{"pageNumber":"513","pageRowStart":"12800","pageSize":"25","recordCount":40778,"records":[{"id":70173496,"text":"70173496 - 2015 - Predictive modelling of habitat use by marine predators with respect to the abundance and depth distribution of pelagic prey","interactions":[],"lastModifiedDate":"2016-06-17T11:32:27","indexId":"70173496","displayToPublicDate":"2016-02-24T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Predictive modelling of habitat use by marine predators with respect to the abundance and depth distribution of pelagic prey","docAbstract":"
    \n
  1. Understanding the ecological processes that underpin species distribution patterns is a fundamental goal in spatial ecology. However, developing predictive models of habitat use is challenging for species that forage in marine environments, as both predators and prey are often highly mobile and difficult to monitor. Consequently, few studies have developed resource selection functions for marine predators based directly on the abundance and distribution of their prey.

    2. \n
  2. We analysed contemporaneous data on the diving locations of two seabird species, the shallow-diving Peruvian Booby (Sula variegata) and deeper diving Guanay Cormorant (Phalacrocorax bougainvilliorum), and the abundance and depth distribution of their main prey, Peruvian anchoveta (Engraulis ringens). Based on this unique data set, we developed resource selection functions to test the hypothesis that the probability of seabird diving behaviour at a given location is a function of the relative abundance of prey in the upper water column.

    3. \n
  3. For both species, we show that the probability of diving behaviour is mostly explained by the distribution of prey at shallow depths. While the probability of diving behaviour increases sharply with prey abundance at relatively low levels of abundance, support for including abundance in addition to the depth distribution of prey is weak, suggesting that prey abundance was not a major factor determining the location of diving behaviour during the study period.

    4. \n
  4. The study thus highlights the importance of the depth distribution of prey for two species of seabird with different diving capabilities. The results complement previous research that points towards the importance of oceanographic processes that enhance the accessibility of prey to seabirds. The implications are that locations where prey is predictably found at accessible depths may be more important for surface foragers, such as seabirds, than locations where prey is predictably abundant.

    5. \n
  5. Analysis of the relative importance of abundance and accessibility is essential for the design and evaluation of effective management responses to reduced prey availability for seabirds and other top predators in marine systems.
    6. \n
","language":"English","publisher":"Wiley","doi":"10.1111/1365-2656.12409","usgsCitation":"Boyd, C., Castillo, R., Hunt, G.L., Punt, A.E., VanBlaricom, G.R., Weimerskirch, H., and Bertrand, S., 2015, Predictive modelling of habitat use by marine predators with respect to the abundance and depth distribution of pelagic prey: Journal of Animal Ecology, v. 85, p. 1575-1588, https://doi.org/10.1111/1365-2656.12409.","productDescription":"14 p.","startPage":"1575","endPage":"1588","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061620","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471497,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.12409","text":"Publisher Index Page"},{"id":323879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ghana, Togo, Bénin, Nigeria, Cameroun, Gabon","otherGeospatial":"Gulf of Guinea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -7.448730468749999,\n 4.23685605976896\n ],\n [\n 8.701171874999998,\n -1.208406497271858\n ],\n [\n 8.701171874999998,\n -0.6811362994451107\n ],\n [\n 9.0087890625,\n -0.5932511181408705\n ],\n [\n 9.16259765625,\n -0.21972602392080884\n ],\n [\n 9.140625,\n 0.4614207935306211\n ],\n [\n 9.525146484375,\n 0.8184536092473124\n ],\n [\n 9.29443359375,\n 1.1644706071806183\n ],\n [\n 9.60205078125,\n 1.7355743631421197\n ],\n [\n 9.7119140625,\n 1.9991059831233327\n ],\n [\n 9.7119140625,\n 2.3504147112508305\n ],\n [\n 9.810791015625,\n 2.701635047944533\n ],\n [\n 9.7998046875,\n 3.030812122664383\n ],\n [\n 9.865722656249998,\n 3.217302058187125\n ],\n [\n 9.667968749999998,\n 3.436658158559092\n ],\n [\n 9.25048828125,\n 3.9519408561575946\n ],\n [\n 8.514404296875,\n 4.466903610394136\n ],\n [\n 8.009033203125,\n 4.488809196778652\n ],\n [\n 7.31689453125,\n 4.357365927900159\n ],\n [\n 6.6796875,\n 4.214943141390651\n ],\n [\n 5.9765625,\n 4.1711154548674365\n ],\n [\n 5.723876953125,\n 4.390228926463384\n ],\n [\n 5.4931640625,\n 4.674979814820243\n ],\n [\n 4.976806640625,\n 5.725311447610156\n ],\n [\n 4.954833984374999,\n 5.769035866122148\n ],\n [\n 4.76806640625,\n 6.031310707125822\n ],\n [\n 4.405517578125,\n 6.271618064314864\n ],\n [\n 3.9880371093749996,\n 6.32621808201486\n ],\n [\n 3.49365234375,\n 6.304378764325824\n ],\n [\n 2.92236328125,\n 6.304378764325824\n ],\n [\n 2.449951171875,\n 6.249776453227831\n ],\n [\n 1.966552734375,\n 6.217012327817175\n ],\n [\n 1.23046875,\n 6.053161295714079\n ],\n [\n 1.12060546875,\n 5.79089681287197\n ],\n [\n 0.37353515625,\n 5.714379819235291\n ],\n [\n -0.3955078125,\n 5.37539777447476\n ],\n [\n -1.1865234375,\n 5.101887070062321\n ],\n [\n -1.9335937499999998,\n 4.674979814820243\n ],\n [\n -2.65869140625,\n 4.8282597468669755\n ],\n [\n -3.40576171875,\n 5.04717073691972\n ],\n [\n -4.5263671875,\n 5.112829778499462\n ],\n [\n -5.185546875,\n 5.069057826784033\n ],\n [\n -6.2841796875,\n 4.8282597468669755\n ],\n [\n -7.448730468749999,\n 4.23685605976896\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-21","publicationStatus":"PW","scienceBaseUri":"57651f3ae4b07657d19c791c","contributors":{"authors":[{"text":"Boyd, Charlotte","contributorId":172067,"corporation":false,"usgs":false,"family":"Boyd","given":"Charlotte","email":"","affiliations":[],"preferred":false,"id":639522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Castillo, Ramiro","contributorId":172068,"corporation":false,"usgs":false,"family":"Castillo","given":"Ramiro","email":"","affiliations":[],"preferred":false,"id":639523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, George L. Jr.","contributorId":56953,"corporation":false,"usgs":true,"family":"Hunt","given":"George","suffix":"Jr.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":639524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Punt, Andre E.","contributorId":172069,"corporation":false,"usgs":false,"family":"Punt","given":"Andre","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":639525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"VanBlaricom, Glenn R. glennvb@usgs.gov","contributorId":3540,"corporation":false,"usgs":true,"family":"VanBlaricom","given":"Glenn","email":"glennvb@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":637198,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weimerskirch, Henri 0000-0002-0457-586X","orcid":"https://orcid.org/0000-0002-0457-586X","contributorId":172070,"corporation":false,"usgs":false,"family":"Weimerskirch","given":"Henri","email":"","affiliations":[],"preferred":false,"id":639526,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bertrand, Sophie","contributorId":172071,"corporation":false,"usgs":false,"family":"Bertrand","given":"Sophie","email":"","affiliations":[],"preferred":false,"id":639527,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70161471,"text":"sir20155190 - 2015 - Flood-inundation maps for the Schoharie Creek at Prattsville, New York, 2014","interactions":[],"lastModifiedDate":"2016-02-22T08:46:30","indexId":"sir20155190","displayToPublicDate":"2016-02-18T15:15:00","publicationYear":"2015","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":"2015-5190","title":"Flood-inundation maps for the Schoharie Creek at Prattsville, New York, 2014","docAbstract":"

Digital flood-inundation maps for a 2.6-mile reach of the Schoharie Creek at Prattsville, New York, were created by the U.S. Geological Survey (USGS) in cooperation with the New York State Department of Environmental Conservation. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science 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 (stages) at the USGS streamgage at Schoharie Creek at Prattsville (station number 01350000). Near-real-time stages at this streamgage may be obtained online from the USGS National Water Information System (http://waterdata.usgs.gov/) or the National Weather Service Advanced Hydrologic Prediction Service (http://water.weather.gov/ahps/), which also forecasts flood hydrographs at this site. National Weather Service-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas and depths of flood inundation.

\n

Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the stage-discharge relation (rating 82.0) at the Schoharie Creek at Prattsville streamgage (station 01350000) and high-water marks from the flood of August 28, 2011. The hydraulic model was then used to compute 17 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to greater than the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model, derived from light detection and ranging (lidar) data having a 0.61-foot vertical root-mean squared error and 6.6-foot horizontal resolution, in order to delineate the area flooded at each water level.

\n

These flood-inundation maps, along with near-real-time stage data from USGS streamgages and forecasted stage data from the National Weather Service, can provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for postflood recovery efforts.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155190","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Nystrom, E.A., 2016, Flood-inundation maps for the Schoharie Creek at Prattsville, New York, 2014: U.S. Geological Survey Scientific Investigations Report 2015–5190, 12 p., 17 sheets, https://dx.doi.org/10.3133/sir20155190.","productDescription":"Report: vii, 15 p.; 17 Sheets: 17.00 x 22.00 inches or smaller; Application Sites; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-067775","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":316401,"rank":12,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2015/5190/downloads/sir20155190_sheet10-prattsville-stage18.pdf","text":"Sheet10—stage of 18.0 feet","size":"6.11 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\"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.45520401000975,\n 42.34484284244194\n ],\n [\n -74.38894271850586,\n 42.34585783931204\n ],\n [\n -74.38568115234375,\n 42.29191344264761\n ],\n [\n -74.45228576660156,\n 42.28810385554954\n ],\n [\n -74.45520401000975,\n 42.34484284244194\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349

\n

Information requests:
(518) 285-5602
Or visit our Web site at:
http://ny.water.usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2016-02-18","noUsgsAuthors":false,"publicationDate":"2016-02-18","publicationStatus":"PW","scienceBaseUri":"56c6eb29e4b0946c6523b0ca","contributors":{"authors":[{"text":"Nystrom, Elizabeth A. 0000-0002-0886-3439 nystrom@usgs.gov","orcid":"https://orcid.org/0000-0002-0886-3439","contributorId":1072,"corporation":false,"usgs":true,"family":"Nystrom","given":"Elizabeth","email":"nystrom@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":586436,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70168348,"text":"70168348 - 2015 - State-space modeling to support management of brucellosis in the Yellowstone bison population","interactions":[],"lastModifiedDate":"2016-02-17T10:37:37","indexId":"70168348","displayToPublicDate":"2016-02-17T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"State-space modeling to support management of brucellosis in the Yellowstone bison population","docAbstract":"

The bison (Bison bison) of the Yellowstone ecosystem, USA, exemplify the difficulty of conserving large mammals that migrate across the boundaries of conservation areas. Bison are infected with brucellosis (Brucella abortus) and their seasonal movements can expose livestock to infection. Yellowstone National Park has embarked on a program of adaptive management of bison, which requires a model that assimilates data to support management decisions. We constructed a Bayesian state-space model to reveal the influence of brucellosis on the Yellowstone bison population. A frequency-dependent model of brucellosis transmission was superior to a density-dependent model in predicting out-of-sample observations of horizontal transmission probability. A mixture model including both transmission mechanisms converged on frequency dependence. Conditional on the frequency-dependent model, brucellosis median transmission rate was 1.87 yr−1. The median of the posterior distribution of the basic reproductive ratio (R0) was 1.75. Seroprevalence of adult females varied around 60% over two decades, but only 9.6 of 100 adult females were infectious. Brucellosis depressed recruitment; estimated population growth rate λ averaged 1.07 for an infected population and 1.11 for a healthy population. We used five-year forecasting to evaluate the ability of different actions to meet management goals relative to no action. Annually removing 200 seropositive female bison increased by 30-fold the probability of reducing seroprevalence below 40% and increased by a factor of 120 the probability of achieving a 50% reduction in transmission probability relative to no action. Annually vaccinating 200 seronegative animals increased the likelihood of a 50% reduction in transmission probability by fivefold over no action. However, including uncertainty in the ability to implement management by representing stochastic variation in the number of accessible bison dramatically reduced the probability of achieving goals using interventions relative to no action. Because the width of the posterior predictive distributions of future population states expands rapidly with increases in the forecast horizon, managers must accept high levels of uncertainty. These findings emphasize the necessity of iterative, adaptive management with relatively short-term commitment to action and frequent reevaluation in response to new data and model forecasts. We believe our approach has broad applications.

","language":"English","publisher":"Ecological Society of America","doi":"10.1890/14-1413.1","usgsCitation":"Hobbs, N., Geremia, C., Treanor, J., Wallen, R., White, P., Hooten, M., and Rhyan, J.C., 2015, State-space modeling to support management of brucellosis in the Yellowstone bison population: Ecological Monographs, v. 85, no. 4, p. 525-556, https://doi.org/10.1890/14-1413.1.","productDescription":"32 p.","startPage":"525","endPage":"556","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053288","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":318110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","volume":"85","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56c599ace4b0946c6521edfc","contributors":{"authors":[{"text":"Hobbs, N. Thompson","contributorId":35031,"corporation":false,"usgs":true,"family":"Hobbs","given":"N. Thompson","affiliations":[],"preferred":false,"id":620718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geremia, Chris","contributorId":167003,"corporation":false,"usgs":false,"family":"Geremia","given":"Chris","email":"","affiliations":[],"preferred":false,"id":620719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Treanor, John","contributorId":92063,"corporation":false,"usgs":true,"family":"Treanor","given":"John","affiliations":[],"preferred":false,"id":620720,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wallen, Rick","contributorId":14202,"corporation":false,"usgs":true,"family":"Wallen","given":"Rick","affiliations":[],"preferred":false,"id":620721,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, P.J.","contributorId":91436,"corporation":false,"usgs":true,"family":"White","given":"P.J.","affiliations":[],"preferred":false,"id":620722,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":619788,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rhyan, Jack C.","contributorId":11185,"corporation":false,"usgs":true,"family":"Rhyan","given":"Jack","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":620723,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70168356,"text":"70168356 - 2015 - Seasonal cues of Arctic grayling movement in a small Arctic stream: the importance of surface water connectivity","interactions":[],"lastModifiedDate":"2016-02-17T10:23:59","indexId":"70168356","displayToPublicDate":"2016-02-17T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal cues of Arctic grayling movement in a small Arctic stream: the importance of surface water connectivity","docAbstract":"

In Arctic ecosystems, freshwater fish migrate seasonally between productive shallow water habitats that freeze in winter and deep overwinter refuge in rivers and lakes. How these movements relate to seasonal hydrology is not well understood. We used passive integrated transponder tags and stream wide antennae to track 1035 Arctic grayling in Crea Creek, a seasonally flowing beaded stream on the Arctic Coastal Plain, Alaska. Migration of juvenile and adult fish into Crea Creek peaked in June immediately after ice break-up in the stream. Fish that entered the stream during periods of high flow and cold stream temperature traveled farther upstream than those entering during periods of lower flow and warmer temperature. We used generalized linear models to relate migration of adult and juvenile fish out of Crea Creek to hydrology. Most adults migrated in late June – early July, and there was best support (Akaike weight = 0.46; w i ) for a model indicating that the rate of migration increased with decreasing discharge. Juvenile migration occurred in two peaks; the early peak consisted of larger juveniles and coincided with adult migration, while the later peak occurred shortly before freeze-up in September and included smaller juveniles. A model that included discharge, minimum stream temperature, year, season, and mean size of potential migrants was most strongly supported (w i  = 0.86). Juvenile migration rate increased sharply as daily minimum stream temperature decreased, suggesting fish respond to impending freeze-up. We found fish movements to be intimately tied to the strong seasonality of discharge and temperature, and demonstrate the importance of small stream connectivity for migratory Arctic grayling during the entire open-water period. The ongoing and anticipated effects of climate change and petroleum development on Arctic hydrology (e.g. reduced stream connectivity, earlier peak flows, increased evapotranspiration) have important implications for Arctic freshwater ecosystems.

","language":"English","publisher":"Springer","doi":"10.1007/s10641-015-0453-x","usgsCitation":"Heim, K.C., Wipfli, M.S., Whitman, M.S., Arp, C.D., Adams, J., and Falke, J.A., 2015, Seasonal cues of Arctic grayling movement in a small Arctic stream: the importance of surface water connectivity: Environmental Biology of Fishes, v. 99, no. 1, p. 49-65, https://doi.org/10.1007/s10641-015-0453-x.","productDescription":"17 p.","startPage":"49","endPage":"65","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060031","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":318109,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"99","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-26","publicationStatus":"PW","scienceBaseUri":"56c599ace4b0946c6521edf6","contributors":{"authors":[{"text":"Heim, Kurt C.","contributorId":138832,"corporation":false,"usgs":false,"family":"Heim","given":"Kurt","email":"","middleInitial":"C.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":620695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":619796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whitman, Matthew S.","contributorId":67961,"corporation":false,"usgs":false,"family":"Whitman","given":"Matthew","email":"","middleInitial":"S.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":620696,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":620697,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Jeff","contributorId":167002,"corporation":false,"usgs":false,"family":"Adams","given":"Jeff","email":"","affiliations":[],"preferred":false,"id":620698,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":620699,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70168357,"text":"70168357 - 2015 - Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests","interactions":[],"lastModifiedDate":"2016-02-16T10:53:43","indexId":"70168357","displayToPublicDate":"2016-02-16T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests","docAbstract":"

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr−1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil RHwith both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

","language":"English","publisher":"AGU Publications","doi":"10.1002/2015JG003130","usgsCitation":"He, Y., Yang, J., Zhuang, Q., Harden, J.W., McGuire, A.D., Liu, Y., Wang, G., and Gu, L., 2015, Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests: Journal of Geophysical Research G: Biogeosciences, v. 120, no. 12, p. 2596-2611, https://doi.org/10.1002/2015JG003130.","productDescription":"16 p.","startPage":"2596","endPage":"2611","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062475","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471499,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jg003130","text":"Publisher Index Page"},{"id":318062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-22","publicationStatus":"PW","scienceBaseUri":"56c4482be4b0946c652116e7","contributors":{"authors":[{"text":"He, Yujie","contributorId":32444,"corporation":false,"usgs":true,"family":"He","given":"Yujie","affiliations":[],"preferred":false,"id":620368,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Jinyan","contributorId":166929,"corporation":false,"usgs":false,"family":"Yang","given":"Jinyan","email":"","affiliations":[],"preferred":false,"id":620369,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhuang, Qianlai","contributorId":101975,"corporation":false,"usgs":true,"family":"Zhuang","given":"Qianlai","affiliations":[],"preferred":false,"id":620370,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":620371,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":619797,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liu, Yaling","contributorId":166930,"corporation":false,"usgs":false,"family":"Liu","given":"Yaling","email":"","affiliations":[],"preferred":false,"id":620372,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Gangsheng","contributorId":166931,"corporation":false,"usgs":false,"family":"Wang","given":"Gangsheng","email":"","affiliations":[],"preferred":false,"id":620373,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gu, Lianhong 0000-0001-5756-8738","orcid":"https://orcid.org/0000-0001-5756-8738","contributorId":166932,"corporation":false,"usgs":false,"family":"Gu","given":"Lianhong","email":"","affiliations":[],"preferred":false,"id":620374,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70168365,"text":"70168365 - 2015 - Population trends and survival of nesting green sea turtles Chelonia mydas on Aves Island, Venezuela","interactions":[],"lastModifiedDate":"2022-11-02T15:06:23.594321","indexId":"70168365","displayToPublicDate":"2016-02-16T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Population trends and survival of nesting green sea turtles Chelonia mydas on Aves Island, Venezuela","title":"Population trends and survival of nesting green sea turtles Chelonia mydas on Aves Island, Venezuela","docAbstract":"

Long-term demographic data are valuable for assessing the effect of anthropogenic impacts on endangered species and evaluating recovery programs. Using a 2-state open robust design model, we analyzed mark-recapture data from green turtles Chelonia mydas sighted between 1979 and 2009 on Aves Island, Venezuela, a rookery heavily impacted by human activities before it was declared a wildlife refuge in 1972. Based on the encounter histories of 7689 nesting females, we estimated the abundance, annual survival, and remigration intervals for this population. Female survival varied from 0.14-0.91, with a mean of 0.79, which is low compared to survival of other populations from the Caribbean (mean = 0.84) and Australia (mean = 0.95), even though we partially corrected for tag loss, which is known to negatively bias survival estimates. This supports prior suggestions that Caribbean populations in general, and the Aves Island population in particular, may be more strongly impacted than populations elsewhere. It is likely that nesters from this rookery are extracted while foraging in remote feeding grounds where hunting still occurs. Despite its relatively low survival, the nesting population at Aves Island increased during the past 30 years from approx. 500 to >1000 nesting females in 2009. Thus, this population, like others in the Caribbean and the Atlantic, seems to be slowly recovering following protective management. Although these findings support the importance of long-term conservation programs aimed at protecting nesting grounds, they also highlight the need to extend management actions to foraging grounds where human activities may still impact green turtle populations.

","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr00695","usgsCitation":"Garcia-Cruz, M.A., Lampo, M., Penaloza, C.L., Kendall, W., Sole, G., and Rodriguez-Clark, K.M., 2015, Population trends and survival of nesting green sea turtles Chelonia mydas on Aves Island, Venezuela: Endangered Species Research, v. 29, no. 2, p. 103-116, https://doi.org/10.3354/esr00695.","productDescription":"14 p.","startPage":"103","endPage":"116","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061027","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471500,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00695","text":"Publisher Index Page"},{"id":318059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Venezuela","otherGeospatial":"Aves Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -63.38424114450454,\n 15.41986000335801\n ],\n [\n -63.38424114450454,\n 15.383063099888886\n ],\n [\n -63.33335107339563,\n 15.383063099888886\n ],\n [\n -63.33335107339563,\n 15.41986000335801\n ],\n [\n -63.38424114450454,\n 15.41986000335801\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56c44831e4b0946c6521170b","contributors":{"authors":[{"text":"Garcia-Cruz, Marco A.","contributorId":166909,"corporation":false,"usgs":false,"family":"Garcia-Cruz","given":"Marco","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":620325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lampo, Margarita","contributorId":166910,"corporation":false,"usgs":false,"family":"Lampo","given":"Margarita","email":"","affiliations":[],"preferred":false,"id":620326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Penaloza, Claudia L.","contributorId":166911,"corporation":false,"usgs":false,"family":"Penaloza","given":"Claudia","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":620327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kendall, William L. 0000-0003-0084-9891 wkendall@usgs.gov","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":166709,"corporation":false,"usgs":true,"family":"Kendall","given":"William L.","email":"wkendall@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":619805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sole, Genaro","contributorId":166912,"corporation":false,"usgs":false,"family":"Sole","given":"Genaro","email":"","affiliations":[],"preferred":false,"id":620328,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rodriguez-Clark, Kathryn M.","contributorId":166913,"corporation":false,"usgs":false,"family":"Rodriguez-Clark","given":"Kathryn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":620329,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70168369,"text":"70168369 - 2015 - Depth of artificial Burrowing Owl burrows affects thermal suitability and occupancy","interactions":[],"lastModifiedDate":"2016-02-16T09:09:59","indexId":"70168369","displayToPublicDate":"2016-02-16T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Depth of artificial Burrowing Owl burrows affects thermal suitability and occupancy","docAbstract":"

Many organizations have installed artificial burrows to help bolster local Burrowing Owl (Athene cunicularia) populations. However, occupancy probability and reproductive success in artificial burrows varies within and among burrow installations. We evaluated the possibility that depth below ground might explain differences in occupancy probability and reproductive success by affecting the temperature of artificial burrows. We measured burrow temperatures from March to July 2010 in 27 artificial burrows in southern California that were buried 15–76 cm below the surface (measured between the surface and the top of the burrow chamber). Burrow depth was one of several characteristics that affected burrow temperature. Burrow temperature decreased by 0.03°C per cm of soil on top of the burrow. The percentage of time that artificial burrows provided a thermal refuge from above-ground temperature decreased with burrow depth and ranged between 50% and 58% among burrows. The percentage of time that burrow temperature was optimal for incubating females also decreased with burrow depth and ranged between 27% and 100% among burrows. However, the percentage of time that burrow temperature was optimal for unattended eggs increased with burrow depth and ranged between 11% and 95% among burrows. We found no effect of burrow depth on reproductive success across 21 nesting attempts. However, occupancy probability had a non-linear relationship with burrow depth. The shallowest burrows (15 cm) had a moderate probability of being occupied (0.46), burrows between 28 and 40 cm had the highest probability of being occupied (>0.80), and burrows >53 cm had the lowest probability of being occupied (<0.43). Burrowing Owls may prefer burrows at moderate depths because these burrows provide a thermal refuge from above-ground temperatures, and are often cool enough to allow females to leave eggs unattended before the onset of full-time incubation, but not too cool for incubating females that spend most of their time in the burrow during incubation. Our results suggest that depth is an important consideration when installing artificial burrows for Burrowing Owls. However, additional study is needed to determine the possible effects of burrow depth on reproductive success and on possible tradeoffs between the effects of burrow depth on optimal temperature and other factors, such as minimizing the risk of nest predation.

","language":"English","publisher":"Wiley","doi":"10.1111/jofo.12119","usgsCitation":"Nadeau, C.P., Conway, C.J., and Rathbun, N., 2015, Depth of artificial Burrowing Owl burrows affects thermal suitability and occupancy: Journal of Field Ornithology, v. 86, no. 4, p. 288-297, https://doi.org/10.1111/jofo.12119.","productDescription":"10 p.","startPage":"288","endPage":"297","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066728","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":318037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-30","publicationStatus":"PW","scienceBaseUri":"56c4482ae4b0946c652116d0","contributors":{"authors":[{"text":"Nadeau, Christopher P.","contributorId":105956,"corporation":false,"usgs":true,"family":"Nadeau","given":"Christopher","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":620303,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":619811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rathbun, Nathan","contributorId":166899,"corporation":false,"usgs":false,"family":"Rathbun","given":"Nathan","email":"","affiliations":[],"preferred":false,"id":620304,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173494,"text":"70173494 - 2015 - Distribution, abundance, and habitat associations of a large bivalve (Panopea generosa) in a eutrophic, fjord estuary","interactions":[],"lastModifiedDate":"2016-06-17T12:01:14","indexId":"70173494","displayToPublicDate":"2016-02-15T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2455,"text":"Journal of Shellfish Research","active":true,"publicationSubtype":{"id":10}},"title":"Distribution, abundance, and habitat associations of a large bivalve (Panopea generosa) in a eutrophic, fjord estuary","docAbstract":"

Marine bivalves are important ecosystem constituents and frequently support valuable fisheries. In many nearshore areas, human disturbance—including declining habitat and water quality—can affect the distribution and abundance of bivalve populations, and complicate ecosystem and fishery management assessments. Infaunal bivalves, in particular, are frequently cryptic and difficult to detect; thus, assessing potential impacts on their populations requires suitable, scalable methods for estimating abundance and distribution. In this study, population size of a common benthic bivalve (the geoduck Panopea generosa) is estimated with a Bayesian habitat-based model fit to scuba and tethered camera data in Hood Canal, a fjord basin in Washington state. Densities declined more than two orders of magnitude along a north—south gradient, concomitant with patterns of deepwater dissolved oxygen, and intensity and duration of seasonal hypoxia. Across the basin, geoducks were most abundant in loose, unconsolidated, sand substrate. The current study demonstrates the utility of using scuba, tethered video, and habitat models to estimate the abundance and distribution of a large infaunal bivalve at a regional (385-km2) scale.

","language":"English","publisher":"National Shellfisheries Association","doi":"10.2983/035.034.0117","usgsCitation":"Mcdonald, P.S., Essington, T.E., Davis, J.P., Galloway, A.W., Stevick, B.C., Jensen, G.C., VanBlaricom, G.R., and Armstrong, D., 2015, Distribution, abundance, and habitat associations of a large bivalve (Panopea generosa) in a eutrophic, fjord estuary: Journal of Shellfish Research, v. 34, no. 1, p. 137-145, https://doi.org/10.2983/035.034.0117.","productDescription":"8 p.","startPage":"137","endPage":"145","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063458","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Hood Canal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.84362792968749,\n 47.44480754169439\n ],\n [\n -122.838134765625,\n 47.428087261714275\n ],\n [\n -122.93426513671875,\n 47.37696459572701\n ],\n [\n -123.02627563476562,\n 47.349989032003215\n ],\n [\n -123.07159423828125,\n 47.344406158662096\n ],\n [\n -123.101806640625,\n 47.352780247239586\n ],\n [\n -123.10867309570311,\n 47.333238640473475\n ],\n [\n -123.14163208007811,\n 47.336961408985005\n ],\n [\n -123.167724609375,\n 47.352780247239586\n ],\n [\n -123.15948486328126,\n 47.38998234483188\n ],\n [\n -123.12240600585938,\n 47.4596655525415\n ],\n [\n -123.06335449218749,\n 47.53111102290634\n ],\n [\n -123.00155639648436,\n 47.61264397257417\n ],\n [\n -122.96585083007812,\n 47.640410285382224\n ],\n [\n -122.93014526367188,\n 47.65891296651944\n ],\n [\n -122.89993286132812,\n 47.706065135695745\n ],\n [\n -122.88894653320311,\n 47.743017409121826\n ],\n [\n -122.87933349609376,\n 47.81684332352077\n ],\n [\n -122.87109375,\n 47.82975208084834\n ],\n [\n -122.81204223632811,\n 47.86293128876346\n ],\n [\n -122.78045654296874,\n 47.83528342275264\n ],\n [\n -122.7777099609375,\n 47.81684332352077\n ],\n [\n -122.80929565429688,\n 47.70514099299205\n ],\n [\n -122.78320312499999,\n 47.68850362252604\n ],\n [\n -122.7777099609375,\n 47.75502125407674\n ],\n [\n -122.75161743164061,\n 47.79470655664555\n ],\n [\n -122.73239135742188,\n 47.82237604116143\n ],\n [\n -122.69119262695311,\n 47.850952356425296\n ],\n [\n -122.68981933593749,\n 47.869380336792005\n ],\n [\n -122.60879516601561,\n 47.8527954492302\n ],\n [\n -122.67608642578126,\n 47.79562911029222\n ],\n [\n -122.71728515624999,\n 47.74486433470359\n ],\n [\n -122.73788452148436,\n 47.71715357016648\n ],\n [\n -122.74200439453125,\n 47.68203210030427\n ],\n [\n -122.75161743164061,\n 47.66168780332917\n ],\n [\n -122.84225463867186,\n 47.635783590864854\n ],\n [\n -122.838134765625,\n 47.65058757118734\n ],\n [\n -122.85873413085936,\n 47.64318610543658\n ],\n [\n -122.91366577148438,\n 47.613569753973955\n ],\n [\n -122.93701171874999,\n 47.581157652951454\n ],\n [\n -122.95486450195311,\n 47.57930492644292\n ],\n [\n -122.96585083007812,\n 47.57467282332527\n ],\n [\n -122.991943359375,\n 47.53945544742392\n ],\n [\n -123.02490234375,\n 47.49864785970502\n ],\n [\n -123.06060791015624,\n 47.45037978769006\n ],\n [\n -123.10455322265625,\n 47.40299687942135\n ],\n [\n -123.09494018554686,\n 47.38440370312246\n ],\n [\n -123.04412841796875,\n 47.37603463349758\n ],\n [\n -123.00292968749999,\n 47.386263315961884\n ],\n [\n -122.97134399414061,\n 47.409502941311075\n ],\n [\n -122.85873413085936,\n 47.44294999517949\n ],\n [\n -122.84362792968749,\n 47.44480754169439\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57651f32e4b07657d19c788d","contributors":{"authors":[{"text":"Mcdonald, P. Sean","contributorId":171699,"corporation":false,"usgs":false,"family":"Mcdonald","given":"P.","email":"","middleInitial":"Sean","affiliations":[],"preferred":false,"id":639537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Essington, Timothy E.","contributorId":95826,"corporation":false,"usgs":false,"family":"Essington","given":"Timothy","email":"","middleInitial":"E.","affiliations":[{"id":13190,"text":"School of Aquatic and Fishery Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":639538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Jonathan P.","contributorId":172078,"corporation":false,"usgs":false,"family":"Davis","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":639539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galloway, Aaron W.E.","contributorId":172072,"corporation":false,"usgs":false,"family":"Galloway","given":"Aaron","email":"","middleInitial":"W.E.","affiliations":[],"preferred":false,"id":639540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stevick, Bethany C.","contributorId":172079,"corporation":false,"usgs":false,"family":"Stevick","given":"Bethany","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":639541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jensen, Gregory C.","contributorId":172080,"corporation":false,"usgs":false,"family":"Jensen","given":"Gregory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":639542,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"VanBlaricom, Glenn R. glennvb@usgs.gov","contributorId":3540,"corporation":false,"usgs":true,"family":"VanBlaricom","given":"Glenn","email":"glennvb@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":637196,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Armstrong, David A.","contributorId":172081,"corporation":false,"usgs":false,"family":"Armstrong","given":"David A.","affiliations":[],"preferred":false,"id":639543,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70168432,"text":"70168432 - 2015 - Large divergence of satellite and Earth system model estimates of global terrestrial CO2 fertilization","interactions":[],"lastModifiedDate":"2016-03-03T11:20:50","indexId":"70168432","displayToPublicDate":"2016-02-12T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Large divergence of satellite and Earth system model estimates of global terrestrial CO2 fertilization","docAbstract":"

Atmospheric mass balance analyses suggest that terrestrial carbon (C) storage is increasing, partially abating the atmospheric [CO2] growth rate, although the continued strength of this important ecosystem service remains uncertain. Some evidence suggests that these increases will persist owing to positive responses of vegetation growth (net primary productivity; NPP) to rising atmospheric [CO2] (that is, ‘CO2 fertilization’). Here, we present a new satellite-derived global terrestrial NPP data set, which shows a significant increase in NPP from 1982 to 2011. However, comparison against Earth system model (ESM) NPP estimates reveals a significant divergence, with satellite-derived increases (2.8 ± 1.50%) less than half of ESM-derived increases (7.6  ±  1.67%) over the 30-year period. By isolating the CO2 fertilization effect in each NPP time series and comparing it against a synthesis of available free-air CO2 enrichment data, we provide evidence that much of the discrepancy may be due to an over-sensitivity of ESMs to atmospheric [CO2], potentially reflecting an under-representation of climatic feedbacks and/or a lack of representation of nutrient constraints. Our understanding of CO2 fertilization effects on NPP needs rapid improvement to enable more accurate projections of future C cycle–climate feedbacks; we contend that better integration of modelling, satellite and experimental approaches offers a promising way forward.

","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/nclimate2879","usgsCitation":"Smith, W.K., Reed, S.C., Cleveland, C.C., Ballantyne, A.P., Anderegg, W.R., Wieder, W.R., Liu, Y.Y., and Running, S.W., 2015, Large divergence of satellite and Earth system model estimates of global terrestrial CO2 fertilization: Nature Climate Change, v. 6, p. 306-310, https://doi.org/10.1038/nclimate2879.","productDescription":"5 p.","startPage":"306","endPage":"310","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066726","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":318001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-07","publicationStatus":"PW","scienceBaseUri":"56bf022be4b06458514b30f6","contributors":{"authors":[{"text":"Smith, W. Kolby","contributorId":166783,"corporation":false,"usgs":false,"family":"Smith","given":"W.","email":"","middleInitial":"Kolby","affiliations":[{"id":24513,"text":"Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":620083,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":620082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cleveland, Cory C.","contributorId":10264,"corporation":false,"usgs":true,"family":"Cleveland","given":"Cory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":620084,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ballantyne, Ashley P","contributorId":166784,"corporation":false,"usgs":false,"family":"Ballantyne","given":"Ashley","email":"","middleInitial":"P","affiliations":[{"id":24513,"text":"Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":620085,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderegg, William R. L.","contributorId":166785,"corporation":false,"usgs":false,"family":"Anderegg","given":"William","email":"","middleInitial":"R. L.","affiliations":[{"id":24514,"text":"Department of Ecology and Evolutionary Biology, Princeton University, Princeton NJ 08544","active":true,"usgs":false}],"preferred":false,"id":620086,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wieder, William R.","contributorId":75792,"corporation":false,"usgs":true,"family":"Wieder","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":620087,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liu, Yi Y","contributorId":166786,"corporation":false,"usgs":false,"family":"Liu","given":"Yi","email":"","middleInitial":"Y","affiliations":[{"id":24515,"text":"ARC Centre of Excellence for Climate Systems Science & Climate Change Research Centre, University of New South Wales, Sydney, Australia","active":true,"usgs":false}],"preferred":false,"id":620089,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Running, Steven W. 0000-0001-6906-3841","orcid":"https://orcid.org/0000-0001-6906-3841","contributorId":53258,"corporation":false,"usgs":false,"family":"Running","given":"Steven","email":"","middleInitial":"W.","affiliations":[{"id":7089,"text":"University of Montana, Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":620088,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70168370,"text":"70168370 - 2015 - Influence of habitat and intrinsic characteristics on survival of neonatal pronghorn","interactions":[],"lastModifiedDate":"2016-02-15T12:37:52","indexId":"70168370","displayToPublicDate":"2016-02-10T16:00:00","publicationYear":"2015","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":"Influence of habitat and intrinsic characteristics on survival of neonatal pronghorn","docAbstract":"

Increased understanding of the influence of habitat (e.g., composition, patch size) and intrinsic (e.g., age, birth mass) factors on survival of neonatal pronghorn (Antilocapra americana) is a prerequisite to successful management programs, particularly as they relate to population dynamics and the role of population models in adaptive species management. Nevertheless, few studies have presented empirical data quantifying the influence of habitat variables on survival of neonatal pronghorn. During 2002–2005, we captured and radiocollared 116 neonates across two sites in western South Dakota. We documented 31 deaths during our study, of which coyote (Canis latrans) predation (n = 15) was the leading cause of mortality. We used known fate analysis in Program MARK to investigate the influence of intrinsic and habitat variables on neonatal survival. We generated a priori models that we grouped into habitat and intrinsic effects. The highest-ranking model indicated that neonate mortality was best explained by site, percent grassland, and open water habitat; 90-day survival (0.80; 90% CI = 0.71–0.88) declined 23% when grassland and water increased from 80.1 to 92.3% and 0.36 to 0.40%, respectively, across 50% natal home ranges. Further, our results indicated that grassland patch size and shrub density were important predictors of neonate survival; neonate survival declined 17% when shrub density declined from 5.0 to 2.5 patches per 100 ha. Excluding the site covariates, intrinsic factors (i.e., sex, age, birth mass, year, parturition date) were not important predictors of survival of neonatal pronghorns. Further, neonatal survival may depend on available land cover and interspersion of habitats. We have demonstrated that maintaining minimum and maximum thresholds for habitat factors (e.g., percentages of grassland and open water patches, density of shrub patches) throughout natal home ranges will in turn, ensure relatively high (>0.50) neonatal survival rates, especially as they relate to coyote predation. Thus, landscape level variables (particularly percentages of open water, grassland habitats, and shrub density) should be incorporated into the development or implementation of pronghorn management plans across sagebrush steppe communities of the western Dakotas, and potentially elsewhere within the geographic range of pronghorn.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0144026","usgsCitation":"Jacques, C.N., Jenks, J., Grovenburg, T.W., and Klaver, R.W., 2015, Influence of habitat and intrinsic characteristics on survival of neonatal pronghorn: PLoS ONE, v. 10, no. 12, e0144026; 17 p., https://doi.org/10.1371/journal.pone.0144026.","productDescription":"e0144026; 17 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067993","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471501,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0144026","text":"Publisher Index Page"},{"id":317924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","county":"Fall River County, Harding County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.029541015625,\n 45.205263456162385\n ],\n [\n -104.029541015625,\n 45.94351068030587\n ],\n [\n -102.89794921875,\n 45.94351068030587\n ],\n [\n -102.89794921875,\n 45.205263456162385\n ],\n [\n -104.029541015625,\n 45.205263456162385\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.04052734375,\n 43.00866413845207\n ],\n [\n -104.04052734375,\n 43.49676775343911\n ],\n [\n -102.9473876953125,\n 43.49676775343911\n ],\n [\n -102.9473876953125,\n 43.00866413845207\n ],\n [\n -104.04052734375,\n 43.00866413845207\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-02","publicationStatus":"PW","scienceBaseUri":"56bc5f34e4b08d617f66001d","contributors":{"authors":[{"text":"Jacques, Christopher N.","contributorId":15521,"corporation":false,"usgs":true,"family":"Jacques","given":"Christopher","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":619813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenks, Jonathan A.","contributorId":51591,"corporation":false,"usgs":true,"family":"Jenks","given":"Jonathan A.","affiliations":[],"preferred":false,"id":619814,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grovenburg, Troy W.","contributorId":57712,"corporation":false,"usgs":true,"family":"Grovenburg","given":"Troy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":619815,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":619812,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168336,"text":"70168336 - 2015 - Bioelectrical impedance analysis: A new tool for assessing fish condition","interactions":[],"lastModifiedDate":"2018-02-28T14:37:39","indexId":"70168336","displayToPublicDate":"2016-02-10T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Bioelectrical impedance analysis: A new tool for assessing fish condition","docAbstract":"

Bioelectrical impedance analysis (BIA) is commonly used in human health and nutrition fields but has only recently been considered as a potential tool for assessing fish condition. Once BIA is calibrated, it estimates fat/moisture levels and energy content without the need to kill fish. Despite the promise held by BIA, published studies have been divided on whether BIA can provide accurate estimates of body composition in fish. In cases where BIA was not successful, the models lacked the range of fat levels or sample sizes we determined were needed for model success (range of dry fat levels of 29%, n = 60, yielding an R2 of 0.8). Reduced range of fat levels requires an increased sample size to achieve that benchmark; therefore, standardization of methods is needed. Here we discuss standardized methods based on a decade of research, identify sources of error, discuss where BIA is headed, and suggest areas for future research.

","language":"English","publisher":"Taylor & Francis","doi":"10.1080/03632415.2015.1106943","usgsCitation":"Hartman, K.J., Margraf, F.J., Hafs, A.W., and Cox, M.K., 2015, Bioelectrical impedance analysis: A new tool for assessing fish condition: Fisheries, v. 40, no. 12, p. 590-600, https://doi.org/10.1080/03632415.2015.1106943.","productDescription":"11 p.","startPage":"590","endPage":"600","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056040","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":317899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-11","publicationStatus":"PW","scienceBaseUri":"56bc5f2ee4b08d617f65fff0","contributors":{"authors":[{"text":"Hartman, Kyle J.","contributorId":6414,"corporation":false,"usgs":false,"family":"Hartman","given":"Kyle","email":"","middleInitial":"J.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":619722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Margraf, F. Joseph jmargraf@usgs.gov","contributorId":257,"corporation":false,"usgs":true,"family":"Margraf","given":"F.","email":"jmargraf@usgs.gov","middleInitial":"Joseph","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":619708,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hafs, Andrew W.","contributorId":57308,"corporation":false,"usgs":true,"family":"Hafs","given":"Andrew","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":619723,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cox, M. Keith","contributorId":166685,"corporation":false,"usgs":false,"family":"Cox","given":"M.","email":"","middleInitial":"Keith","affiliations":[],"preferred":false,"id":619724,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160003,"text":"sir20155177 - 2015 - Transport and deposition of asbestos-rich sediment in the Sumas River, Whatcom County, Washington","interactions":[],"lastModifiedDate":"2016-06-23T15:03:46","indexId":"sir20155177","displayToPublicDate":"2016-02-08T01:15:00","publicationYear":"2015","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":"2015-5177","title":"Transport and deposition of asbestos-rich sediment in the Sumas River, Whatcom County, Washington","docAbstract":"

Heavy sediment loads in the Sumas River of Whatcom County, Washington, increase seasonal turbidity and cause locally acute sedimentation. Most sediment in the Sumas River is derived from a deep-seated landslide of serpentinite that is located on Sumas Mountain and drained by Swift Creek, a tributary to the Sumas River. This mafic sediment contains high amounts of naturally occurring asbestiform chrysotile. A known human-health hazard, asbestiform chrysotile comprises 0.25–37 percent, by mass, of the total suspended sediment sampled from the Sumas River as part of this study, which included part of water year 2011 and all of water years 2012 and 2013. The suspended-sediment load in the Sumas River at South Pass Road, 0.6 kilometers (km) downstream of the confluence with Swift Creek, was 22,000 tonnes (t) in water year 2012 and 49,000 t in water year 2013. The suspended‑sediment load at Telegraph Road, 18.8 km downstream of the Swift Creek confluence, was 22,000 t in water year 2012 and 27,000 t in water year 2013. Although hydrologic conditions during the study were wetter than normal overall, the 2-year flood peak was only modestly exceeded in water years 2011 and 2013; runoff‑driven geomorphic disturbance to the watershed, which might have involved mass wasting from the landslide, seemed unexceptional. In water year 2012, flood peaks were modest, and the annual streamflow was normal. The fact that suspended-sediment loads in water year 2012 were equivalent at sites 0.6 and 18.8 km downstream of the sediment source indicates that the conservation of suspended‑sediment load can occur under normal hydrologic conditions. The substantial decrease in suspended-sediment load in the downstream direction in water year 2013 was attributed to either sedimentation in the intervening river reach, transfer to bedload as an alternate mode of sediment transport, or both.

The sediment in the Sumas River is distinct from sediment in most other river systems because of the large percentage of asbestiform chrysotile in suspension. The suspended sediment carried by the Sumas River consists of three major components: (1) a relatively dense, largely non-flocculated material that settles rapidly out of suspension; (2) a lighter component containing relatively high proportions of flocculated material, much of it composed of asbestiform chrysotile; and (3) individual chrysotile fibers that are too small to flocculate or settle out, and remain in suspension as wash load (these fibers are on the order of microns in length and tenths of microns in diameter). Whereas the bulk density of the first (heaviest) component of suspended sediment was between 1.5 and 1.6 grams per cubic centimeter (g/cm3), the bulk density of the flocculated material was an order of magnitude lower (0.16 g/cm3), even after 24 hours of settling. Soon after immersion in water, the fresh chrysotile fibers derived from the Swift Creek landslide seem to flocculate readily into large bundles, or floccules, that exhibit settling velocities characteristic of coarse silts and fine sands (30 and 250 micrometers). In quiescent water within this river system, the floccules settle out quickly, but still leave between 2.4 and 19.5 million chrysotile fibers per liter in the clear overlying water. Consistent with the results from previous laboratory research, the amounts of asbestiform chrysotile in the water column in Swift Creek, as well as in the Sumas River close to and downstream of its confluence with Swift Creek, were determined to be directly correlated with pH. This observation offers a possible alternative to either turbidity or suspended‑sediment concentration as a surrogate for the concentration of fresh asbestiform chrysotile in suspension.

Continued movement and associated erosion of the landslide through mass wasting and runoff will maintain large sediment loads in Swift Creek and in the Sumas River for the foreseeable future. Given the present channel morphology of the river system, aggradation (that is, sediment accumulation) in Swift Creek and the Sumas River are also likely to continue.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155177","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Curran, C.A., Anderson, S.W., Barbash, J.E., Magirl, C.S., Cox, S.E., Norton, K.K., Gendaszek, A.S., Spanjer, A.R., and Foreman, J.R., 2016, Transport and deposition of asbestos-rich sediment in the Sumas River, Whatcom County, Washington: U.S. Geological Survey Scientific Investigations Report 2015–5177, 51 p., https://dx.doi.org/10.3133/sir20155177.","productDescription":"Report: viii, 51 p.; Appendixes A-H","startPage":"1","endPage":"51","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066836","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":316682,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5177/sir20155177.pdf","text":"Report","size":"3.1 MB","description":"SIR 2015-5177 PDF"},{"id":316683,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5177/sir20155177_appendixa.xlsx","text":"Appendix A","size":"25 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix A"},{"id":316684,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5177/sir20155177_appendixb.xlsx","text":"Appendix B","size":"51 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix B"},{"id":316685,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5177/sir20155177_appendixc.xlsx","text":"Appendix C","size":"6.5 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix C"},{"id":316686,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5177/sir20155177_appendixd.xlsx","text":"Appendix D","size":"15 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix D"},{"id":316687,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5177/sir20155177_appendixe.xlsx","text":"Appendix E","size":"13 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix E"},{"id":316688,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5177/sir20155177_appendixf.xlsx","text":"Appendix F","size":"234 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix F"},{"id":316689,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5177/sir20155177_appendixg.xlsx","text":"Appendix G","size":"29 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix G"},{"id":316690,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5177/sir20155177_appendixh.xlsx","text":"Appendix H","size":"20 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix H"},{"id":316511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5177/coverthb.jpg"}],"country":"United States","state":"Washington","county":"Whatcom County","otherGeospatial":"Sumas River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.35267639160156,\n 49.00139345263396\n ],\n [\n -122.36160278320311,\n 48.99733908118444\n ],\n [\n -122.37876892089842,\n 48.98562459864604\n ],\n [\n -122.37670898437499,\n 48.97751295870069\n ],\n [\n -122.3650360107422,\n 48.972555195463336\n ],\n [\n -122.36709594726562,\n 48.94820993324199\n ],\n [\n -122.35748291015625,\n 48.91347483782297\n ],\n [\n -122.33070373535155,\n 48.90354608612109\n ],\n [\n -122.32315063476562,\n 48.87826399706969\n ],\n [\n -122.310791015625,\n 48.86381134898791\n ],\n [\n -122.28675842285158,\n 48.84212454876025\n ],\n [\n -122.25997924804688,\n 48.83941303819501\n ],\n [\n -122.20985412597656,\n 48.871038194878636\n ],\n [\n -122.18788146972655,\n 48.907608086640366\n ],\n [\n -122.17758178710939,\n 48.950013693526294\n ],\n [\n -122.17758178710939,\n 48.98787759766659\n ],\n [\n -122.17689514160158,\n 49.002294379248696\n ],\n [\n -122.35267639160156,\n 49.00139345263396\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-02-08","noUsgsAuthors":false,"publicationDate":"2016-02-08","publicationStatus":"PW","scienceBaseUri":"56b081bee4b010e2af2a11c0","contributors":{"authors":[{"text":"Curran, Christopher A. 0000-0001-8933-416X ccurran@usgs.gov","orcid":"https://orcid.org/0000-0001-8933-416X","contributorId":1650,"corporation":false,"usgs":true,"family":"Curran","given":"Christopher","email":"ccurran@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":581513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":107001,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":581514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barbash, Jack E. 0000-0001-9854-8880 jbarbash@usgs.gov","orcid":"https://orcid.org/0000-0001-9854-8880","contributorId":1003,"corporation":false,"usgs":true,"family":"Barbash","given":"Jack","email":"jbarbash@usgs.gov","middleInitial":"E.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":581515,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Magirl, Christopher S. 0000-0002-9922-6549 magirl@usgs.gov","orcid":"https://orcid.org/0000-0002-9922-6549","contributorId":1822,"corporation":false,"usgs":true,"family":"Magirl","given":"Christopher","email":"magirl@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":581516,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cox, Stephen E. 0000-0001-6614-8225 secox@usgs.gov","orcid":"https://orcid.org/0000-0001-6614-8225","contributorId":1642,"corporation":false,"usgs":true,"family":"Cox","given":"Stephen","email":"secox@usgs.gov","middleInitial":"E.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":581517,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Norton, Katherine K. knorton@usgs.gov","contributorId":156270,"corporation":false,"usgs":true,"family":"Norton","given":"Katherine K.","email":"knorton@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":581521,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gendaszek, Andrew S. 0000-0002-2373-8986 agendasz@usgs.gov","orcid":"https://orcid.org/0000-0002-2373-8986","contributorId":3509,"corporation":false,"usgs":true,"family":"Gendaszek","given":"Andrew","email":"agendasz@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":581518,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Spanjer, Andrew R. 0000-0002-7288-2722 aspanjer@usgs.gov","orcid":"https://orcid.org/0000-0002-7288-2722","contributorId":156271,"corporation":false,"usgs":true,"family":"Spanjer","given":"Andrew","email":"aspanjer@usgs.gov","middleInitial":"R.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":581519,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Foreman, James R. 0000-0003-0535-4580 jforeman@usgs.gov","orcid":"https://orcid.org/0000-0003-0535-4580","contributorId":139316,"corporation":false,"usgs":true,"family":"Foreman","given":"James R.","email":"jforeman@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":581520,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70159980,"text":"ofr20151226 - 2015 - Science information to support Missouri River Scaphirhynchus albus (pallid sturgeon) effects analysis","interactions":[],"lastModifiedDate":"2017-03-03T09:08:04","indexId":"ofr20151226","displayToPublicDate":"2016-01-26T10:00:00","publicationYear":"2015","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":"2015-1226","title":"Science information to support Missouri River Scaphirhynchus albus (pallid sturgeon) effects analysis","docAbstract":"

The Missouri River Pallid Sturgeon Effects Analysis (EA) was commissioned by the U.S. Army Corps of Engineers to develop a foundation of understanding of how pallid sturgeon (Scaphirhynchus albus) population dynamics are linked to management actions in the Missouri River. The EA consists of several steps: (1) development of comprehensive, conceptual ecological models illustrating pallid sturgeon population dynamics and links to management actions and other drivers; (2) compilation and assessment of available scientific literature, databases, and models; (3) development of predictive, quantitative models to explore the system dynamics and population responses to management actions; and (4) analysis and assessment of effects of system operations and actions on species’ habitats and populations. This report addresses the second objective, compilation and assessment of relevant information.

\n

Scientific information on pallid sturgeon and its environment has grown substantially during the last decade. Presently available (2015) information indicates that stocked sturgeon are surviving and growing, and that wild and hatchery sturgeon are spawning in the wild. However, natural recruitment to age-1 and older has not been detected since systematic sampling began in 2005. Population models indicate the sensitivity of population growth to certain demographic variables, in particular early-life stage survival and perhaps adult fecundity. This report documents the existing population models for the pallid sturgeon, and the substantial quantities of information developed through the Pallid Sturgeon Population Assessment Program (PSPAP), the Habitat Assessment and Monitoring Program (HAMP), the Comprehensive Sturgeon Research Project (CSRP), range-wide genetics databases, and related research studies. The reference database compiled for the EA consists of over 190 peer-reviewed documents specifically related to pallid sturgeon and over 12,000 references on the Missouri River system and related species.

\n

Notwithstanding the large quantity of information available, the EA faces challenges in synthesizing the information into useful, quantitative models. In particular, critical demographic parameters for population models remain uncertain and the functional relationships between the two main categories of physical management action—changes in flow regime and reengineering channel form—and pallid sturgeon survival responses are obscure. In addition, there is an overarching uncertainty about how physical management actions interact with propagation management actions in view of evolving understanding of genetic structuring of the pallid sturgeon population. Synthesis efforts are also challenged by the fragmentation of information sources among projects and agencies; one objective of this report is to facilitate future assessments by providing documentation of what information is available and where.

\n

 

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151226","collaboration":"Prepared in cooperation with the Missouri River Recovery Program","usgsCitation":"Jacobson, R.B., Parsley, M.J., Annis, M.L., Colvin, M.E., Welker, T.L., and James, D.A.,\n2015, Science information to support Missouri River Scaphirhynchus albus (pallid sturgeon)\neffects analysis: U.S. Geological Survey Open-File Report 2015–1226, 78 p.,\nhttps://dx.doi.org/10.3133/ofr20151226.","productDescription":"vii, 78 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059606","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":314737,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1226/coverthb.jpg"},{"id":314738,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1226/ofr20151226.pdf","text":"Report","size":"5.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1226"}],"country":"United States","state":"Iowa, Kansas, Missouri, Montana, Nebraska, North Dakota, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.6142578125,\n 37.28279464911045\n ],\n [\n -91.82373046875,\n 37.52715361723378\n ],\n [\n -90.06591796875,\n 38.8225909761771\n ],\n [\n -96.50390625,\n 43.96119063892024\n ],\n [\n -100.26123046875,\n 48.37084770238363\n ],\n [\n -104.04052734375,\n 48.99463598353408\n ],\n [\n -112.8076171875,\n 49.023461463214126\n ],\n [\n -112.60986328125,\n 45.089035564831036\n ],\n [\n -106.74316406249999,\n 40.979898069620155\n ],\n [\n -102.06298828125,\n 38.993572058209466\n ],\n [\n -94.6142578125,\n 37.28279464911045\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, USGS Columbia Environmental Research Center
4200 New Haven Road
Columbia, MO 65201

\n

http://www.cerc.usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-01-26","noUsgsAuthors":false,"publicationDate":"2016-01-26","publicationStatus":"PW","scienceBaseUri":"56a898b0e4b0b28f1184dbcd","contributors":{"authors":[{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":581415,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parsley, Michael J. 0000-0003-0097-6364 mparsley@usgs.gov","orcid":"https://orcid.org/0000-0003-0097-6364","contributorId":2608,"corporation":false,"usgs":true,"family":"Parsley","given":"Michael","email":"mparsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":581416,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Annis, Mandy L.","contributorId":41575,"corporation":false,"usgs":true,"family":"Annis","given":"Mandy L.","affiliations":[],"preferred":false,"id":581417,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colvin, Michael E.","contributorId":140975,"corporation":false,"usgs":false,"family":"Colvin","given":"Michael E.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":581418,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welker, Timothy L.","contributorId":140976,"corporation":false,"usgs":false,"family":"Welker","given":"Timothy","email":"","middleInitial":"L.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":581419,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"James, Daniel A.","contributorId":41737,"corporation":false,"usgs":true,"family":"James","given":"Daniel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":581420,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70162262,"text":"70162262 - 2015 - The shifting climate portfolio of the Greater Yellowstone Area","interactions":[],"lastModifiedDate":"2016-01-20T13:40:54","indexId":"70162262","displayToPublicDate":"2016-01-20T14:30:00","publicationYear":"2015","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":"The shifting climate portfolio of the Greater Yellowstone Area","docAbstract":"

Knowledge of climatic variability at small spatial extents (< 50 km) is needed to assess vulnerabilities of biological reserves to climate change. We used empirical and modeled weather station data to test if climate change has increased the synchrony of surface air temperatures among 50 sites within the Greater Yellowstone Area (GYA) of the interior western United States. This important biological reserve is the largest protected area in the Lower 48 states and provides critical habitat for some of the world’s most iconic wildlife. We focused our analyses on temporal shifts and shape changes in the annual distributions of seasonal minimum and maximum air temperatures among valley-bottom and higher elevation sites from 1948–2012. We documented consistent patterns of warming since 1948 at all 50 sites, with the most pronounced changes occurring during the Winter and Summer when minimum and maximum temperature distributions increased. These shifts indicate more hot temperatures and less cold temperatures would be expected across the GYA. Though the shifting statistical distributions indicate warming, little change in the shape of the temperature distributions across sites since 1948 suggest the GYA has maintained a diverse portfolio of temperatures within a year. Spatial heterogeneity in temperatures is likely maintained by the GYA’s physiographic complexity and its large size, which encompasses multiple climate zones that respond differently to synoptic drivers. Having a diverse portfolio of temperatures may help biological reserves spread the extinction risk posed by climate change.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0145060","usgsCitation":"Sepulveda, A.J., Tercek, M.T., Al-Chokhachy, R.K., Ray, A., Thoma, D.P., Hossack, B.R., Pederson, G.T., Rodman, A., and Olliff, T., 2015, The shifting climate portfolio of the Greater Yellowstone Area: PLoS ONE, v. 10, no. 12, e0145060; 16 p., https://doi.org/10.1371/journal.pone.0145060.","productDescription":"e0145060; 16 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065298","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471506,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0145060","text":"Publisher Index Page"},{"id":314536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n 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Science Center","active":true,"usgs":true}],"preferred":true,"id":589007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tercek, Mike T","contributorId":152351,"corporation":false,"usgs":false,"family":"Tercek","given":"Mike","email":"","middleInitial":"T","affiliations":[{"id":18906,"text":"Walking Shadow Ecology, Gardiner, MT, 59030, USA","active":true,"usgs":false}],"preferred":false,"id":589008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":589009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ray, Andrew","contributorId":101972,"corporation":false,"usgs":true,"family":"Ray","given":"Andrew","affiliations":[],"preferred":false,"id":589010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thoma, David P.","contributorId":45975,"corporation":false,"usgs":true,"family":"Thoma","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":589011,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":589012,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":589013,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rodman, Ann","contributorId":150932,"corporation":false,"usgs":false,"family":"Rodman","given":"Ann","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":589014,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Olliff, Tom","contributorId":152352,"corporation":false,"usgs":false,"family":"Olliff","given":"Tom","email":"","affiliations":[{"id":18907,"text":"National Park Service, Intermountain Region Landscape Conservation and Climate Change Division, 2327 University Way, Suite 2, Bozeman, MT 59715, USA","active":true,"usgs":false}],"preferred":false,"id":589015,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70162212,"text":"70162212 - 2015 - Stability of detectability over 17 years at a single site and other lizard detection comparisons from Guam","interactions":[],"lastModifiedDate":"2016-01-19T08:38:15","indexId":"70162212","displayToPublicDate":"2016-01-19T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Stability of detectability over 17 years at a single site and other lizard detection comparisons from Guam","docAbstract":"

To obtain quantitative information about population dynamics from counts of animals, the per capita detectabilities of each species must remain constant over the course of monitoring. We characterized lizard detection constancy for four species over 17 yr from a single site in northern Guam, a relatively benign situation because detection was relatively easy and we were able to hold constant the site, habitat type, species, season, and sampling method. We monitored two species of diurnal terrestrial skinks (Carlia ailanpalai [Curious Skink], Emoia caeruleocauda [Pacific Bluetailed Skink]) using glueboards placed on the ground in the shade for 3 h on rainless mornings, yielding 10,286 skink captures. We additionally monitored two species of nocturnal arboreal geckos (Hemidactylus frenatus [Common House Gecko]; Lepidodactylus lugubris [Mourning Gecko]) on the basis of 15,212 sightings. We compared these count samples to a series of complete censuses we conducted from four or more total removal plots (everything removed to mineral soil) totaling 400 m2(about 1% of study site) in each of the years 1995, 1999, and 2012, providing time-stamped quantification of detectability for each species. Unfortunately, the actual population trajectories taken by the four species were masked by unexplained variation in detectability. This observation of debilitating latent variability in lizard detectability under nearly ideal conditions undercuts our trust in population estimation techniques that fail to quantify venue-specific detectability, rely on pooled detection probability estimates, or assume that modulation in predefined environmental covariates suffices for estimating detectability.

","language":"English","publisher":"The Society for the Study of Amphibians and Reptiles","doi":"10.1670/14-085","usgsCitation":"Rodda, G.H., Dean-Bradley, K., Campbell, E., Fritts, T.H., Lardner, B., Yackel Adams, A.A., and Reed, R., 2015, Stability of detectability over 17 years at a single site and other lizard detection comparisons from Guam: Journal of Herpetology, v. 49, no. 4, p. 513-521, https://doi.org/10.1670/14-085.","productDescription":"9 p.","startPage":"513","endPage":"521","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057632","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":314455,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 144.60411071777344,\n 13.233261466546951\n ],\n [\n 144.60411071777344,\n 13.655328309840225\n ],\n [\n 144.97283935546872,\n 13.655328309840225\n ],\n [\n 144.97283935546872,\n 13.233261466546951\n ],\n [\n 144.60411071777344,\n 13.233261466546951\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"569f5e34e4b0961cf27fd16d","contributors":{"authors":[{"text":"Rodda, Gordon H. roddag@usgs.gov","contributorId":3196,"corporation":false,"usgs":true,"family":"Rodda","given":"Gordon","email":"roddag@usgs.gov","middleInitial":"H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":588873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dean-Bradley, Kathryn","contributorId":152309,"corporation":false,"usgs":false,"family":"Dean-Bradley","given":"Kathryn","email":"","affiliations":[{"id":18905,"text":"2016 Rosemont Drive, Landenberg, Pennsylvania, USA","active":true,"usgs":false}],"preferred":false,"id":588874,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell, Earl W. III","contributorId":84202,"corporation":false,"usgs":true,"family":"Campbell","given":"Earl W.","suffix":"III","affiliations":[],"preferred":false,"id":588875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fritts, Thomas H.","contributorId":77204,"corporation":false,"usgs":true,"family":"Fritts","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":588876,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lardner, Bjorn lardnerb@usgs.gov","contributorId":5546,"corporation":false,"usgs":true,"family":"Lardner","given":"Bjorn","email":"lardnerb@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":588877,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":588878,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Robert N. reedr@usgs.gov","contributorId":1686,"corporation":false,"usgs":true,"family":"Reed","given":"Robert N.","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":588872,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70162213,"text":"70162213 - 2015 - Caveats for correlative species distribution modeling","interactions":[],"lastModifiedDate":"2016-01-19T08:31:38","indexId":"70162213","displayToPublicDate":"2016-01-19T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1457,"text":"Ecological Informatics","active":true,"publicationSubtype":{"id":10}},"title":"Caveats for correlative species distribution modeling","docAbstract":"

Correlative species distribution models are becoming commonplace in the scientific literature and public outreach products, displaying locations, abundance, or suitable environmental conditions for harmful invasive species, threatened and endangered species, or species of special concern. Accurate species distribution models are useful for efficient and adaptive management and conservation, research, and ecological forecasting. Yet, these models are often presented without fully examining or explaining the caveats for their proper use and interpretation and are often implemented without understanding the limitations and assumptions of the model being used. We describe common pitfalls, assumptions, and caveats of correlative species distribution models to help novice users and end users better interpret these models. Four primary caveats corresponding to different phases of the modeling process, each with supporting documentation and examples, include: (1) all sampling data are incomplete and potentially biased; (2) predictor variables must capture distribution constraints; (3) no single model works best for all species, in all areas, at all spatial scales, and over time; and (4) the results of species distribution models should be treated like a hypothesis to be tested and validated with additional sampling and modeling in an iterative process.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2015.06.007","usgsCitation":"Jarnevich, C.S., Stohlgren, T.J., Kumar, S., Morisette, J.T., and Holcombe, T.R., 2015, Caveats for correlative species distribution modeling: Ecological Informatics, v. 29, no. 1, p. 6-15, https://doi.org/10.1016/j.ecoinf.2015.06.007.","productDescription":"10 p.","startPage":"6","endPage":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066207","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":314454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"569f5e30e4b0961cf27fd165","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":588879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stohlgren, Thomas J. 0000-0001-9696-4450 stohlgrent@usgs.gov","orcid":"https://orcid.org/0000-0001-9696-4450","contributorId":2902,"corporation":false,"usgs":true,"family":"Stohlgren","given":"Thomas","email":"stohlgrent@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":588880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kumar, Sunil","contributorId":84992,"corporation":false,"usgs":true,"family":"Kumar","given":"Sunil","affiliations":[],"preferred":false,"id":588881,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":588882,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holcombe, Tracy R. holcombet@usgs.gov","contributorId":3694,"corporation":false,"usgs":true,"family":"Holcombe","given":"Tracy","email":"holcombet@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":588883,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70162084,"text":"70162084 - 2015 - Long-term changes in nitrate conditions over the 20th century in two Midwestern Corn Belt streams","interactions":[],"lastModifiedDate":"2016-06-01T15:39:43","indexId":"70162084","displayToPublicDate":"2016-01-13T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Long-term changes in nitrate conditions over the 20th century in two Midwestern Corn Belt streams","docAbstract":"

Long-term changes in nitrate concentration and flux between the middle of the 20th century and the first decade of the 21st century were estimated for the Des Moines River and the Middle Illinois River, two Midwestern Corn Belt streams, using a novel weighted regression approach that is able to detect subtle changes in solute transport behavior over time. The results show that the largest changes in flow-normalized concentration and flux occurred between 1960 and 1980 in both streams, with smaller or negligible changes between 1980 and 2004. Contrasting patterns were observed between (1) nitrate export linked to non-point sources, explicitly runoff of synthetic fertilizer or other surface sources and (2) nitrate export presumably associated with point sources such as urban wastewater or confined livestock feeding facilities, with each of these modes of transport important under different domains of streamflow. Surface runoff was estimated to be consistently most important under high-flow conditions during the spring in both rivers. Nitrate export may also have been considerable in the Des Moines River even under some conditions during the winter when flows are generally lower, suggesting the influence of point sources during this time. Similar results were shown for the Middle Illinois River, which is subject to significant influence of wastewater from the Chicago area, where elevated nitrate concentrations were associated with at the lowest flows during the winter and fall. By modeling concentration directly, this study highlights the complex relationship between concentration and streamflow that has evolved in these two basins over the last 50 years. This approach provides insights about changing conditions that only become observable when stationarity in the relationship between concentration and streamflow is not assumed.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2015.03.062","usgsCitation":"Kelly, V.J., Stets, E., and Crawford, C.G., 2015, Long-term changes in nitrate conditions over the 20th century in two Midwestern Corn Belt streams: Journal of Hydrology, v. 525, p. 559-571, https://doi.org/10.1016/j.jhydrol.2015.03.062.","productDescription":"13 p.","startPage":"559","endPage":"571","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059752","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":471511,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2015.03.062","text":"Publisher Index Page"},{"id":314258,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa","city":"Keosaque, Peoria","otherGeospatial":"Des Moines River, Middle Illinois River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.01221466064453,\n 40.70380607385548\n ],\n [\n -92.01221466064453,\n 40.76676160346336\n ],\n [\n -91.9071578979492,\n 40.76676160346336\n ],\n [\n -91.9071578979492,\n 40.70380607385548\n ],\n [\n -92.01221466064453,\n 40.70380607385548\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.72396850585936,\n 40.602484146302096\n ],\n [\n -89.72396850585936,\n 40.76182096906601\n ],\n [\n -89.44656372070312,\n 40.76182096906601\n ],\n [\n -89.44656372070312,\n 40.602484146302096\n ],\n [\n -89.72396850585936,\n 40.602484146302096\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"525","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56977530e4b039675d00a6c0","contributors":{"authors":[{"text":"Kelly, Valerie J. vjkelly@usgs.gov","contributorId":4161,"corporation":false,"usgs":true,"family":"Kelly","given":"Valerie","email":"vjkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":588484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stets, Edward G. estets@usgs.gov","contributorId":3593,"corporation":false,"usgs":true,"family":"Stets","given":"Edward G.","email":"estets@usgs.gov","affiliations":[],"preferred":false,"id":588485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crawford, Charles G. 0000-0003-1653-7841 cgcrawfo@usgs.gov","orcid":"https://orcid.org/0000-0003-1653-7841","contributorId":1064,"corporation":false,"usgs":true,"family":"Crawford","given":"Charles","email":"cgcrawfo@usgs.gov","middleInitial":"G.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":588486,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70161998,"text":"70161998 - 2015 - Efficient wetland surface water detection and monitoring via Landsat: Comparison with in situ data from the Everglades Depth Estimation Network","interactions":[],"lastModifiedDate":"2019-12-12T10:54:01","indexId":"70161998","displayToPublicDate":"2016-01-11T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Efficient wetland surface water detection and monitoring via Landsat: Comparison with in situ data from the Everglades Depth Estimation Network","docAbstract":"

The U.S. Geological Survey is developing new Landsat science products. One, named Dynamic Surface Water Extent (DSWE), is focused on the representation of ground surface inundation as detected in cloud-/shadow-/snow-free pixels for scenes collected over the U.S. and its territories. Characterization of DSWE uncertainty to facilitate its appropriate use in science and resource management is a primary objective. A unique evaluation dataset developed from data made publicly available through the Everglades Depth Estimation Network (EDEN) was used to evaluate one candidate DSWE algorithm that is relatively simple, requires no scene-based calibration data, and is intended to detect inundation in the presence of marshland vegetation. A conceptual model of expected algorithm performance in vegetated wetland environments was postulated, tested and revised. Agreement scores were calculated at the level of scenes and vegetation communities, vegetation index classes, water depths, and individual EDEN gage sites for a variety of temporal aggregations. Landsat Archive cloud cover attribution errors were documented. Cloud cover had some effect on model performance. Error rates increased with vegetation cover. Relatively low error rates for locations of little/no vegetation were unexpectedly dominated by omission errors due to variable substrates and mixed pixel effects. Examined discrepancies between satellite and in situ modeled inundation demonstrated the utility of such comparisons for EDEN database improvement. Importantly, there seems no trend or bias in candidate algorithm performance as a function of time or general hydrologic conditions, an important finding for long-term monitoring. The developed database and knowledge gained from this analysis will be used for improved evaluation of candidate DSWE algorithms as well as other measurements made on Everglades surface inundation, surface water heights and vegetation using radar, lidar and hyperspectral instruments. Although no other sites have such an extensive in situ network or long-term records, the broader applicability of this and other candidate DSWE algorithms is being evaluated in other wetlands using this work as a guide. Continued interaction among DSWE producers and potential users will help determine whether the measured accuracies are adequate for practical utility in resource management.

","language":"English","publisher":"MDPI","doi":"10.3390/rs70912503","usgsCitation":"Jones, J., 2015, Efficient wetland surface water detection and monitoring via Landsat: Comparison with in situ data from the Everglades Depth Estimation Network: Remote Sensing, v. 9, no. 7, p. 12503-12538, https://doi.org/10.3390/rs70912503.","productDescription":"36 p.","startPage":"12503","endPage":"12538","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066317","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471512,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs70912503","text":"Publisher Index Page"},{"id":314188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.331787109375,\n 24.831610355586918\n ],\n [\n -80.31280517578125,\n 24.831610355586918\n ],\n [\n -80.31280517578125,\n 26.561506704037942\n ],\n [\n -81.331787109375,\n 26.561506704037942\n ],\n [\n -81.331787109375,\n 24.831610355586918\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-23","publicationStatus":"PW","scienceBaseUri":"5694d22de4b039675d005dc0","contributors":{"authors":[{"text":"Jones, John 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":588290,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70159957,"text":"sir20155176 - 2015 - Decision analysis to support development of the Glen Canyon Dam long-term experimental and management plan","interactions":[],"lastModifiedDate":"2024-03-04T20:23:08.804716","indexId":"sir20155176","displayToPublicDate":"2016-01-07T16:30:00","publicationYear":"2015","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":"2015-5176","title":"Decision analysis to support development of the Glen Canyon Dam long-term experimental and management plan","docAbstract":"

The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, National Park Service, and Argonne National Laboratory, completed a decision analysis to use in the evaluation of alternatives in the Environmental Impact Statement concerning the long-term management of water releases from Glen Canyon Dam and associated management activities. Two primary decision analysis methods, multicriteria decision analysis and the expected value of information, were used to evaluate the alternative strategies against the resource goals and to evaluate the influence of uncertainty.

\n

A total of 18 performance metrics associated with 8 out of 12 resource goals (fundamental objectives) were developed by the Bureau of Reclamation and National Park Service in partnership with subject-matter teams composed of Federal, State, tribal, and private experts. A total of 19 long-term strategies associated with 7 alternatives were developed by the Bureau of Reclamation, National Park Service, Argonne National Laboratory, U.S. Geological Survey, and Cooperating Agencies. The 19 long-term strategies were evaluated against the 18 performance metrics using a series of coupled simulation models, taking into account the effects of several important sources of uncertainty. A total of 27 Federal, State, tribal, and nongovernmental agencies were invited by the Assistant Secretary of Interior to participate in a swing-weighting exercise to understand the range of perspectives about how to place relative value on the resource goals and performance metrics; 14 of the 27 chose to participate. The results of the swing-weighting exercise were combined with the evaluation of the alternatives to complete a multicriteria decision analysis. The effects of uncertainty on the ranking of long-term strategies were evaluated through calculation of the value of information.

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The alternatives and their long-term strategies differed across performance metrics, producing unavoidable tradeoffs; thus, there was no long-term strategy that was dominated by another across all performance metrics. When the performance of each alternative was weighted across performance metrics, three alternatives (B, D, and G) were top-ranked depending on the set of weights proposed: Alternative B was favored by those stakeholders that placed a high value on hydropower; Alternative G was favored by those stakeholders that placed a high value on the restoration of natural processes, like beachbuilding and natural vegetation; and Alternative D was favored by the remaining stakeholders. Surprisingly, these rankings were not sensitive to the critical uncertainties that were evaluated; that is, the choice of a preferred long-term strategy was sensitive to the value-based judgment about how to place relative weight on the resource goals but was not sensitive to the uncertainties in the system dynamics that were evaluated in this analysis. The one area of uncertainty that did slightly affect the ranking of alternatives was the long-term pattern of hydrological input; because of this sensitivity, some attention to the possible effects of climate change is warranted.

\n

The results of the decision analysis are meant to serve as only one of many sources of information that can be used to evaluate the alternatives proposed in the Environmental Impact Statement. These results only focus on those resource goals for which quantitative performance metrics could be formulated and evaluated; there are other important aspects of the resource goals that also need to be considered. Not all the stakeholders who were invited to participate in the decision analysis chose to do so; thus, the Bureau of Reclamation, National Park Service, and U.S. Department of Interior may want to consider other input.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155176","collaboration":"Prepared in cooperation with the Bureau of Reclamation, National Park Service, and Argonne National Laboratory","usgsCitation":"Runge, M.C., LaGory, K.E., Russell, Kendra, Balsom, J.R., Butler, R.A., Coggins, L.G., Jr., Grantz, K.A., Hayse, John, Hlohowskyj, Ihor, Korman, Josh, May, J.E., O’Rourke, D.J., Poch, L.A., Prairie, J.R., VanKuiken, J.C., Van Lonkhuyzen, R.A., Varyu, D.R., Verhaaren, B.T., Vesekla, T.D., Williams, N.T., Wuthrich, K.K., Yackulic, C.B., Billerbeck, R.P., and Knowles, G.W., 2015, Decision analysis to support development of the Glen Canyon Dam Long-Term Experimental and Management Plan: U.S. Geological Survey Scientific Investigations Report 2015–5176, 64 p., https://dx.doi.org/10.3133/sir20155176.","productDescription":"xi, 64 p.","numberOfPages":"80","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070238","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":312032,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5176/sir20155176.pdf","text":"Report","size":"2.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5176"},{"id":312031,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5176/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Glen Canyon Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.70825195312501,\n 35.074964853989556\n ],\n [\n -114.70825195312501,\n 37.00255267215955\n ],\n [\n -111.258544921875,\n 37.00255267215955\n ],\n [\n -111.258544921875,\n 35.074964853989556\n ],\n [\n -114.70825195312501,\n 35.074964853989556\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Eastern Ecological Science Center
12100 Beech Forest Rd., Ste 4039
Laurel, MD 20708-4039

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2016-01-07","noUsgsAuthors":false,"publicationDate":"2016-01-07","publicationStatus":"PW","scienceBaseUri":"568f8c33e4b0e7a44bc5ec85","contributors":{"authors":[{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":581163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaGory, Kirk E.","contributorId":150246,"corporation":false,"usgs":false,"family":"LaGory","given":"Kirk","email":"","middleInitial":"E.","affiliations":[{"id":17946,"text":"Argonne National Laboratory","active":true,"usgs":false}],"preferred":false,"id":581164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Russell, Kendra","contributorId":150247,"corporation":false,"usgs":false,"family":"Russell","given":"Kendra","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":581165,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Balsom, Janet R.","contributorId":150248,"corporation":false,"usgs":false,"family":"Balsom","given":"Janet","email":"","middleInitial":"R.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":581166,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Butler, R. Alan","contributorId":150249,"corporation":false,"usgs":false,"family":"Butler","given":"R.","email":"","middleInitial":"Alan","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":581168,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coggins, Jr.","contributorId":54306,"corporation":false,"usgs":true,"family":"Coggins","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":581169,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grantz, Katrina A.","contributorId":150250,"corporation":false,"usgs":false,"family":"Grantz","given":"Katrina","email":"","middleInitial":"A.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":581170,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hayse, John","contributorId":150251,"corporation":false,"usgs":false,"family":"Hayse","given":"John","email":"","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":581171,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hlohowskyj, Ihor","contributorId":150252,"corporation":false,"usgs":false,"family":"Hlohowskyj","given":"Ihor","email":"","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":581172,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Korman, Josh","contributorId":29922,"corporation":false,"usgs":true,"family":"Korman","given":"Josh","affiliations":[],"preferred":false,"id":581173,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"May, James E.","contributorId":85255,"corporation":false,"usgs":true,"family":"May","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":581174,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"O’Rourke, Daniel J.","contributorId":150253,"corporation":false,"usgs":false,"family":"O’Rourke","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":581175,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Poch, Leslie A.","contributorId":150254,"corporation":false,"usgs":false,"family":"Poch","given":"Leslie","email":"","middleInitial":"A.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":581176,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Prairie, James R.","contributorId":150255,"corporation":false,"usgs":false,"family":"Prairie","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":581177,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"VanKuiken, Jack C.","contributorId":150256,"corporation":false,"usgs":false,"family":"VanKuiken","given":"Jack","email":"","middleInitial":"C.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":581178,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Van Lonkhuyzen, Robert A.","contributorId":49705,"corporation":false,"usgs":true,"family":"Van Lonkhuyzen","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":581179,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Varyu, David R.","contributorId":150257,"corporation":false,"usgs":false,"family":"Varyu","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":581180,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Verhaaren, Bruce T.","contributorId":150258,"corporation":false,"usgs":false,"family":"Verhaaren","given":"Bruce","email":"","middleInitial":"T.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":581181,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Veselka, Thomas D.","contributorId":150259,"corporation":false,"usgs":false,"family":"Veselka","given":"Thomas","email":"","middleInitial":"D.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":581182,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Williams, Nicholas T.","contributorId":150260,"corporation":false,"usgs":false,"family":"Williams","given":"Nicholas","email":"","middleInitial":"T.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":581183,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Wuthrich, Kelsey K.","contributorId":150261,"corporation":false,"usgs":false,"family":"Wuthrich","given":"Kelsey","email":"","middleInitial":"K.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":581184,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":581167,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Billerbeck, Robert P.","contributorId":150262,"corporation":false,"usgs":false,"family":"Billerbeck","given":"Robert","email":"","middleInitial":"P.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":581185,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Knowles, Glen W.","contributorId":150263,"corporation":false,"usgs":false,"family":"Knowles","given":"Glen","email":"","middleInitial":"W.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":581186,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}} ,{"id":70160922,"text":"70160922 - 2015 - Insights into controls on hexavalent chromium in groundwater provided by environmental tracers, Sacramento Valley, California, USA","interactions":[],"lastModifiedDate":"2016-01-05T10:11:06","indexId":"70160922","displayToPublicDate":"2016-01-05T11:00:00","publicationYear":"2015","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":"Insights into controls on hexavalent chromium in groundwater provided by environmental tracers, Sacramento Valley, California, USA","docAbstract":"
\n

Environmental tracers are useful for determining groundwater age and recharge source, yet their application in studies of geogenic Cr(VI) in groundwater has been limited. Environmental tracer data from 166 wells located in the Sacramento Valley, northern California, were interpreted and compared to Cr concentrations to determine the origin and age of groundwater with elevated Cr(VI), and better understand where Cr(VI) becomes mobilized and how it evolves along flowpaths. In addition to major ion and trace element concentrations, the dataset includes δ18O, δ2H, 3H concentration, 14C activity (of dissolved inorganic C), δ13C, 3He/4He ratio, and noble gas concentrations (He, Ne, Ar, Kr, Xe). Noble gas recharge temperatures (NGTs) were computed, and age-related tracers were interpreted in combination to constrain the age distribution in samples and sort them into six different age categories spanning from <60 yr old to >10,000 yr old. Nearly all measured Cr is in the form of Cr(IV). Concentrations range from <1 to 46 μg L−1, with 10% exceeding the state of California’s Cr(VI) maximum contaminant level of 10 μg L−1. Two groups with elevated Cr(VI) (⩾5 μg L−1) were identified. Group 1 samples are from the southern part of the valley and contain modern (<60 yr old) water, have elevated NO3− concentrations (>3 mg L−1), and commonly have δ18O values enriched relative to local precipitation. These samples likely contain irrigation water and are elevated due to accelerated mobilization of Cr(VI) in the unsaturated zone (UZ) in irrigated areas. Group 2 samples are from throughout the valley and typically contain water 1000–10,000 yr old, have δ18O values consistent with local precipitation, and have unexpectedly warm NGTs. Chromium(VI) concentrations in Group 2 samples may be elevated for multiple reasons, but the hypothesis most consistent with all available data (notably, the warm NGTs) is a relatively long UZ residence time due to recharge through a deep UZ near the margin of the basin. A possible explanation for why Cr(VI) may be primarily mobilized in the UZ rather than farther along flowpaths in the oxic portion of the saturated zone is more dynamic cycling of Mn in the UZ due to transient moisture and redox conditions.

\n
\n
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2015.05.010","usgsCitation":"Manning, A.H., Mills, C., Morrison, J.M., and Ball, L.B., 2015, Insights into controls on hexavalent chromium in groundwater provided by environmental tracers, Sacramento Valley, California, USA: Applied Geochemistry, v. 62, p. 186-199, https://doi.org/10.1016/j.apgeochem.2015.05.010.","productDescription":"14 p.","startPage":"186","endPage":"199","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060217","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":313330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.728515625,\n 37.900865092570065\n ],\n [\n -120.69580078125001,\n 38.25543637637947\n ],\n [\n -121.761474609375,\n 39.86758762451019\n ],\n [\n -121.9482421875,\n 40.73893324113603\n ],\n [\n -122.92602539062501,\n 40.36328834091583\n ],\n [\n -122.618408203125,\n 39.96870074491696\n ],\n [\n -122.662353515625,\n 39.54641191968671\n ],\n [\n -122.03613281249999,\n 38.315801006824984\n ],\n [\n -121.728515625,\n 37.900865092570065\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"568ce931e4b0e7a44bc0f10f","contributors":{"authors":[{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":584236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mills, Christopher T. 0000-0001-8414-1414 cmills@usgs.gov","orcid":"https://orcid.org/0000-0001-8414-1414","contributorId":150137,"corporation":false,"usgs":true,"family":"Mills","given":"Christopher T.","email":"cmills@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":584237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morrison, Jean M. 0000-0002-6614-8783 jmorrison@usgs.gov","orcid":"https://orcid.org/0000-0002-6614-8783","contributorId":994,"corporation":false,"usgs":true,"family":"Morrison","given":"Jean","email":"jmorrison@usgs.gov","middleInitial":"M.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":584238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":584239,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160925,"text":"70160925 - 2015 - Using noble gas tracers to constrain a groundwater flow model with recharge elevations: A novel approach for mountainous terrain","interactions":[],"lastModifiedDate":"2016-01-05T10:05:52","indexId":"70160925","displayToPublicDate":"2016-01-05T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Using noble gas tracers to constrain a groundwater flow model with recharge elevations: A novel approach for mountainous terrain","docAbstract":"

Environmental tracers provide information on groundwater age, recharge conditions, and flow processes which can be helpful for evaluating groundwater sustainability and vulnerability. Dissolved noble gas data have proven particularly useful in mountainous terrain because they can be used to determine recharge elevation. However, tracer-derived recharge elevations have not been utilized as calibration targets for numerical groundwater flow models. Herein, we constrain and calibrate a regional groundwater flow model with noble-gas-derived recharge elevations for the first time. Tritium and noble gas tracer results improved the site conceptual model by identifying a previously uncertain contribution of mountain block recharge from the Coast Mountains to an alluvial coastal aquifer in humid southwestern British Columbia. The revised conceptual model was integrated into a three-dimensional numerical groundwater flow model and calibrated to hydraulic head data in addition to recharge elevations estimated from noble gas recharge temperatures. Recharge elevations proved to be imperative for constraining hydraulic conductivity, recharge location, and bedrock geometry, and thus minimizing model nonuniqueness. Results indicate that 45% of recharge to the aquifer is mountain block recharge. A similar match between measured and modeled heads was achieved in a second numerical model that excludes the mountain block (no mountain block recharge), demonstrating that hydraulic head data alone are incapable of quantifying mountain block recharge. This result has significant implications for understanding and managing source water protection in recharge areas, potential effects of climate change, the overall water budget, and ultimately ensuring groundwater sustainability.

","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015WR017274","usgsCitation":"Doyle, J.M., Gleeson, T., Manning, A.H., and Mayer, K.U., 2015, Using noble gas tracers to constrain a groundwater flow model with recharge elevations: A novel approach for mountainous terrain: Water Resources Research, v. 51, no. 10, p. 8094-8113, https://doi.org/10.1002/2015WR017274.","productDescription":"20 p.","startPage":"8094","endPage":"8113","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065559","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":471513,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr017274","text":"Publisher Index Page"},{"id":313328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-12","publicationStatus":"PW","scienceBaseUri":"568ce932e4b0e7a44bc0f115","contributors":{"authors":[{"text":"Doyle, Jessica M.","contributorId":151068,"corporation":false,"usgs":false,"family":"Doyle","given":"Jessica","email":"","middleInitial":"M.","affiliations":[{"id":18175,"text":"Waterline Resources Inc., Nanaimo, British Columbia, Canada","active":true,"usgs":false}],"preferred":false,"id":584241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gleeson, Tom","contributorId":81041,"corporation":false,"usgs":true,"family":"Gleeson","given":"Tom","email":"","affiliations":[],"preferred":false,"id":584242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":584240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mayer, K. Ulrich","contributorId":151069,"corporation":false,"usgs":false,"family":"Mayer","given":"K.","email":"","middleInitial":"Ulrich","affiliations":[{"id":18176,"text":"Department of Earth and Ocean Science, University of British Columbia, Vancouver, British Columbia, Canada","active":true,"usgs":false}],"preferred":false,"id":584243,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157594,"text":"ofr20151187 - 2015 - Detecting sea-level hazards: Simple regression-based methods for calculating the acceleration of sea level","interactions":[],"lastModifiedDate":"2016-01-05T08:36:22","indexId":"ofr20151187","displayToPublicDate":"2016-01-04T13:30:00","publicationYear":"2015","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":"2015-1187","title":"Detecting sea-level hazards: Simple regression-based methods for calculating the acceleration of sea level","docAbstract":"

This report documents the development of statistical tools used to quantify the hazard presented by the response of sea-level elevation to natural or anthropogenic changes in climate and ocean circulation. A hazard is a physical process (or processes) that, when combined with vulnerability (or susceptibility to the hazard), results in risk. This study presents the development and comparison of new and existing sea-level analysis methods, exploration of the strengths and weaknesses of the methods using synthetic time series, and when appropriate, synthesis of the application of the method to observed sea-level time series. These reports are intended to enhance material presented in peer-reviewed journal articles where it is not always possible to provide the level of detail that might be necessary to fully support or recreate published results.

\n

The purpose of this report is to document and compare three simple methodologies that have previously been used to provide estimates with associated errors of the acceleration of sea-level elevation. These techniques have been used by coastal scientists and planners in assessing coastal risk over a wide range of spatial and temporal scales. Because relative sea-level (SL) elevation time series contain energetic fluctuations at many time scales, extracting what can be relatively small rate and acceleration signals (along with estimates of the error) from much larger “noise” has proven to be both difficult and controversial. Acceleration is a preferred measure of SL response to recent changes in the Earth’s climate because over time scales of 100 years or less slow vertical land motions (such as glacial isostatic adjustment) contribute only to the linear signal and not to acceleration, thus reducing the complexity of the analysis. Hence acceleration is useful if the goal of a study is to characterize and quantify the hazard associated with the changing relative elevation of water with respect to land on decadal time scales. Although in some cases it may be necessary to determine the cause of relative sea level rise, as a first step, it is important to accurately estimate the magnitude of the threat.

\n

Most researchers agree that global sea level (GSL) rose persistently through much of the 20th century at about 1.5–2.0 millimeters per year (mm/yr). There is far less agreement about whether the rate of sea-level rise (SLR) is increasing (that is, an acceleration in SL).

\n

Recent studies, and most of their predecessors, use tide gage data to quantify SL acceleration, ASL(t). In the current study, three techniques were used to calculate acceleration from tide gage data, and of those examined, it was determined that the two techniques based on sliding a regression window through the time series are more robust compared to the technique that fits a single quadratic form to the entire time series, particularly if there is temporal variation in the magnitude of the acceleration. The single-fit quadratic regression method has been the most commonly used technique in determining acceleration in tide gage data. The inability of the single-fit method to account for time-varying acceleration may explain some of the inconsistent findings between investigators. Properly quantifying ASL(t) from field measurements is of particular importance in evaluating numerical models of past, present, and future SLR resulting from anticipated climate change.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151187","issn":"2331-1258","usgsCitation":"Doran, K.S., Howd, P.A., and Sallenger, A.H., Jr., 2015, Detecting sea-level hazards—Simple regression-based methods for calculating the acceleration of sea level: U.S. Geological Survey Open-File Report 2015–1187, 28 p.","productDescription":"v, 28 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-039300","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":313205,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1187/cover.jpg"},{"id":313038,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1187/ofr20151187.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1187"}],"contact":"

St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
http://coastal.er.usgs.gov/

","tableOfContents":"","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"publishedDate":"2016-01-04","noUsgsAuthors":false,"publicationDate":"2016-01-04","publicationStatus":"PW","scienceBaseUri":"568b97a8e4b0e7594ee77620","contributors":{"authors":[{"text":"Doran, Kara S. 0000-0001-8050-5727","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":33010,"corporation":false,"usgs":true,"family":"Doran","given":"Kara S.","affiliations":[],"preferred":false,"id":573709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howd, Peter A. phowd@usgs.gov","contributorId":4105,"corporation":false,"usgs":true,"family":"Howd","given":"Peter","email":"phowd@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":583801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sallenger, Jr.","contributorId":105768,"corporation":false,"usgs":true,"family":"Sallenger","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":583802,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70184221,"text":"70184221 - 2015 - Relations between soil hydraulic properties and burn severity","interactions":[],"lastModifiedDate":"2017-03-06T11:29:10","indexId":"70184221","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Relations between soil hydraulic properties and burn severity","docAbstract":"

Wildfire can affect soil hydraulic properties, often resulting in reduced infiltration. The magnitude of change in infiltration varies depending on the burn severity. Quantitative approaches to link burn severity with changes in infiltration are lacking. This study uses controlled laboratory measurements to determine relations between a remotely sensed burn severity metric (dNBR, change in normalised burn ratio) and soil hydraulic properties (SHPs). SHPs were measured on soil cores collected from an area burned by the 2013 Black Forest fire in Colorado, USA. Six sites with the same soil type were selected across a range of burn severities, and 10 random soil cores were collected from each site within a 30-m diameter circle. Cumulative infiltration measurements were made in the laboratory using a tension infiltrometer to determine field-saturated hydraulic conductivity, Kfs, and sorptivity, S. These measurements were correlated with dNBR for values ranging from 124 (low severity) to 886 (high severity). SHPs were related to dNBR by inverse functions for specific conditions of water repellency (at the time of sampling) and soil texture. Both functions had a threshold value for dNBR between 124 and 420, where Kfs and S were unchanged and equal to values for soil unaffected by fire. For dNBRs >~420, the Kfs was an exponentially decreasing function of dNBR and S was a linearly decreasing function of dNBR. These initial quantitative empirical relations provide a first step to link SHPs to burn severity, and can be used in quantitative infiltration models to predict post-wildfire infiltration and resulting runoff.

","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF14062","usgsCitation":"Moody, J.A., Ebel, B.A., Nyman, P., Martin, D.A., Stoof, C.R., and McKinley, R., 2015, Relations between soil hydraulic properties and burn severity: International Journal of Wildland Fire, v. 25, no. 3, p. 279-293, https://doi.org/10.1071/WF14062.","productDescription":"15 p.","startPage":"279","endPage":"293","ipdsId":"IP-061603","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":336871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58be833be4b014cc3a3a99ef","contributors":{"authors":[{"text":"Moody, John A. 0000-0003-2609-364X jamoody@usgs.gov","orcid":"https://orcid.org/0000-0003-2609-364X","contributorId":771,"corporation":false,"usgs":true,"family":"Moody","given":"John","email":"jamoody@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":680603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":680604,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nyman, Petter","contributorId":187489,"corporation":false,"usgs":false,"family":"Nyman","given":"Petter","email":"","affiliations":[],"preferred":false,"id":680605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":1900,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":680606,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stoof, Cathelijne R.","contributorId":168663,"corporation":false,"usgs":false,"family":"Stoof","given":"Cathelijne","email":"","middleInitial":"R.","affiliations":[{"id":25346,"text":"Cornell University, Ithaca, NY","active":true,"usgs":false}],"preferred":false,"id":680607,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKinley, Randy 0000-0001-7644-6365 rmckinley@usgs.gov","orcid":"https://orcid.org/0000-0001-7644-6365","contributorId":1354,"corporation":false,"usgs":true,"family":"McKinley","given":"Randy","email":"rmckinley@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":680608,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70169155,"text":"70169155 - 2015 - Arctic biodiversity: Increasing richness accompanies shrinking refugia for a cold-associated tundra fauna","interactions":[],"lastModifiedDate":"2018-06-12T20:50:46","indexId":"70169155","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Arctic biodiversity: Increasing richness accompanies shrinking refugia for a cold-associated tundra fauna","docAbstract":"

As ancestral biodiversity responded dynamically to late-Quaternary climate changes, so are extant organisms responding to the warming trajectory of the Anthropocene. Ecological predictive modeling, statistical hypothesis tests, and genetic signatures of demographic change can provide a powerful integrated toolset for investigating these biodiversity responses to climate change, and relative resiliency across different communities. Within the biotic province of Beringia, we analyzed specimen localities and DNA sequences from 28 mammal species associated with boreal forest and Arctic tundra biomes to assess both historical distributional and evolutionary responses and then forecasted future changes based on statistical assessments of past and present trajectories, and quantified distributional and demographic changes in relation to major management regions within the study area. We addressed three sets of hypotheses associated with aspects of methodological, biological, and socio-political importance by asking (1) what is the consistency among implications of predicted changes based on the results of both ecological and evolutionary analyses; (2) what are the ecological and evolutionary implications of climate change considering either total regional diversity or distinct communities associated with major biomes; and (3) are there differences in management implications across regions? Our results indicate increasing Arctic richness through time that highlights a potential state shift across the Arctic landscape. However, within distinct ecological communities, we found a predicted decline in the range and effective population size of tundra species into several discrete refugial areas. Consistency in results based on a combination of both ecological and evolutionary approaches demonstrates increased statistical confidence by applying cross-discipline comparative analyses to conservation of biodiversity, particularly considering variable management regimes that seek to balance sustainable ecosystems with other anthropogenic values. Refugial areas for cold-adapted taxa appear to be persistent across both warm and cold climate phases and although fragmented, constitute vital regions for persistence of Arctic mammals.

","language":"English","publisher":"Ecological Society of America","doi":"10.1890/ES15-00104.1","usgsCitation":"Hope, A.G., Waltari, E., Malaney, J.L., Payer, D.C., Cook, J., and Talbot, S.L., 2015, Arctic biodiversity: Increasing richness accompanies shrinking refugia for a cold-associated tundra fauna: Ecosphere, v. 6, no. 9, p. 1-67, https://doi.org/10.1890/ES15-00104.1.","productDescription":"67 p.","startPage":"1","endPage":"67","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056204","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":471531,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es15-00104.1","text":"Publisher Index Page"},{"id":319203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-28","publicationStatus":"PW","scienceBaseUri":"56f3be2ce4b0f59b85e02da3","contributors":{"authors":[{"text":"Hope, Andrew G. 0000-0003-3814-2891 ahope@usgs.gov","orcid":"https://orcid.org/0000-0003-3814-2891","contributorId":4309,"corporation":false,"usgs":true,"family":"Hope","given":"Andrew","email":"ahope@usgs.gov","middleInitial":"G.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":623251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waltari, Eric","contributorId":105946,"corporation":false,"usgs":false,"family":"Waltari","given":"Eric","affiliations":[],"preferred":false,"id":623284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Malaney, Jason L.","contributorId":140462,"corporation":false,"usgs":false,"family":"Malaney","given":"Jason","email":"","middleInitial":"L.","affiliations":[{"id":13048,"text":"Department of Natural Resources and Environmental Science, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":623285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Payer, David C.","contributorId":7495,"corporation":false,"usgs":false,"family":"Payer","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":623286,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cook, J.A.","contributorId":60868,"corporation":false,"usgs":true,"family":"Cook","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":623287,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":623252,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70168949,"text":"70168949 - 2015 - Context of ancient aqueous environments on Mars from in situ geologic mapping at Endeavour Crater","interactions":[],"lastModifiedDate":"2018-11-13T10:58:25","indexId":"70168949","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"Context of ancient aqueous environments on Mars from in situ geologic mapping at Endeavour Crater","docAbstract":"

Using the Mars Exploration Rover Opportunity, we have compiled one of the first field geologic maps on Mars while traversing the Noachian terrain along the rim of the 22 km diameter Endeavour Crater (Latitude −2°16′33″, Longitude −5°10′51″). In situ mapping of the petrographic, elemental, structural, and stratigraphic characteristics of outcrops and rocks distinguishes four mappable bedrock lithologic units. Three of these rock units predate the surrounding Burns formation sulfate-rich sandstones and one, the Matijevic Formation, represents conditions on early Mars predating the formation of Endeavour Crater. The stratigraphy assembled from these observations includes several geologic unconformities. The differences in lithologic units across these unconformities record changes in the character and intensity of the Martian aqueous environment over geologic time. Water circulated through fractures in the oldest rocks over periods long enough that texturally and elementally significant alteration occurred in fracture walls. These oldest pre-Endeavour rocks and their network of mineralized and altered fractures were preserved by burial beneath impact ejecta and were subsequently exhumed and exposed. The alteration along joints in the oldest rocks and the mineralized veins and concentrations of trace metals in overlying lithologic units is direct evidence that copious volumes of mineralized and/or hydrothermal fluids circulated through the early Martian crust. The wide range in intensity of structural and chemical modification from outcrop to outcrop along the crater rim shows that the ejecta of large (>8 km in diameter) impact craters is complex. These results imply that geologic complexity is to be anticipated in other areas of Mars where cratering has been a fundamental process in the local and regional geology and mineralogy.

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