between August 2011 and August 2013 at selected locations on the Pee Dee River and on its tributaries Brown Creek, Rocky River, and Thoroughfare Creek. Cross-section, stage, and flow data were used to develop the model and simulate water-surface profiles at 1.0-foot increments at the USGS streamgage Pee Dee River at Pee Dee Refuge near Ansonville, N.C. The profiles were produced for 31 selected water levels that ranged from approximately 193.0 feet to 223.0 feet in elevation at the Pee Dee River at Pee Dee Refuge streamgage.
\nA series of digital flood-inundation maps were developed on the basis of the water-surface profiles produced by the model. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program Web site at http://water.usgs.gov/osw/flood_inundation, depict estimates of the areal extent and depth of flooding corresponding to selected water levels at the USGS streamgage Pee Dee River at Pee Dee Refuge near Ansonville, N.C. These maps, when combined with real-time water-level information from USGS streamgages, provide managers with critical information to help plan flood-response activities and resource protection efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155137","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Smith, D.G., and Wagner, C.R., 2016, Hydraulic model and flood-inundation maps developed for the Pee Dee National Wildlife Refuge, North Carolina: U.S. Geological Survey Scientific Investigations Report 2015–5137, 14 p., https://dx.doi.org/10.3133/sir20155137.","productDescription":"Document: vi, 14 p.; Metadata: 3 downloadable files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069288","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":319758,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5137/sir20155137.pdf","size":"1.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5137"},{"id":319789,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5137/sir20155137_peedee.xml","size":"15.6 KB xml","description":"SIR 2015-5137"},{"id":319787,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5137/sir20155137_peedee-grids.zip","size":"302 MB grids","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5137"},{"id":319788,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5137/sir20155137_peedee-shapefiles.zip","size":"18.8 MB","linkFileType":{"id":4,"text":"shapefile"},"description":"SIR 2015-5137"},{"id":319757,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5137/coverthb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Pee Dee National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.266667,\n 35.233333\n ],\n [\n -80.266667,\n 35\n ],\n [\n -79.85,\n 35\n ],\n [\n -79.85,\n 35.233333\n ],\n [\n -80.266667,\n 35.233333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
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Parasites, by definition, extract energy from their hosts and thus affect trophic and food web dynamics even when the parasite may have limited effects on host population size. We studied the energetic costs of mange (Sarcoptes scabiei) in wolves (Canis lupus) using thermal cameras to estimate heat losses associated with compromised insulation during the winter. We combined the field data of known, naturally infected wolves with data set on captive wolves with shaved patches of fur as a positive control to simulate mange-induced hair loss. We predict that during the winter in Montana, more severe mange infection increases heat loss by around 5.2 to 12 MJ per night (1240 to 2850 kcal, or a 65% to 78% increase) for small and large wolves, respectively accounting for wind effects. To maintain body temperature would require a significant proportion of a healthy wolf's total daily energy demands (18-22 MJ/day). We also predict how these thermal costs may increase in colder climates by comparing our predictions in Bozeman, Montana to those from a place with lower ambient temperatures (Fairbanks, Alaska). Contrary to our expectations, the 14°C differential between these regions was not as important as the potential differences in wind speed. These large increases in energetic demands can be mitigated by either increasing consumption rates or decreasing other energy demands. Data from GPS-collared wolves indicated that healthy wolves move, on average, 17 km per day, which was reduced by 1.5, 1.8 and 6.5 km for light, medium, and severe hair loss. In addition, the wolf with the most hair loss was less active at night and more active during the day, which is the converse of the movement patterns of healthy wolves. At the individual level mange infections create significant energy demands and altered behavioral patterns, this may have cascading effects on prey consumption rates, food web dynamics, predator-prey interactions, and scavenger communities.
","language":"English","publisher":"Wiley","doi":"10.1890/15-1346.1","usgsCitation":"Cross, P.C., Almberg, E., Haase, C.G., Hudson, P., Maloney, S.K., Metz, M., Munn, A.J., Nugent, P., Putzeys, O., Stahler, D.R., Stewart, A.C., and Smith, D.W., 2016, Energetic costs of mange in wolves estimated from infrared thermography: Ecology, v. 97, no. 8, p. 1938-1948, https://doi.org/10.1890/15-1346.1.","productDescription":"11 p.","startPage":"1938","endPage":"1948","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067138","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471110,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"text":"Publisher Index Page"},{"id":319675,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.7474365234375,\n 44.66865287227321\n ],\n [\n -111.7474365234375,\n 45.590978249451936\n ],\n [\n -110.10498046875,\n 45.590978249451936\n ],\n [\n -110.10498046875,\n 44.66865287227321\n ],\n [\n -111.7474365234375,\n 44.66865287227321\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"97","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56fe3c32e4b075ab2b2aa0b4","chorus":{"doi":"10.1890/15-1346.1","url":"http://dx.doi.org/10.1890/15-1346.1","publisher":"Wiley-Blackwell","authors":"Cross P. C., Almberg E. S., Haase C. G., Hudson P. J., Maloney S. K., Metz M. C., Munn A. J., Nugent P., Putzeys O., Stahler D. R., Stewart A. C., Smith D. 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The terminus is often characterized by rapidly changing thermal and hydraulic conditions that result in abrupt shifts in surface water/groundwater (sw/gw) exchange patterns, creating the potential for unique biogeochemical processes and ecosystems. Worldwide shoreline development is changing stream-lake interfaces through channelization of stream mouths, i.e., channel straightening and bank stabilization to prevent natural meandering at the shoreline. In the central Sierra Nevada (USA), Lake Tahoe's shoreline has an abundance of both “unmodified” (i.e., not engineered though potentially impacted by broader watershed engineering) and channelized stream mouths. Two representative stream mouths along the lake's north shore, one channelized and one unmodified, were selected to compare and contrast water and heat exchanges. Hydraulic and thermal properties were monitored during separate campaigns in September 2012 and 2013 and sw/gw exchanges were estimated within the stream mouth-shoreline continuum. Heat-flow and water-flow patterns indicated clear differences in the channelized versus the unmodified stream mouth. For the channelized stream mouth, relatively modulated, cool-temperature, low-velocity longitudinal streambed flows discharged offshore beneath warmer buoyant lakeshore water. In contrast, a seasonal barrier bar formed across the unmodified stream mouth, creating higher-velocity subsurface flow paths and higher diurnal temperature variations relative to shoreline water. As a consequence, channelization altered sw/gw exchanges potentially altering biogeochemical processing and ecological systems in and near the stream mouth.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2015WR017013","usgsCitation":"Constantz, J., Naranjo, R.C., Niswonger, R.G., Allander, K.K., Neilson, B., Rosenberry, D.O., Smith, D.W., Rosecrans, C., and Stonestrom, D.A., 2016, Groundwater exchanges near a channelized versus unmodified stream mouth discharging to a subalpine lake: Water Resources Research, v. 52, no. 3, p. 2157-2177, https://doi.org/10.1002/2015WR017013.","productDescription":"21 p.","startPage":"2157","endPage":"2177","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061592","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":319737,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":471125,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index 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Using the same data, we show there is a step-cline in both the frequency of a mtDNA haplotype and in plumage variation roughly concordant with the currently recognized boundary between E. t. extimus and E. t adastus, the subspecies with which it shares the longest common boundary. The geographical pattern of plumage variation is also concordant with previous song analyses differentiating those 2 subspecies and identified birds in one low-latitude, high-elevation site in Arizona as the northern subspecies. We also demonstrate that the ecological niche modeling approach used by Zink yields the same result whether applied to the 2 flycatcher subspecies or to 2 unrelated species, E. t. extimus and Yellow Warbler (Setophaga petechia). As a result, any interpretation of those results as evidence for lack of ecological niche differentiation among Willow Flycatcher subspecies would also indicate no differentiation among recognized species and would therefore be an inappropriate standard for delineating subspecies. We agree that many analytical techniques now available to examine genetic, morphological, and ecological differentiation would improve our understanding of the distinctness (or lack thereof) of Willow Flycatcher subspecies, but we argue that currently available evidence supports protection of the Southwestern Willow Flycatcher under the Endangered Species Act.
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The spatiotemporal scaling of soil-air Hg fluxes identified that the largest emissions occurred from irrigated agricultural landscapes in California. Vegetation was shown to have a large impact on surface-air Hg fluxes due to both a reduction in solar radiation reaching the soil as well as from direct uptake of Hg in foliage. Despite high soil Hg emissions from some forested and other heavily vegetated regions, the net ecosystem flux (soil flux + vegetation uptake) was low. Conversely, sparsely vegetated regions showed larger net ecosystem emissions, which were similar in magnitude to atmospheric Hg deposition (except for the Mediterranean California region where soil emissions were higher). The net ecosystem flux results highlight the important role of landscape characteristics in effecting the balance between Hg sequestration and (re-)emission to the atmosphere.
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California","interactions":[],"lastModifiedDate":"2025-05-14T18:41:14.173917","indexId":"ofr20161021","displayToPublicDate":"2016-02-23T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1021","title":"Ecoregions of California","docAbstract":"Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. By recognizing the spatial differences in the capacities and potentials of ecosystems, ecoregions stratify the environment by its probable response to disturbance (Bryce and others, 1999). These general purpose regions are critical for structuring and implementing ecosystem management strategies across Federal agencies, State agencies, and nongovernment organizations that are responsible for different types of resources in the same geographical areas (Omernik and others, 2000).
The approach used to compile this map is based on the premise that ecological regions are hierarchical and can be identified through the analysis of the spatial patterns and the composition of biotic and abiotic phenomena that affect or reflect differences in ecosystem quality and integrity (Wiken, 1986; Omernik, 1987, 1995). These phenomena include geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another regardless of the hierarchical level. A Roman numeral hierarchical scheme has been adopted for different levels of ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997, map revised 2006). At level III, the continental United States contains 105 ecoregions and the conterminous United States has 85 ecoregions (U.S. Environmental Protection Agency, 2013). Level IV, depicted here for California, is a further refinement of level III ecoregions. Explanations of the methods used to define these ecoregions are given in Omernik (1995), Omernik and others (2000), and Omernik and Griffith (2014).
California has great ecological and biological diversity. The State contains offshore islands and coastal lowlands, large alluvial valleys, forested mountain ranges, deserts, and various aquatic habitats. There are 13 level III ecoregions and 177 level IV ecoregions in California and most continue into ecologically similar parts of adjacent States of the United States or Mexico (Bryce and others, 2003; Thorson and others, 2003; Griffith and others, 2014).
The California ecoregion map was compiled at a scale of 1:250,000. It revises and subdivides an earlier national ecoregion map that was originally compiled at a smaller scale (Omernik, 1987; U.S. Environmental Protection Agency, 2013). This poster is the result of a collaborative project primarily between U.S. Environmental Protection Agency (USEPA) Region IX, USEPA National Health and Environmental Effects Research Laboratory (Corvallis, Oregon), California Department of Fish and Wildlife (DFW), U.S. Department of Agriculture (USDA)–Natural Resources Conservation Service (NRCS), U.S. Department of the Interior–Geological Survey (USGS), and other State of California agencies and universities.
The project is associated with interagency efforts to develop a common framework of ecological regions (McMahon and others, 2001). Reaching that objective requires recognition of the differences in the conceptual approaches and mapping methodologies applied to develop the most common ecoregion-type frameworks, including those developed by the USDA–Forest Service (Bailey and others, 1994; Miles and Goudy, 1997; Cleland and others, 2007), the USEPA (Omernik 1987, 1995), and the NRCS (U.S. Department of Agriculture–Soil Conservation Service, 1981; U.S. Department of Agriculture–Natural Resources Conservation Service, 2006). As each of these frameworks is further refined, their differences are becoming less discernible. Regional collaborative projects such as this one in California, where some agreement has been reached among multiple resource-management agencies, are a step toward attaining consensus and consistency in ecoregion frameworks for the entire nation.
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\"}}]}","contact":"Western Geographic Science Center
U.S. Geological Survey
345 Middlefield Road, MS 531
Menlo Park, CA 94025
http://geography.wr.usgs.gov/
Quaking aspen (Populus tremuloides) is the most widespread tree species in North America and has supported a unique ecosystem for tens of thousands of years, yet is currently threatened by dramatic loss and possible local extinctions. While multiple factors such as climate change and fire suppression are thought to contribute to aspen’s decline, increased browsing by elk (Cervus elaphus), which have experienced dramatic population increases in the last ∼80 years, may severely inhibit aspen growth and regeneration. Fires are known to favor aspen recovery, but in the last several decades the spatial scale and intensity of wildfires has greatly increased, with poorly understood ramifications for aspen growth. Here, focusing on the 2000 Cerro Grande fire in central New Mexico – one of the earliest fires described as a “mega-fire” - we use three methods to examine the impact of elk browsing on aspen regeneration after a mega-fire. First, we use an exclosure experiment to show that aspen growing in the absence of elk were 3× taller than trees growing in the presence of elk. Further, aspen that were both protected from elk and experienced burning were 8.5× taller than unburned trees growing in the presence of elk, suggesting that the combination of release from herbivores and stimulation from fire creates the largest aspen growth rates. Second, using surveys at the landscape level, we found a correlation between elk browsing intensity and aspen height, such that where elk browsing was highest, aspen were shortest. This relationship between elk browsing intensity and aspen height was stronger in burned (r = −0.53) compared to unburned (r = −0.24) areas. Third, in conjunction with the landscape-level surveys, we identified possible natural refugia, microsites containing downed logs, shrubs etc. that may inhibit elk browsing by physically blocking aspen from elk or by impeding elk’s ability to move through the forest patch. We did not find any consistent patterns between refuge elements and aspen size or canopy cover suggesting that natural refugia are not aiding in aspen recruitment and that all young aspen were susceptible to browsing. In much of their normal range, aspen are not growing to large size classes, which threatens the future of this iconic species and calls into question the ability of ecosystems to recover from mega-fires. Our results highlight the importance of considering multiple interacting factors (i.e. fire and increased elk browsing) when considering aspen management and regeneration.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2015.11.020","usgsCitation":"Smith, D.S., Fettig, S.M., and Bowker, M.A., 2016, Elevated Rocky Mountain elk numbers prevent positive effects of fire on quaking aspen (Populus tremuloides) recruitment: Forest Ecology and Management, v. 362, p. 46-54, https://doi.org/10.1016/j.foreco.2015.11.020.","productDescription":"9 p.","startPage":"46","endPage":"54","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067527","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Cerro Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.42507553100586,\n 35.858309181565716\n ],\n [\n -106.42507553100586,\n 35.881122573005875\n ],\n [\n -106.38971328735352,\n 35.881122573005875\n ],\n [\n -106.38971328735352,\n 35.858309181565716\n ],\n [\n -106.42507553100586,\n 35.858309181565716\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"362","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"573ee3afe4b04a3a6a24acf8","contributors":{"authors":[{"text":"Smith, David Solance","contributorId":169498,"corporation":false,"usgs":false,"family":"Smith","given":"David","email":"","middleInitial":"Solance","affiliations":[{"id":25534,"text":"Dept. of Biological Sciences, Northern Arizona Univ, PO Box 15018, Flagstaff AZ 86011; current address: Denison Univ, Dept of Biology, PO Box 810, Granville, OH 43023. Email: smithd@denison.edu","active":true,"usgs":false}],"preferred":false,"id":629814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fettig, Stephen M.","contributorId":169499,"corporation":false,"usgs":false,"family":"Fettig","given":"Stephen","email":"","middleInitial":"M.","affiliations":[{"id":25535,"text":"U.S. National Park Service, Bandelier National Monument, 15 Entrance Rd., Los Alamos, NM 87544","active":true,"usgs":false}],"preferred":false,"id":629815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowker, Matthew A. mbowker@usgs.gov","contributorId":2875,"corporation":false,"usgs":true,"family":"Bowker","given":"Matthew","email":"mbowker@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":629813,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204449,"text":"70204449 - 2016 - Integrative modelling reveals mechanisms linking productivity and plant species richness","interactions":[],"lastModifiedDate":"2019-07-24T13:43:37","indexId":"70204449","displayToPublicDate":"2016-01-13T13:03:52","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Integrative modelling reveals mechanisms linking productivity and plant species richness","docAbstract":"How ecosystem productivity and species richness are interrelated is one of the most debated subjects in the history of ecology. Decades of intensive study have yet to discern the actual mechanisms behind observed global patterns. Here, by integrating the predictions from multiple theories into a single model and using data from 1,126 grassland plots spanning five continents, we detect the clear signals of numerous underlying mechanisms linking productivity and richness. We find that an integrative model has substantially higher explanatory power than traditional bivariate analyses. In addition, the specific results unveil several surprising findings that conflict with classical models. These include the isolation of a strong and consistent enhancement of productivity by richness, an effect in striking contrast with superficial data patterns. Also revealed is a consistent importance of competition across the full range of productivity values, in direct conflict with some (but not all) proposed models. The promotion of local richness by macroecological gradients in climatic favourability, generally seen as a competing hypothesis, is also found to be important in our analysis. The results demonstrate that an integrative modelling approach leads to a major advance in our ability to discern the underlying processes operating in ecological systems.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/nature16524","usgsCitation":"Grace, J.B., Anderson, T.M., Seabloom, E.W., Borer, E.T., Adler, P.B., Harpole, W., Hautier, Y., Hillebrand, H., Lind, E.M., Partel, M., Bakker, J.D., Buckley, Y.M., Crawley, M.J., Damschen, E.I., Davies, K.F., Fay, P.A., Firn, J., Gruner, D.S., Hector, A., Knops, J.M., MacDougall, A.S., Melbourne, B.A., Morgan, J.W., Orrock, J., Prober, S.M., and Smith, M., 2016, Integrative modelling reveals mechanisms linking productivity and plant species richness: Nature, v. 529, p. 390-393, https://doi.org/10.1038/nature16524.","productDescription":"4 p.","startPage":"390","endPage":"393","ipdsId":"IP-051258","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471330,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://dspace.library.uu.nl/handle/1874/344413","text":"External Repository"},{"id":365909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"529","noUsgsAuthors":false,"publicationDate":"2016-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":766959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, T. Michael","contributorId":203893,"corporation":false,"usgs":false,"family":"Anderson","given":"T.","email":"","middleInitial":"Michael","affiliations":[{"id":36744,"text":"Wake Forest University","active":true,"usgs":false}],"preferred":false,"id":766963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seabloom, Eric W.","contributorId":60762,"corporation":false,"usgs":false,"family":"Seabloom","given":"Eric","email":"","middleInitial":"W.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":766964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borer, Elizabeth T.","contributorId":45049,"corporation":false,"usgs":false,"family":"Borer","given":"Elizabeth","email":"","middleInitial":"T.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":766965,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adler, Peter B.","contributorId":64789,"corporation":false,"usgs":false,"family":"Adler","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":766966,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harpole, W Stanley","contributorId":131028,"corporation":false,"usgs":false,"family":"Harpole","given":"W Stanley","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":766967,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hautier, Yann","contributorId":84065,"corporation":false,"usgs":true,"family":"Hautier","given":"Yann","email":"","affiliations":[],"preferred":false,"id":766968,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hillebrand, Helmut","contributorId":83655,"corporation":false,"usgs":true,"family":"Hillebrand","given":"Helmut","email":"","affiliations":[],"preferred":false,"id":766969,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lind, Eric 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A.","contributorId":51443,"corporation":false,"usgs":true,"family":"Fay","given":"Philip","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":766977,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Firn, Jennifer","contributorId":66405,"corporation":false,"usgs":false,"family":"Firn","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":766978,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Gruner, Daniel S.","contributorId":195507,"corporation":false,"usgs":false,"family":"Gruner","given":"Daniel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":766979,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Hector, Andy","contributorId":102620,"corporation":false,"usgs":true,"family":"Hector","given":"Andy","email":"","affiliations":[],"preferred":false,"id":766980,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Knops, Johannes M.H.","contributorId":105843,"corporation":false,"usgs":true,"family":"Knops","given":"Johannes","email":"","middleInitial":"M.H.","affiliations":[],"preferred":false,"id":766981,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"MacDougall, Andrew S.","contributorId":39509,"corporation":false,"usgs":true,"family":"MacDougall","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":766982,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Melbourne, Brett A.","contributorId":86473,"corporation":false,"usgs":true,"family":"Melbourne","given":"Brett","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":766983,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Morgan, John W.","contributorId":88077,"corporation":false,"usgs":true,"family":"Morgan","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":766984,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Orrock, John L.","contributorId":18101,"corporation":false,"usgs":true,"family":"Orrock","given":"John L.","affiliations":[],"preferred":false,"id":766985,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Prober, Suzanne M.","contributorId":74498,"corporation":false,"usgs":false,"family":"Prober","given":"Suzanne","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":766986,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Smith, Melinda D.","contributorId":94028,"corporation":false,"usgs":true,"family":"Smith","given":"Melinda D.","affiliations":[],"preferred":false,"id":766987,"contributorType":{"id":1,"text":"Authors"},"rank":26}]}} ,{"id":70161841,"text":"ofr20161003 - 2016 - Evaluation of the hydraulic and biological performance of the portable floating fish collector at Cougar Reservoir and Dam, Oregon, 2014","interactions":[],"lastModifiedDate":"2016-01-12T15:38:42","indexId":"ofr20161003","displayToPublicDate":"2016-01-12T16:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1003","title":"Evaluation of the hydraulic and biological performance of the portable floating fish collector at Cougar Reservoir and Dam, Oregon, 2014","docAbstract":"The biological and hydraulic performance of a new portable floating fish collector (PFFC) located in a cul-de-sac within the forebay of Cougar Dam, Oregon, was evaluated during 2014. The purpose of the PFFC was to explore surface collection as a means to capture juvenile salmonids at one or more sites using a small, cost-effective, pilot-scale device. The PFFC used internal pumps to draw attraction flow over an inclined plane about 3 meters (m) deep, through a flume at a design velocity of as much as 6 feet per second (ft/s), and to empty a small amount of water and any entrained fish into a collection box. Performance of the PFFC was evaluated at 64 cubic feet per second (ft3/s) (Low) and 109 ft3/s (High) inflow rates alternated using a randomized-block schedule from May 27 to December 16, 2014. The evaluation of the biological performance was based on trap catch; behaviors, locations, and collection of juvenile Chinook salmon (Oncorhynchus tshawytscha) tagged with acoustic transmitters plus passive integrated transponder (PIT) tags; collection of juvenile Chinook salmon implanted with only PIT tags; and untagged fish monitored near and within the PFFC using acoustic cameras. The evaluation of hydraulic performance was based on measurements of water velocity and direction of flow in the PFFC.
\nThe PFFC collected 156 juvenile Chinook salmon and 280 individuals of other species, primarily dace (Cyprinidae) and largemouth bass (Micropterus salmoides). The collection included one of the 212 acoustic+PIT-tagged fish detected near the PFFC and two of the 1,505 PIT-tagged fish released near the head of the reservoir. No juvenile salmonids were collected between early July and early September when water temperatures near the water surface were greater than about 16 degrees Celsius (°C). Depths of acoustic+PIT-tagged fish indicated a preferential selection of water temperature of 13–15 °C, which was often deeper than the entrance to the PFFC, and those fish rarely were at depths with water temperatures greater than 16 °C. Dam passage of acoustic+PIT-tagged fish was similar to previous years, but much of the passage occurred prior to the date the PFFC began operation. Discovery Efficiency, the proportion of acoustic+PIT-tagged fish detected in the cul-de-sac that were within 10 m of the PFFC entrance and 0–6 m deep (the Discovery Zone), was 0.736 during the Low treatment and 0.639 during the High treatment. Entrance Efficiency, the proportion of fish in the Discovery Zone that were collected by the PFFC, was 0.007 during the Low treatment and 0.000 during the High treatment. Fish Collection Efficiency, the proportion of acoustic+PIT-tagged fish collected of those detected in the cul-de-sac, was 0.005 and 0.000 during the Low and High treatments, respectively. The areas of highest use by acoustic+PIT-tagged fish were between the stern of the PFFC and the outlet of the reservoir (a water temperature control tower), with the greatest use being near the tower.
\nResults from untagged fish detected with acoustic cameras indicated that most fish near and within the PFFC were in the 90–250-millimeter length bin and few were less than 60 millimeters long; most fish were present during crepuscular periods; trajectories of fish outside the PFFC were rarely directed toward the entrance; and many fish entering the PFFC swam back out before they could be collected.
\nThe hydraulic performance of the PFFC did not achieve the design goals of smooth acceleration of inflow culminating in a peak water velocity of 6 ft/s and, as a result, the hydraulic performance likely contributed to the low biological performance. The greatest water velocity measured in the PFFC (1.87 ft/s) was lower than designed due at least in part to the PFFC being lower in the water column than expected. Additionally, difficulties during anchor deployment prevented placement of the PFFC as near to the reservoir outlet as planned, resulting in a PFFC position outside the prevailing flow field and known areas of high fish densities. Overall, the results indicate that location, hydraulic conditions, water temperature, and shallow depth of the entrance were among the factors contributing to the low biological performance of the PFFC in 2014.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161003","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Beeman, J.W., Evans, S.D., Haner, P.V., Hansel, H.C., Hansen, A.C., Hansen, G.S., Hatton, T.W., Sprando, J.M., Smith, C.D., and Adams, N.S., 2016, Evaluation of the biological and hydraulic performance of the portable floating fish collector at Cougar Reservoir and Dam, Oregon, 2014: U.S. Geological Survey Open-File Report 2016-1003, 127 p., https://dx.doi.org/ 10.3133/ofr20161003.","productDescription":"xii, 127 p.","numberOfPages":"143","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066415","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":314044,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1003/coverthb.jpg"},{"id":314045,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1003/ofr20161003.pdf","text":"Report","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1003 PDF"}],"country":"United States","state":"Oregon","otherGeospatial":"Cougar Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.25173950195311,\n 44.06464670206631\n ],\n [\n -122.25173950195311,\n 44.132449357705454\n ],\n [\n -122.2071075439453,\n 44.132449357705454\n ],\n [\n -122.2071075439453,\n 44.06464670206631\n ],\n [\n -122.25173950195311,\n 44.06464670206631\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
Acidification has historically impaired Cheat Lake's fish community, but recent mitigation efforts within the Cheat River watershed have improved water quality and species richness. Presently, channel catfish Ictalurus punctatus are abundant and attain desirable sizes for anglers. We evaluated the age, growth, and fall diet of the population. We collected a sample of 155 channel catfish from Cheat Lake from 5 August to 4 December 2014, a subset of which we aged (n = 148) using lapillus otoliths. We fit four growth models (von Bertalanffy, logistic, Gompertz, and power) to length-at-age data and compared models using an information theoretic approach. We collected fall diets from 55 fish sampled from 13 October to 4 December 2014. Total lengths of individuals in the sample ranged from 154 to 721 mm and ages ranged from 2 to 19 y. We AICc-selected the von Bertalanffy growth model as the best approximating model, and the power and Gompertz models also had considerable support. Diets were numerically dominated by Diptera larvae, specifically Chironomidae and Chaoboridae, while 39% of stomachs contained terrestrial food items. This study provides baseline data for management of Cheat Lake's channel catfish population. Further, this study fills a knowledge gap in the scientific literature on channel catfish, because few previously published studies have examined the population ecology of channel catfish in the Central Appalachian region.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/092015-JFWM-091","usgsCitation":"Hilling, C., Welsh, S.A., and Smith, D.M., 2016, Age, growth and fall diet of channel catfish in Cheat Lake, West Virginia: Journal of Fish and Wildlife Management, v. 7, no. 2, p. 304-314, https://doi.org/10.3996/092015-JFWM-091.","productDescription":"11 p.","startPage":"304","endPage":"314","ipdsId":"IP-074154","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471372,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/092015-jfwm-091","text":"Publisher Index Page"},{"id":340456,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Cheat Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": 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data","interactions":[],"lastModifiedDate":"2017-06-29T15:25:44","indexId":"70189105","displayToPublicDate":"2015-12-31T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Regional tectonic setting for the Trinidad earthquake swarms (2000-2012) from gravity and magnetic data","docAbstract":"Earthquakes in the Raton basin near Trinidad, Colorado, (Figure 1) are located (Rubenstein et. al., 2014) near a major gravity and magnetic boundary. These earthquakes also occur in an area of hydrocarbon production that includes several high-capacity produced water injection wells. This presentation gives a very basic outline of the relation between the earthquakes, the potential field data, and possible basement structure.
Research comparing different sampling techniques helps improve the efficiency and efficacy of sampling efforts. We compared the effectiveness of three sampling techniques (small-mesh hoop nets, benthic trawls, boat-mounted electrofishing) for 30 species in the Green (WY, USA) and Kootenai (ID, USA) rivers by estimating conditional detection probabilities (probability of detecting a species given its presence at a site). Electrofishing had the highest detection probabilities (generally greater than 0.60) for most species (88%), but hoop nets also had high detectability for several taxa (e.g., adult burbot Lota lota, juvenile northern pikeminnow Ptychocheilus oregonensis). Benthic trawls had low detection probabilities (<0.05) for most taxa (84%). Gear-specific effects were present for most species indicating large differences in gear effectiveness among techniques. In addition to gear effects, habitat characteristics also influenced detectability of fishes. Most species-specific habitat relationships were idiosyncratic and reflected the ecology of the species. Overall findings of our study indicate that boat-mounted electrofishing and hoop nets are the most effective techniques for sampling fish assemblages in large, coldwater rivers.
","language":"English","publisher":"Scientific Journals","doi":"10.3996/022015-JFWM-011","usgsCitation":"Smith, C.D., Quist, M., and Hardy, R.S., 2015, Detection probabilities of electrofishing, hoop nets, and benthic trawls for fishes in two western North American rivers: Journal of Fish and Wildlife Management, v. 6, no. 2, p. 371-391, https://doi.org/10.3996/022015-JFWM-011.","productDescription":"21 p.","startPage":"371","endPage":"391","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053442","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471547,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/022015-jfwm-011","text":"Publisher Index Page"},{"id":318145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Wyoming","otherGeospatial":"Kootenai River, Green River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.08850097656249,\n 41.51474739095224\n ],\n [\n -110.08850097656249,\n 42.0227732629691\n ],\n [\n -109.37164306640625,\n 42.0227732629691\n ],\n [\n -109.37164306640625,\n 41.51474739095224\n ],\n [\n -110.08850097656249,\n 41.51474739095224\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.6033935546875,\n 48.61112192003074\n ],\n [\n -116.6033935546875,\n 49.00004203215395\n ],\n [\n -116.05133056640625,\n 49.00004203215395\n ],\n [\n -116.05133056640625,\n 48.61112192003074\n ],\n [\n -116.6033935546875,\n 48.61112192003074\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-01","publicationStatus":"PW","scienceBaseUri":"56c6f93fe4b0946c65240729","contributors":{"authors":[{"text":"Smith, Christopher D.","contributorId":167031,"corporation":false,"usgs":false,"family":"Smith","given":"Christopher","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":620817,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. mquist@usgs.gov","contributorId":166707,"corporation":false,"usgs":true,"family":"Quist","given":"Michael C.","email":"mquist@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":619789,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hardy, Ryan S.","contributorId":167032,"corporation":false,"usgs":false,"family":"Hardy","given":"Ryan","email":"","middleInitial":"S.","affiliations":[{"id":6764,"text":"Idaho Department of Fish and Game, Nampa, Idaho","active":true,"usgs":false}],"preferred":false,"id":620818,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192950,"text":"70192950 - 2015 - Developing a conservation strategy to maximize persistence of an endangered freshwater mussel species while considering management effectiveness and cost","interactions":[],"lastModifiedDate":"2017-11-29T13:52:49","indexId":"70192950","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Developing a conservation strategy to maximize persistence of an endangered freshwater mussel species while considering management effectiveness and cost","docAbstract":"We used a structured decision-making process to develop conservation strategies to increase persistence of Dwarf Wedgemussel (Alasmidonta heterodon) in North Carolina, USA, while accounting for uncertainty in management effectiveness and considering costs. Alternative conservation strategies were portfolios of management actions that differed by location of management actions on the landscape. Objectives of the conservation strategy were to maximize species persistence, maintain genetic diversity, maximize public support, and minimize management costs. We compared 4 conservation strategies: 1) the ‘status quo’ strategy represented current management, 2) the ‘protect the best’ strategy focused on protecting the best populations in the Tar River basin, 3) the ‘expand the distribution’ strategy focused on management of extant populations and establishment of new populations in the Neuse River basin, and 4) the ‘hybrid’ strategy combined elements of each strategy to balance conservation in the Tar and Neuse River basins. A population model informed requirements for population management, and experts projected performance of alternative strategies over a 20-y period. The optimal strategy depended on the relative value placed on competing objectives, which can vary among stakeholders. The protect the best and hybrid strategies were optimal across a wide range of relative values with 2 exceptions: 1) if minimizing management cost was of overriding concern, then status quo was optimal, or 2) if maximizing population persistence in the Neuse River basin was emphasized, then expand the distribution strategy was optimal. The optimal strategy was robust to uncertainty in management effectiveness. Overall, the structured decision process can help identify the most promising strategies for endangered species conservation that maximize conservation benefit given the constraint of limited funding.
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,{"id":70154881,"text":"70154881 - 2015 - Assessment and Mmanagement of North American horseshoe crab populations, with emphasis on a multispecies framework for Delaware Bay, U.S.A. populations: Chapter 24","interactions":[],"lastModifiedDate":"2016-08-17T11:33:56","indexId":"70154881","displayToPublicDate":"2015-11-19T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Assessment and Mmanagement of North American horseshoe crab populations, with emphasis on a multispecies framework for Delaware Bay, U.S.A. populations: Chapter 24","docAbstract":"The horseshoe crab fishery on the US Atlantic coast represents a compelling fishery management story for many reasons, including ecological complexity, health and human safety ramifications, and socio-economic conflicts. Knowledge of stock status and assessment and monitoring capabilities for the species have increased greatly in the last 15 years and permitted managers to make more informed harvest recommendations. Incorporating the bioenergetics needs of migratory shorebirds, which feed on horseshoe crab eggs, into the management framework for horseshoe crabs was identified as a goal, particularly in the Delaware Bay region where the birds and horseshoe crabs exhibit an important ecological interaction. In response, significant effort was invested in studying the population dynamics, migration ecology, and the ecologic relationship of a key migratory shorebird, the Red Knot, to horseshoe crabs. A suite of models was developed that linked Red Knot populations to horseshoe crab populations through a mass gain function where female spawning crab abundance determined what proportion of the migrating Red Knot population reached a critical body mass threshold. These models were incorporated in an adaptive management framework wherein optimal harvest decisions for horseshoe crab are recommended based on several resource-based and value-based variables and thresholds. The current adaptive framework represents a true multispecies management effort where additional data over time are employed to improve the predictive models and reduce parametric uncertainty. The possibility of increasing phenologic asynchrony between the two taxa in response to climate change presents a potential challenge to their ecologic interaction in Delaware Bay.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Changing Global Perspectives on Horseshoe Crab Biology, Conservation and Management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"Cham","doi":"10.1007/978-3-319-19542-1_24","usgsCitation":"Millard, M.J., Sweka, J.A., McGowan, C., and Smith, D., 2015, Assessment and Mmanagement of North American horseshoe crab populations, with emphasis on a multispecies framework for Delaware Bay, U.S.A. populations: Chapter 24, chap. of Changing Global Perspectives on Horseshoe Crab Biology, Conservation and Management, p. 407-431, https://doi.org/10.1007/978-3-319-19542-1_24.","startPage":"407","endPage":"431","numberOfPages":"25","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059817","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":326655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57b58abee4b03bcb0104bb5e","contributors":{"authors":[{"text":"Millard, Michael J.","contributorId":23411,"corporation":false,"usgs":false,"family":"Millard","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":645754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweka, John A.","contributorId":80945,"corporation":false,"usgs":true,"family":"Sweka","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":645755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGowan, Conor P. cmcgowan@usgs.gov","contributorId":145496,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":564308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, David R.","contributorId":173756,"corporation":false,"usgs":false,"family":"Smith","given":"David R.","affiliations":[],"preferred":false,"id":645756,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178511,"text":"70178511 - 2015 - Horseshoe crab spawning activity in Delaware Bay, USA, after harvest reduction: A mixed-model analysis","interactions":[],"lastModifiedDate":"2016-11-22T12:24:38","indexId":"70178511","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Horseshoe crab spawning activity in Delaware Bay, USA, after harvest reduction: A mixed-model analysis","docAbstract":"A Delaware Bay, USA, standardized survey of spawning horseshoe crabs, Limulus polyphemus, was carried out in 1999 − 2013 through a citizen science network. Previous trend analyses of the data were at the state (DE or NJ) or bay-wide levels. Here, an alternative mixed-model regression analysis was used to estimate trends in female and male spawning densities at the beach level (n = 26) with the objective of inferring their causes. For females, there was no overall trend and no single explanation applies to the temporal and spatial patterns in their densities. Individual beaches that initially had higher densities tended to experience a decrease, while beaches that initially had lower densities tended to experience an increase. As a result, densities of spawning females at the end of the study period were relatively similar among beaches, suggesting a redistribution of females among the beaches over the study period. For males, there was a positive overall trend in spawning abundance from 1999 to 2013, and this increase occurred broadly among beaches. Moreover, the beaches with below-average initial male density tended to have the greatest increases. Possible explanations for these patterns include harvest reduction, sampling artifact, habitat change, density-dependent habitat selection, or mate selection. The broad and significant increase in male spawning density, which occurred after enactment of harvest controls, is consistent with the harvest reduction explanation, but there is no single explanation for the temporal or spatial pattern in female densities. These results highlight the continued value of a citizen-science-based spawning survey in understanding horseshoe crab ecology and conservation.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-015-9961-3","usgsCitation":"Smith, D.R., and Robinson, T., 2015, Horseshoe crab spawning activity in Delaware Bay, USA, after harvest reduction: A mixed-model analysis: Estuaries and Coasts, v. 38, no. 6, p. 2345-2354, https://doi.org/10.1007/s12237-015-9961-3.","productDescription":"10 p.","startPage":"2345","endPage":"2354","ipdsId":"IP-057549","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":331187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-27","publicationStatus":"PW","scienceBaseUri":"5835672ce4b0070c0abfb6da","contributors":{"authors":[{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":654198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Timothy J.","contributorId":171636,"corporation":false,"usgs":false,"family":"Robinson","given":"Timothy J.","affiliations":[],"preferred":false,"id":654199,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70154741,"text":"fs20153049 - 2015 - USGS Arctic Science Strategy","interactions":[],"lastModifiedDate":"2017-06-30T15:03:44","indexId":"fs20153049","displayToPublicDate":"2015-07-17T03:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3049","title":"USGS Arctic Science Strategy","docAbstract":"The United States is one of eight Arctic nations responsible for the stewardship of a polar region undergoing dramatic environmental, social, and economic changes. Although warming and cooling cycles have occurred over millennia in the Arctic region, the current warming trend is unlike anything recorded previously and is affecting the region faster than any other place on Earth, bringing dramatic reductions in sea ice extent, altered weather, and thawing permafrost. Implications of these changes include rapid coastal erosion threatening villages and critical infrastructure, potentially significant effects on subsistence activities and cultural resources, changes to wildlife habitat, increased greenhouse-gas emissions from thawing permafrost, threat of invasive species, and opening of the Arctic Ocean to oil and gas exploration and increased shipping. The Arctic science portfolio of the U.S. Geological Survey (USGS) and its response to climate-related changes focuses on landscapescale ecosystem and natural resource issues and provides scientific underpinning for understanding the physical processes that shape the Arctic. The science conducted by the USGS informs the Nation's resource management policies and improves the stewardship of the Arctic Region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153049","usgsCitation":"Shasby, Mark, and Smith, Durelle, 2015, USGS Arctic science strategy, 2015–2020: U.S. Geological Survey Fact Sheet 2015-3049, 2 p., https://dx.doi.org/10.3133/fs20153049.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-065204","costCenters":[{"id":113,"text":"Alaska Regional Director's Office","active":true,"usgs":true}],"links":[{"id":305544,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3049/fs20153049.pdf","text":"Report PDF","size":"446 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3049"},{"id":305543,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3049/images/cover.jpg"},{"id":305545,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3049/","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"FS 2015-3049 HTML"}],"otherGeospatial":"Arctic Circle boundary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -217.265625,\n 67.74275906666387\n ],\n [\n -198.98437499999997,\n 65.94647177615738\n ],\n [\n -163.828125,\n 65.94647177615738\n ],\n [\n -59.765625,\n 66.23145747862573\n ],\n [\n -11.25,\n 76.67978490310692\n ],\n [\n -11.953125,\n 84.05256097843035\n ],\n [\n -340.3125,\n 82.21421714106776\n ],\n [\n -341.71875,\n 69.41124235697256\n ],\n [\n -217.265625,\n 67.74275906666387\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Regional Director for Alaska
U.S. Geological Survey
4210 University Drive, Anchorage, Alaska 99508
(907) 786-7000
http://alaska.usgs.gov
This report describes the initial year of a 2-year study to determine the feasibility of using acoustic cameras to monitor fish movements to help inform decisions about fish passage at Cougar Dam near Springfield, Oregon. Specifically, we used acoustic cameras to measure fish presence, travel speed, and direction adjacent to the water temperature control tower in the forebay of Cougar Dam during the spring (May, June, and July) and fall (September, October, and November) of 2013. Cougar Dam is a high-head flood-control dam, and the water temperature control tower enables depth-specific water withdrawals to facilitate adjustment of water temperatures released downstream of the dam. The acoustic cameras were positioned at the upstream entrance of the tower to monitor free-ranging subyearling and yearling-size juvenile Chinook salmon (Oncorhynchus tshawytscha). Because of the large size discrepancy, we could distinguish juvenile Chinook salmon from their predators, which enabled us to measure predators and prey in areas adjacent to the entrance of the tower. We used linear models to quantify and assess operational and environmental factors—such as time of day, discharge, and water temperature—that may influence juvenile Chinook salmon movements within the beam of the acoustic cameras. Although extensive milling behavior of fish near the structure may have masked directed movement of fish and added unpredictability to fish movement models, the acoustic-camera technology enabled us to ascertain the general behavior of discrete size classes of fish. Fish travel speed, direction of travel, and counts of fish moving toward the water temperature control tower primarily were influenced by the amount of water being discharged through the dam.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151124","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Adams, N.S., Smith, C.D., Plumb, J.M., Hansen, G.S., and Beeman, J.W., 2015, An evaluation of fish behavior upstream of the water temperature control tower at Cougar Dam, Oregon, using acoustic cameras, 2013: U.S. Geological Survey Open-File Report 2015-1124, 62 p., https://dx.doi.org/10.3133/ofr20151124.","productDescription":"x, 62 p.","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063666","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":305440,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1124/coverthb.jpg"},{"id":305441,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1124/ofr20151124.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Oregon","otherGeospatial":"Cougar Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.25345611572266,\n 44.122345529999656\n ],\n [\n -122.25345611572266,\n 44.132942183139654\n ],\n [\n -122.23114013671875,\n 44.132942183139654\n ],\n [\n -122.23114013671875,\n 44.122345529999656\n ],\n [\n -122.25345611572266,\n 44.122345529999656\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov
Infection risk is assumed to increase with social group size, and thus be a cost of group living. We assess infection risk and costs with respect to group size using data from an epidemic of sarcoptic mange (Sarcoptes scabiei) among grey wolves (Canis lupus). We demonstrate that group size does not predict infection risk and that individual costs of infection, in terms of reduced survival, can be entirely offset by having sufficient numbers of pack-mates. Infected individuals experience increased mortality hazards with increasing proportions of infected pack-mates, but healthy individuals remain unaffected. The social support of group hunting and territory defence are two possible mechanisms mediating infection costs. This is likely a common phenomenon among other social species and chronic infections, but difficult to detect in systems where infection status cannot be measured continuously over time.
","language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford","doi":"10.1111/ele.12444","usgsCitation":"Almberg, E., Cross, P.C., Dobson, A.P., Smith, D.W., Metz, M., Stahler, D.R., and Hudson, P., 2015, Social living mitigates the costs of a chronic illness in a cooperative carnivore: Ecology Letters, v. 18, no. 7, p. 660-667, https://doi.org/10.1111/ele.12444.","productDescription":"8 p.","startPage":"660","endPage":"667","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062430","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471957,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ele.12444","text":"Publisher Index Page"},{"id":306321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-18","publicationStatus":"PW","scienceBaseUri":"55c090b5e4b033ef521042b7","chorus":{"doi":"10.1111/ele.12444","url":"http://dx.doi.org/10.1111/ele.12444","publisher":"Wiley-Blackwell","authors":"Almberg E. S., Cross P. C., Dobson A. P., Smith D. W., Metz M. C., Stahler D. R., Hudson P. J.","journalName":"Ecology Letters","publicationDate":"5/18/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Almberg, Emily S.","contributorId":101111,"corporation":false,"usgs":true,"family":"Almberg","given":"Emily S.","affiliations":[],"preferred":false,"id":565146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":565145,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dobson, Andrew P.","contributorId":63693,"corporation":false,"usgs":true,"family":"Dobson","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":565147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Douglas W.","contributorId":95727,"corporation":false,"usgs":true,"family":"Smith","given":"Douglas","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":565148,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Metz, Matthew C","contributorId":145750,"corporation":false,"usgs":false,"family":"Metz","given":"Matthew C","affiliations":[{"id":16224,"text":"Yellowstone Wolf Project, Yellowstone National Park, WY, USA; College of Forestry and Conservation, University of Montana, Missoula, MT, USA","active":true,"usgs":false}],"preferred":false,"id":565149,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stahler, Daniel R.","contributorId":57703,"corporation":false,"usgs":true,"family":"Stahler","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":565150,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hudson, Peter J.","contributorId":85056,"corporation":false,"usgs":true,"family":"Hudson","given":"Peter J.","affiliations":[],"preferred":false,"id":565151,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70191255,"text":"70191255 - 2015 - The distribution of selected elements and minerals in soil of the conterminous United States","interactions":[],"lastModifiedDate":"2025-05-14T19:08:03.94424","indexId":"70191255","displayToPublicDate":"2015-07-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"The distribution of selected elements and minerals in soil of the conterminous United States","docAbstract":"In 2007, the U.S. Geological Survey initiated a low-density (1 site per 1600 km2, 4857 sites) geochemical and mineralogical survey of soil of the conterminous United States as part of the North American Soil Geochemical Landscapes Project. Three soil samples were collected, if possible, from each site; (1) a sample from a depth of 0 to 5 cm, (2) a composite of the soil A-horizon, and (3) a deeper sample from the soil C-horizon or, if the top of the C-horizon was at a depth greater than 100 cm, from a depth of approximately 80–100 cm. The < 2 mm fraction of each sample was analysed for a suite of 45 major and trace elements following near-total multi-acid digestion. The major mineralogical components in samples from the soil A- and C-horizons were determined by a quantitative X-ray diffraction method using Rietveld refinement. Sampling ended in 2010 and chemical and mineralogical analyses were completed in May 2013. Maps of the conterminous United States showing predicted element and mineral concentrations were interpolated from actual soil data for each soil sample type by an inverse distance weighted (IDW) technique using ArcGIS software. Regional- and national-scale map patterns for selected elements and minerals apparent in interpolated maps are described here in the context of soil-forming factors and possible human inputs. These patterns can be related to (1) soil parent materials, for example, in the distribution of quartz, (2) climate impacts, for example, in the distribution of feldspar and kaolinite, (3) soil age, for example, in the distribution of carbonate in young glacial deposits, and (4) possible anthropogenic loading of phosphorus (P) and lead (Pb) to surface soil. This new geochemical and mineralogical data set for the conterminous United States represents a major step forward from prior national-scale soil geochemistry data and provides a robust soil data framework for the United States now and into the future.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2015.01.006","usgsCitation":"Woodruff, L.G., Cannon, W.F., Smith, D.B., and Solano, F., 2015, The distribution of selected elements and minerals in soil of the conterminous United States: Journal of Geochemical Exploration, v. 154, p. 49-60, https://doi.org/10.1016/j.gexplo.2015.01.006.","productDescription":"12 p.","startPage":"49","endPage":"60","ipdsId":"IP-054587","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":346320,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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