Occurrence models that account for imperfect detection of species are increasingly used for estimating geographical range, for determining species-landscape relations and to prioritize conservation actions worldwide. In 2010, we conducted a large-scale survey in Río Muni, the mainland territory of Equatorial Guinea, which aimed to estimate the probabilities of occurrence and detection of threatened mammals based on environmental covariates, and to identify priority areas for conservation. Interviews with hunters were designed to record presence/absence data of seven species (golden cat, leopard, forest elephant, forest buffalo, western gorilla, chimpanzee and mandrill) in 225 sites throughout the region. We fitted single season occupancy models and recently developed models which also include false positive errors (i.e. species detected in places where it actually does not occur), which should provide more accurate estimates for most species, which are susceptible to mis-identification. Golden cat and leopard had the lowest occurrence rates in the region, whereas primates had the highest rates. All species, except gorilla, were affected negatively by human settlements. The southern half of Río Muni showed the highest occurrence of the species studied, and conservation strategies for ensuring the persistence of threatened mammals should be focused on this area.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/srep33838","usgsCitation":"Martinez-Marti, C., Jimenez-Franco, M.V., Royle, J., Palazon, J.A., and Calvo, J.F., 2016, Integrating occurrence and detectability patterns based on interview data: a case study for threatened mammals in Equatorial Guinea: Scientific Reports, v. 6, 33838; 9 p., https://doi.org/10.1038/srep33838.","productDescription":"33838; 9 p.","ipdsId":"IP-078834","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470554,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep33838","text":"Publisher Index Page"},{"id":329485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Equatorial Guinea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 9.8162841796875,\n 2.3668802418421357\n ],\n [\n 9.84375,\n 2.3394375828714224\n ],\n [\n 9.832763671875,\n 2.311994386907854\n ],\n [\n 9.832763671875,\n 2.28455066023697\n ],\n [\n 9.8822021484375,\n 2.2406396093827334\n ],\n [\n 9.9151611328125,\n 2.2077054557054083\n ],\n [\n 9.942626953125,\n 2.20221635884472\n ],\n [\n 10.0140380859375,\n 2.180259769681356\n ],\n [\n 10.074462890625,\n 2.169281354771587\n ],\n [\n 10.140380859375,\n 2.169281354771587\n ],\n [\n 10.1788330078125,\n 2.1747705722118864\n ],\n [\n 10.2777099609375,\n 2.180259769681356\n ],\n [\n 11.35986328125,\n 2.1857489471296665\n ],\n [\n 11.348876953125,\n 0.9997051308419692\n ],\n [\n 9.7833251953125,\n 0.9997051308419692\n ],\n [\n 9.73388671875,\n 1.0656123898763876\n ],\n [\n 9.6734619140625,\n 1.0711045990129324\n ],\n [\n 9.569091796875,\n 1.016182073033441\n ],\n [\n 9.5526123046875,\n 1.0601201709472332\n ],\n [\n 9.5086669921875,\n 1.1150419135172274\n ],\n [\n 9.437255859375,\n 1.1095497845377595\n ],\n [\n 9.3878173828125,\n 1.087581167162357\n ],\n [\n 9.3328857421875,\n 1.1479944704491494\n ],\n [\n 9.327392578125,\n 1.2138984340943106\n ],\n [\n 9.3768310546875,\n 1.257833522873487\n ],\n [\n 9.3988037109375,\n 1.323734761011294\n ],\n [\n 9.437255859375,\n 1.3402098002785028\n ],\n [\n 9.4482421875,\n 1.417091829441639\n ],\n [\n 9.51416015625,\n 1.4720060101903352\n ],\n [\n 9.569091796875,\n 1.554374729735434\n ],\n [\n 9.5855712890625,\n 1.6202674001017445\n ],\n [\n 9.5965576171875,\n 1.6861579269987979\n ],\n [\n 9.667968749999998,\n 1.7520462233579808\n ],\n [\n 9.7119140625,\n 1.812441794538039\n ],\n [\n 9.7393798828125,\n 1.8893059628373186\n ],\n [\n 9.7943115234375,\n 1.9277367801405985\n ],\n [\n 9.7393798828125,\n 2.070472083193102\n ],\n [\n 9.766845703125,\n 2.180259769681356\n ],\n [\n 9.766845703125,\n 2.273573022378629\n ],\n [\n 9.7503662109375,\n 2.3504147112508176\n ],\n [\n 9.8162841796875,\n 2.3668802418421357\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-26","publicationStatus":"PW","scienceBaseUri":"57fe679ee4b0824b2d14370f","contributors":{"authors":[{"text":"Martinez-Marti, Chele","contributorId":175261,"corporation":false,"usgs":false,"family":"Martinez-Marti","given":"Chele","email":"","affiliations":[{"id":27549,"text":"Departamento de Ecología e Hidrología, Facultad de Biología, Universidad de Murcia, Campus de Espinardo, 30100 Murcia, Spain","active":true,"usgs":false}],"preferred":false,"id":650627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jimenez-Franco, Maria V.","contributorId":175262,"corporation":false,"usgs":false,"family":"Jimenez-Franco","given":"Maria","email":"","middleInitial":"V.","affiliations":[{"id":27549,"text":"Departamento de Ecología e Hidrología, Facultad de Biología, Universidad de Murcia, Campus de Espinardo, 30100 Murcia, Spain","active":true,"usgs":false}],"preferred":false,"id":650628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":138865,"corporation":false,"usgs":true,"family":"Royle","given":"J. 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The objective of this session, sponsored by the Historical Records Committee of the ESA, was to explore how ecological concepts have been shaped and changed by influences that are external to the scientific method, such as funding priorities, ideology, politics, personalities, and differences between the ecosystems where influential ecologists developed their ideas. Among the many memorable quotations of the philosopher/poet George Santayana (1863–1952) is the often quoted and misquoted observation, “Those who cannot remember the past are condemned to repeat it.”
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/bes2.1241","usgsCitation":"Huston, M., Ellison, A., Jackson, S.T., Frank, D., Jiang, X., Lau, M.K., Lockwood, J., Prager, S.D., Reiners, D.S., Reiners, W.A., Schulze, E., Vandermeer, J., and Werner, P.A., 2016, External influences on ecological theory: Report on organized oral Session 80 at the 100th Anniversary Meeting of the Ecological Society of America: Bulletin of the Ecological Society of America, v. 97, no. 3, p. 311-317, https://doi.org/10.1002/bes2.1241.","productDescription":"7 p.","startPage":"311","endPage":"317","ipdsId":"IP-075739","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":470555,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/bes2.1241","text":"Publisher Index Page"},{"id":357706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc03298e4b0fc368eb53a65","contributors":{"authors":[{"text":"Huston, M.A.","contributorId":28564,"corporation":false,"usgs":true,"family":"Huston","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":746211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellison, Aaron M.","contributorId":94996,"corporation":false,"usgs":true,"family":"Ellison","given":"Aaron M.","affiliations":[],"preferred":false,"id":746212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Stephen T. 0000-0002-1487-4652 stjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-1487-4652","contributorId":344,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen","email":"stjackson@usgs.gov","middleInitial":"T.","affiliations":[{"id":560,"text":"South Central Climate Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":745222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frank, David","contributorId":13969,"corporation":false,"usgs":true,"family":"Frank","given":"David","affiliations":[],"preferred":false,"id":746213,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jiang, X.","contributorId":150848,"corporation":false,"usgs":false,"family":"Jiang","given":"X.","email":"","affiliations":[],"preferred":false,"id":746214,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lau, Matthew K.","contributorId":208171,"corporation":false,"usgs":false,"family":"Lau","given":"Matthew","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":746215,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lockwood, Jeffrey A.","contributorId":208172,"corporation":false,"usgs":false,"family":"Lockwood","given":"Jeffrey A.","affiliations":[],"preferred":false,"id":746216,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prager, Steven D.","contributorId":208173,"corporation":false,"usgs":false,"family":"Prager","given":"Steven","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":746217,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reiners, Derek S.","contributorId":208175,"corporation":false,"usgs":false,"family":"Reiners","given":"Derek","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":746218,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reiners, William A.","contributorId":147117,"corporation":false,"usgs":false,"family":"Reiners","given":"William","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":746219,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Schulze, Ernst-Detlef","contributorId":189321,"corporation":false,"usgs":false,"family":"Schulze","given":"Ernst-Detlef","email":"","affiliations":[],"preferred":false,"id":746220,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Vandermeer, J.H.","contributorId":14350,"corporation":false,"usgs":true,"family":"Vandermeer","given":"J.H.","email":"","affiliations":[],"preferred":false,"id":746221,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Werner, Patricia A.","contributorId":208176,"corporation":false,"usgs":false,"family":"Werner","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":746222,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70176627,"text":"70176627 - 2016 - Encounters with Pinyon-Juniper influence riskier movements in Greater Sage-Grouse across the Great Basin","interactions":[],"lastModifiedDate":"2016-09-26T17:21:40","indexId":"70176627","displayToPublicDate":"2016-09-25T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Encounters with Pinyon-Juniper influence riskier movements in Greater Sage-Grouse across the Great Basin","docAbstract":"Fine-scale spatiotemporal studies can better identify relationships between individual survival and habitat fragmentation so that mechanistic interpretations can be made at the population level. Recent advances in Global Positioning System (GPS) technology and statistical models capable of deconstructing high-frequency location data have facilitated interpretation of animal movement within a behaviorally mechanistic framework. Habitat fragmentation due to singleleaf pinyon (Pinus monophylla; hereafter pinyon) and Utah juniper (Juniperus osteosperma; hereafter juniper) encroachment into sagebrush (Artemisia spp.) communities is a commonly implicated perturbation that can adversely influence greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) demographic rates. Using an extensive GPS data set (233 birds and 282,954 locations) across 12 study sites within the Great Basin, we conducted a behavioral change point analysis and subsequently constructed Brownian bridge movement models from each behaviorally homogenous section. We found a positive relationship between modeled movement rate and probability of encountering pinyon-juniper with significant variation among age classes. The probability of encountering pinyon-juniper among adults was two and three times greater than that of yearlings and juveniles, respectively. However, the movement rate in response to the probability of encountering pinyon-juniper trees was 1.5 times greater for juveniles. We then assessed the risk of mortality associated with an interaction between movement rate and the probability of encountering pinyon-juniper using shared frailty models. During pinyon-juniper encounters, on average, juvenile, yearling, and adult birds experienced a 10.4%, 0.2%, and 0.3% reduction in annual survival probabilities. Populations that used pinyon-juniper habitats with a frequency ≥ 3.8 times the overall mean experienced decreases in annual survival probabilities of 71.1%, 0.9%, and 0.9%. This analytical framework identifies a likely behavioral mechanism behind how pinyon-juniper encroachment decreases habitat suitability for sage-grouse, whereby encountering pinyon-juniper stimulates faster yet riskier movements that may make sage-grouse more vulnerable to visually acute predators.","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rama.2016.07.004","collaboration":"FWS, BLM, NDOW, FS","usgsCitation":"Prochazka, B.G., Coates, P.S., Ricca, M.A., Casazza, M.L., Gustafson, K.B., and Hull, J.M., 2016, Encounters with Pinyon-Juniper influence riskier movements in Greater Sage-Grouse across the Great Basin: Rangeland Ecology and Management, https://doi.org/10.1016/j.rama.2016.07.004.","onlineOnly":"Y","ipdsId":"IP-074788","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":470556,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2016.07.004","text":"Publisher Index Page"},{"id":329009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c63ce4b0bc0bec09c854","contributors":{"authors":[{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649420,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649422,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649423,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gustafson, K. Benjamin 0000-0003-3530-0372 kgustafson@usgs.gov","orcid":"https://orcid.org/0000-0003-3530-0372","contributorId":166818,"corporation":false,"usgs":true,"family":"Gustafson","given":"K.","email":"kgustafson@usgs.gov","middleInitial":"Benjamin","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649424,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hull, Josh M.","contributorId":174840,"corporation":false,"usgs":false,"family":"Hull","given":"Josh","email":"","middleInitial":"M.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":649425,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176637,"text":"70176637 - 2016 - First estimates of the probability of survival in a small-bodied, high-elevation frog (Boreal Chorus Frog, Pseudacris maculata), or how historical data can be useful","interactions":[],"lastModifiedDate":"2021-08-24T15:36:59.792178","indexId":"70176637","displayToPublicDate":"2016-09-23T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"First estimates of the probability of survival in a small-bodied, high-elevation frog (Boreal Chorus Frog, Pseudacris maculata), or how historical data can be useful","title":"First estimates of the probability of survival in a small-bodied, high-elevation frog (Boreal Chorus Frog, Pseudacris maculata), or how historical data can be useful","docAbstract":"In an era of shrinking budgets yet increasing demands for conservation, the value of existing (i.e., historical) data are elevated. Lengthy time series on common, or previously common, species are particularly valuable and may be available only through the use of historical information. We provide first estimates of the probability of survival and longevity (0.67–0.79 and 5–7 years, respectively) for a subalpine population of a small-bodied, ostensibly common amphibian, the Boreal Chorus Frog (Pseudacris maculata (Agassiz, 1850)), using historical data and contemporary, hypothesis-driven information–theoretic analyses. We also test a priori hypotheses about the effects of color morph (as suggested by early reports) and of drought (as suggested by recent climate predictions) on survival. Using robust mark–recapture models, we find some support for early hypotheses regarding the effect of color on survival, but we find no effect of drought. The congruence between early findings and our analyses highlights the usefulness of historical information in providing raw data for contemporary analyses and context for conservation and management decisions.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjz-2016-0024","usgsCitation":"Muths, E.L., Scherer, R.D., Amburgey, S.M., Matthews, T., Spencer, A.W., and Corn, P., 2016, First estimates of the probability of survival in a small-bodied, high-elevation frog (Boreal Chorus Frog, Pseudacris maculata), or how historical data can be useful: Canadian Journal of Zoology, v. 94, no. 9, p. 599-606, https://doi.org/10.1139/cjz-2016-0024.","productDescription":"8 p.","startPage":"599","endPage":"606","ipdsId":"IP-064683","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":488529,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/73513","text":"External Repository"},{"id":328941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c63ce4b0bc0bec09c856","contributors":{"authors":[{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":649575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scherer, R. D.","contributorId":8061,"corporation":false,"usgs":false,"family":"Scherer","given":"R.","email":"","middleInitial":"D.","affiliations":[{"id":6674,"text":"Department of Integrative Biology, University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":649576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amburgey, S. M.","contributorId":174896,"corporation":false,"usgs":false,"family":"Amburgey","given":"S.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":649577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matthews, T.","contributorId":174897,"corporation":false,"usgs":false,"family":"Matthews","given":"T.","email":"","affiliations":[],"preferred":false,"id":649578,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spencer, A. W.","contributorId":174898,"corporation":false,"usgs":false,"family":"Spencer","given":"A.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":649579,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corn, P.S.","contributorId":63751,"corporation":false,"usgs":true,"family":"Corn","given":"P.S.","affiliations":[],"preferred":false,"id":649580,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70175284,"text":"sir20165115 - 2016 - Simulation of groundwater withdrawal scenarios for the Redwall-Muav and Coconino Aquifer Systems of northern and central Arizona","interactions":[],"lastModifiedDate":"2016-09-26T08:58:47","indexId":"sir20165115","displayToPublicDate":"2016-09-23T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5115","title":"Simulation of groundwater withdrawal scenarios for the Redwall-Muav and Coconino Aquifer Systems of northern and central Arizona","docAbstract":"The Northern Arizona Regional Groundwater Flow Model was used to estimate the hydrologic changes, including water-level change and groundwater discharge to streams and springs, that may result from future changes in groundwater withdrawals in and near the Coconino Plateau Water Advisory Council study area, Coconino and Navajo Counties, Arizona. Three future groundwater withdrawal scenarios for tribal and nontribal uses were developed by the Coconino Plateau Water Advisory Council and were simulated for the period representing the years from 2006 through 2105. Scenario 1 assumes no major changes in groundwater use except for increased demand based on population projections. Scenario 2 assumes that a pipeline will provide a source of surface water from Lake Powell to areas near Cameron and Moenkopi that would replace local groundwater withdrawals. Scenario 3 assumes that the pipeline extends to the Flagstaff and Williams areas, and would replace groundwater demands for water in the area.
The Coconino Plateau Water Advisory Council withdrawal scenarios primarily influence water levels and groundwater discharge in the Coconino Plateau basin, near the western margin of the Little Colorado River Plateau basin, and the Verde Valley subbasin. Simulated effects of the withdrawal scenarios are superimposed on effects of previous variations in groundwater withdrawals and artificial and incidental recharge. Pre-scenario variations include changes in water-levels in wells; groundwater storage; discharge to streams and springs; and evapotranspiration by plants that use groundwater. Future variations in groundwater discharge and water-levels in wells will continue to occur as a result of both the past and any future changes.
Water-level variations resulting from post-2005 stresses, including groundwater withdrawals and incidental and artificial recharge, in the area of the withdrawal scenarios are primarily localized and superimposed on the regional changes caused by variations in stresses that occurred since the beginning of the initial stresses in the early 1900s through 2005. Withdrawal scenario 1 produced a broad region on the Coconino Plateau where water-levels declined 3–5 feet by 2105, and local areas with water-level declines of 100 feet or more where groundwater withdrawals are concentrated, near the City of Flagstaff Woody Mountain and Lake Mary well fields, and the towns of Tusayan, Williams, and Moenkopi. Water-level rises of 100 feet or more were simulated at areas of incidental recharge near wastewater treatment facilities near Flagstaff, Tusayan, Grand Canyon South Rim, Williams, and Munds Park.
Simulated water-level change from 2006 through 2105 for scenarios 2 and 3 is mostly different from water-level change simulated for scenario 1 at the local level. For scenarios 2 and 3, water levels near Cameron in 2105 where 1–3 feet higher than simulated for scenario 1. Water levels at Moenkopi are more than 100 feet higher due to the elimination of a proposed withdrawal well that was simulated in scenario 1. Scenario 3 eliminates more groundwater withdrawals in the Flagstaff and Williams areas, simulates 1–3 feet less water-level decline than scenario 1 across much of the Coconino Plateau, and water levels that are as much as 50 feet higher than simulated by scenario 1 near withdrawal wells in the Williams and Flagstaff areas.
Scenario 1 simulated the most change in groundwater discharge for the Little Colorado River below Cameron and for Oak Creek above Page Springs where declines in discharge of about 1.3 and 0.9 cubic feet per second (ft3/s), respectively, were simulated. Other simulated changes in discharge through 2105 in scenario 1 are losses of less than 0.4 ft3/s at the Upper Verde River, losses of less than 0.3 ft3/s at Havasu Creek and at Colorado River below Havasu Creek, losses of less than 0.1 ft3/s at Clear Creek, and increases in flow at the south rim springs and Chevelon Creek of less than 0.1 and 0.3 ft3/s, respectively. Simulated changes in discharge for scenarios 2 and 3 are less than for scenario 1 because of lower rates of groundwater withdrawal. Scenario 3 resulted in greater groundwater discharge than scenarios 1 and 2 at all major groundwater discharge features from 2006 through 2105 except for Clear and Chevelon Creeks, where the same groundwater discharge was simulated by each of the three scenarios.
Changes in groundwater discharge are expected to occur after 2105 to all major surface features that discharge from the Redwall-Muav and Coconino aquifers because change in aquifer storage was occurring at the end of the simulation in 2105. The accuracy of simulated changes resulting from the Coconino Plateau Water Advisory Council groundwater withdrawal scenarios is dependent on the persistence of several hydrologic assumptions that are inherent in the Northern Arizona Regional Groundwater Flow Model including, but not limited to, the reasonably accurate simulation of (1) transmissivity distributions, (2) distributions of vertical hydraulic properties, (3) distributions of spatial rates of withdrawal and incidental recharge, (4) aquifer extents, and (5) hydrologic barriers and conduits.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165115","collaboration":"Prepared in cooperation with the Arizona Department of Water Resources and Yavapai County","usgsCitation":"Pool, D.R., 2016, Simulation of groundwater withdrawal scenarios for the Redwall-Muav and Coconino aquifer systems of northern and central Arizona: U.S. Geological Survey Scientific Investigations Report 2016–5115, 38 p., https://dx.doi.org/10.3133/sir20165115.","productDescription":"vi, 38 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-072545","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":328682,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5115/coverthb.jpg"},{"id":328683,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5115/sir20165115.pdf","text":"Report","size":"7.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5115"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5384521484375,\n 34.511083202999714\n ],\n [\n -112.5384521484375,\n 36.9806150652861\n ],\n [\n -110.50048828124999,\n 36.9806150652861\n ],\n [\n -110.50048828124999,\n 34.511083202999714\n ],\n [\n -112.5384521484375,\n 34.511083202999714\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
http://az.water.usgs.gov/
On Thursday evening, May 23, 2013 (0347 May 24 UTC), a moment magnitude (Mw) = 5.7 earthquake occurred northeast of Canyondam, California. A two-person team of U.S. Geological Survey scientists went to the area to search for surface rupture and to canvass damage in the communities around Lake Almanor. While the causative fault had not been identified at the time of the field survey, surface rupture was expected to have occurred just south of Lake Almanor, approximately 2–4 kilometers south of the epicenter. No surface rupture was discovered. Felt intensity among the communities around Lake Almanor appeared to vary significantly. Lake Almanor West (LAW), Lake Almanor Country Club (LACC), and Hamilton Branch (HB) experienced Modified Mercalli Intensity (MMI) ≥7, whereas other communities around the lake experienced MMI ≤6; the maximum observed intensity was MMI 8, in LAW. Damage in the high intensity areas consisted of broken and collapsed chimneys, ruptured pipes, and some damage to foundations and to structural elements within houses. Although this shaking damage is not usually expected for an Mw 5.7 earthquake, the intensities at Lake Almanor Country Club correlate with the peak ground acceleration (38 percent g) and peak ground velocity (30 centimeters per second) recorded by the California Strong Motion Instrumentation Program accelerometer located at the nearby Lake Almanor Fire Station. The intensity distribution for the three hardest hit areas (LAW, LACC, and HB) appears to increase as the azimuth from epicenter to the intensity sites approaches the fault strike. The small communities of Almanor and Prattville on the southwestern shore of Lake Almanor experienced somewhat lower intensities. The town of Canyondam experienced a lower intensity as well, despite its location up-dip of the earthquake rupture. This report contains information on the earthquake itself, the search for surface rupture, and the damage we observed and compiled from other sources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161145","usgsCitation":"Chapman, K., Gold, M.B., Boatwright, J., Sipe, J., Quitoriano, V., Dreger, D., and Hardebeck, J., 2016, Faulting, damage, and intensity in the Canyondam earthquake of May 23, 2013: U.S. Geological Survey Open-File Report 2016-1145, 49 p., https://dx.doi.org/10.3133/ofr20161145. ","productDescription":"iv, 49 p.","onlineOnly":"Y","ipdsId":"IP-079067","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":328669,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1145/ofr20161145.pdf","text":"Report","size":"14.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1145"},{"id":328668,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1145/coverthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.508544921875,\n 38.46219172306828\n ],\n [\n -122.508544921875,\n 40.643135583312805\n ],\n [\n -119.33349609375,\n 40.643135583312805\n ],\n [\n -119.33349609375,\n 38.46219172306828\n ],\n [\n -122.508544921875,\n 38.46219172306828\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
http://earthquake.usgs.gov/
Although biotic responses to contemporary climate change are spatially pervasive and often reflect synergies between climate and other ecological disturbances, the relative importance of climatic factors versus habitat extent for species persistence remains poorly understood. To address this shortcoming, we performed surveys for American pikas (Ochotona princeps) at > 910 locations in 3 geographic regions of western North America during 2014 and 2015, complementing earlier modern (1994–2013) and historical (1898–1990) surveys. We sought to compare extirpation rates and the relative importance of climatic factors versus habitat area for pikas in a mainland-versus-islands framework. In each region, we found widespread evidence of distributional loss—local extirpations, upslope retractions, and encounter of only old sign. Locally comprehensive surveys suggest extirpation of O. princeps from 5 of 9 new sites from the hydrographic Great Basin and from 11 of 29 sites in northeastern California. Although American pikas were recorded as recently as 2011 in Zion National Park and in 2012 from Cedar Breaks National Monument in Utah, O. princeps now appears extirpated from all reported localities in both park units. Multiple logistic regressions for each region suggested that both temperature-related and water-balance-related variables estimated from DAYMET strongly explained pika persistence at sites in the Great Basin and in Utah but not in the Sierra-Cascade “mainland” portion of northeastern California. Conversely, talus-habitat area did not predict American pika persistence in the Great Basin or Utah but strongly predicted persistence in the Sierra-Cascade mainland. These results not only add new areas to our understanding of long-term trend of the American pika’s distribution, but also can inform decisions regarding allocation of conservation effort and management actions. Burgeoning research on species such as O. princeps has collectively demonstrated the heterogeneity and nuance with which climate can act on the distribution of mountain-dwelling mammals.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/jmammal/gyw128","usgsCitation":"Beever, E.A., Perrine, J.D., Rickman, T., Flores, M., Clark, J.P., Waters, C., Weber, S.S., Yardley, B., Thoma, D.P., Chesley-Preston, T.L., Goehring, K.E., Magnuson, M., Nordensten, N., Nelson, M., and Collins, G.H., 2016, Pika (Ochotona princeps) losses from two isolated regions reflect temperature and water balance, but reflect habitat area in a mainland region: Journal of Mammalogy, v. 97, no. 6, p. 1495-1511, https://doi.org/10.1093/jmammal/gyw128.","productDescription":"17 p.","startPage":"1495","endPage":"1511","ipdsId":"IP-061599","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":462075,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyw128","text":"Publisher Index Page"},{"id":328851,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"6","noUsgsAuthors":false,"publicationDate":"2016-08-25","publicationStatus":"PW","scienceBaseUri":"57f7c63ce4b0bc0bec09c866","chorus":{"doi":"10.1093/jmammal/gyw128","url":"http://dx.doi.org/10.1093/jmammal/gyw128","publisher":"Oxford University Press (OUP)","authors":"Beever Erik A., Perrine John D., Rickman Tom, Flores Mary, Clark John P., Waters Cassie, Weber Shana S., Yardley Braden, Thoma David, Chesley-Preston Tara, Goehring Kenneth E., Magnuson Michael, Nordensten Nancy, Nelson Melissa, Collins Gail H.","journalName":"Journal of Mammalogy","publicationDate":"8/25/2016"},"contributors":{"authors":[{"text":"Beever, Erik A. 0000-0002-9369-486X 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Mary","contributorId":174799,"corporation":false,"usgs":false,"family":"Flores","given":"Mary","email":"","affiliations":[],"preferred":false,"id":649300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, John P.","contributorId":174800,"corporation":false,"usgs":false,"family":"Clark","given":"John","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":649301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waters, Cassie","contributorId":174801,"corporation":false,"usgs":false,"family":"Waters","given":"Cassie","email":"","affiliations":[],"preferred":false,"id":649302,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weber, Shana S.","contributorId":174802,"corporation":false,"usgs":false,"family":"Weber","given":"Shana","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":649303,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yardley, Braden","contributorId":174803,"corporation":false,"usgs":false,"family":"Yardley","given":"Braden","email":"","affiliations":[],"preferred":false,"id":649304,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thoma, David P.","contributorId":45975,"corporation":false,"usgs":true,"family":"Thoma","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":649305,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Chesley-Preston, Tara L. tchesley-preston@usgs.gov","contributorId":5557,"corporation":false,"usgs":true,"family":"Chesley-Preston","given":"Tara","email":"tchesley-preston@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":649306,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Goehring, Kenneth E.","contributorId":174804,"corporation":false,"usgs":false,"family":"Goehring","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":649307,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Magnuson, Michael","contributorId":174806,"corporation":false,"usgs":false,"family":"Magnuson","given":"Michael","email":"","affiliations":[],"preferred":false,"id":649308,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Nordensten, Nancy","contributorId":174807,"corporation":false,"usgs":false,"family":"Nordensten","given":"Nancy","email":"","affiliations":[],"preferred":false,"id":649309,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Nelson, Melissa","contributorId":174808,"corporation":false,"usgs":false,"family":"Nelson","given":"Melissa","email":"","affiliations":[],"preferred":false,"id":649310,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Collins, Gail H.","contributorId":59170,"corporation":false,"usgs":false,"family":"Collins","given":"Gail","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":649311,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70175519,"text":"sir20165116 - 2016 - Simulating groundwater flow in karst aquifers with distributed parameter models—Comparison of porous-equivalent media and hybrid flow approaches","interactions":[],"lastModifiedDate":"2016-09-22T15:54:17","indexId":"sir20165116","displayToPublicDate":"2016-09-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5116","title":"Simulating groundwater flow in karst aquifers with distributed parameter models—Comparison of porous-equivalent media and hybrid flow approaches","docAbstract":"Understanding karst aquifers, for purposes of their management and protection, poses unique challenges. Karst aquifers are characterized by groundwater flow through conduits (tertiary porosity), and (or) layers with interconnected pores (secondary porosity) and through intergranular porosity (primary or matrix porosity). Since the late 1960s, advances have been made in the development of numerical computer codes and the use of mathematical model applications towards the understanding of dual (primary [matrix] and secondary [fractures and conduits]) porosity groundwater flow processes, as well as characterization and management of karst aquifers. The Floridan aquifer system (FAS) in Florida and parts of Alabama, Georgia, and South Carolina is composed of a thick sequence of predominantly carbonate rocks. Karst features are present over much of its area, especially in Florida where more than 30 first-magnitude springs occur, numerous sinkholes and submerged conduits have been mapped, and numerous circular lakes within sinkhole depressions are present. Different types of mathematical models have been applied for simulation of the FAS. Most of these models are distributed parameter models based on the assumption that, like a sponge, water flows through connected pores within the aquifer system and can be simulated with the same mathematical methods applied to flow through sand and gravel aquifers; these models are usually referred to as porous-equivalent media models. The partial differential equation solved for groundwater flow is the potential flow equation of fluid mechanics, which is used when flow is dominated by potential energy and has been applied for many fluid problems in which kinetic energy terms are dropped from the differential equation solved. In many groundwater model codes (basic MODFLOW), it is assumed that the water has a constant temperature and density and that flow is laminar, such that kinetic energy has minimal impact on flow. Some models have been developed that incorporate the submerged conduits as a one-dimensional pipe network within the aquifer rather than as discrete, extremely transmissive features in a porous-equivalent medium; these submerged conduit models are usually referred to as hybrid models and may include the capability to simulate both laminar and turbulent flow in the one-dimensional pipe network. Comparisons of the application of a porous-equivalent media model with and without turbulence (MODFLOW-Conduit Flow Process mode 2 and basic MODFLOW, respectively) and a hybrid (MODFLOW-Conduit Flow Process mode 1) model to the Woodville Karst Plain near Tallahassee, Florida, indicated that for annual, monthly, or seasonal average hydrologic conditions, all methods met calibration criteria (matched observed groundwater levels and average flows). Thus, the increased effort required, such as the collection of data on conduit location, to develop a hybrid model and its increased computational burden, is not necessary for simulation of average hydrologic conditions (non-laminar flow effects on simulated head and spring discharge were minimal). However, simulation of a large storm event in the Woodville Karst Plain with daily stress periods indicated that turbulence is important for matching daily springflow hydrographs. Thus, if matching streamflow hydrographs over a storm event is required, the simulation of non-laminar flow and the location of conduits are required. The main challenge in application of the methods and approaches for developing hybrid models relates to the difficulty of mapping conduit networks or having high-quality datasets to calibrate these models. Additionally, hybrid models have long simulation times, which can preclude the use of parameter estimation for calibration. Simulation of contaminant transport that does not account for preferential flow through conduits or extremely permeable zones in any approach is ill-advised. Simulation results in other karst aquifers or other parts of the FAS may differ from the comparison demonstrated herein.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165116","collaboration":"A product of the Water Use and Availability Science Program","usgsCitation":"Kuniansky, E.L., 2016, Simulating groundwater flow in karst aquifers with distributed parameter models—Comparison of porous-equivalent media and hybrid flow approaches: U.S. Geological Survey Scientific Investigations Report 2016–5116, 14 p., https://dx.doi.org/10.3133/sir20165116.","productDescription":"Report: v, 14 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-071317","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":328727,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5116/sir20165116.pdf","text":"Report","size":"3.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5116"},{"id":328833,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7PK0D87","text":"USGS data release - MODFLOW and MODFLOW Conduit Flow Process data sets for simulation experiments of the Woodville Karst Plain, near Tallahassee, Florida with three different approaches and different stress periods","description":"SIR 2016–5116 Data Release"},{"id":328726,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5116/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Woodville Karst Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.4903564453125,\n 30.04532159026885\n ],\n [\n -84.4903564453125,\n 30.456368670179007\n ],\n [\n -84.06875610351562,\n 30.456368670179007\n ],\n [\n -84.06875610351562,\n 30.04532159026885\n ],\n [\n -84.4903564453125,\n 30.04532159026885\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Chief, Caribbean-Florida Water Science Center-Florida
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559–6302
Bats (Order Chiroptera) are an abundant group of mammals with tremendous ecological value as insectivores and plant dispersers, but their role as reservoirs of zoonotic diseases has received more attention in the last decade. With the goal of managing disease in free-ranging bats, we tested modified vaccinia Ankara (MVA) and raccoon poxvirus (RCN) as potential vaccine vectors in the Brazilian Free-tailed bat (Tadarida brasiliensis), using biophotonic in vivo imaging and immunogenicity studies. Animals were administered recombinant poxviral vectors expressing the luciferase gene (MVA-luc, RCN-luc) through oronasal (ON) or intramuscular (IM) routes and subsequently monitored for bioluminescent signal indicative of viral infection. No clinical illness was noted after exposure to any of the vectors, and limited luciferase expression was observed. Higher and longer levels of expression were observed with the RCN-luc construct. When given IM, luciferase expression was limited to the site of injection, while ON exposure led to initial expression in the oral cavity, often followed by secondary replication at another location, likely the gastric mucosa or gastric associated lymphatic tissue. Viral DNA was detected in oral swabs up to 7 and 9 days post infection (dpi) for MVA and RCN, respectively. While no live virus was detected in oral swabs from MVA-infected bats, titers up to 3.88 x 104 PFU/ml were recovered from oral swabs of RCN-infected bats. Viral DNA was also detected in fecal samples from two bats inoculated IM with RCN, but no live virus was recovered. Finally, we examined the immunogenicity of a RCN based rabies vaccine (RCN-G) following ON administration. Significant rabies neutralizing antibody titers were detected in the serum of immunized bats using the rapid fluorescence focus inhibition test (RFFIT). These studies highlight the safety and immunogenicity of attenuated poxviruses and their potential use as vaccine vectors in bats.
","language":"English","publisher":"Elsevier Ltd.","doi":"10.1016/j.vaccine.2016.08.088","usgsCitation":"Stading, B., Osorio, J., Velasco-Villa, A., Smotherman, M., Kingstad-Bakke, B., and Rocke, T.E., 2016, Infectivity of attenuated poxvirus vaccine vectors and immunogenicity of a raccoonpox vectored rabies vaccine in the Brazilian Free-tailed bat (Tadarida brasiliensis): Vaccine, v. 34, no. 44, p. 5352-5358, https://doi.org/10.1016/j.vaccine.2016.08.088.","productDescription":"7 p.","startPage":"5352","endPage":"5358","ipdsId":"IP-077071","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":470558,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.1016/j.vaccine.2016.08.088","text":"Publisher Index Page"},{"id":328815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"44","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c63de4b0bc0bec09c872","chorus":{"doi":"10.1016/j.vaccine.2016.08.088","url":"http://dx.doi.org/10.1016/j.vaccine.2016.08.088","publisher":"Elsevier BV","authors":"Stading Ben R., Osorio Jorge E., Velasco-Villa Andres, Smotherman Michael, Kingstad-Bakke Brock, Rocke Tonie E.","journalName":"Vaccine","publicationDate":"10/2016"},"contributors":{"authors":[{"text":"Stading, Benjamin bstading@usgs.gov","contributorId":174757,"corporation":false,"usgs":true,"family":"Stading","given":"Benjamin","email":"bstading@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":649207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Osorio, Jorge E.","contributorId":50392,"corporation":false,"usgs":false,"family":"Osorio","given":"Jorge E.","affiliations":[{"id":13052,"text":"Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":649208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Velasco-Villa, Andres","contributorId":174760,"corporation":false,"usgs":false,"family":"Velasco-Villa","given":"Andres","email":"","affiliations":[{"id":16974,"text":"US Centers for Disease Control and Prevention (CDC)","active":true,"usgs":false}],"preferred":false,"id":649209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smotherman, Michael","contributorId":174761,"corporation":false,"usgs":false,"family":"Smotherman","given":"Michael","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":649210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kingstad-Bakke, Brock","contributorId":174762,"corporation":false,"usgs":false,"family":"Kingstad-Bakke","given":"Brock","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":649211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":649212,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176533,"text":"70176533 - 2016 - A semelparous fish continues upstream migration when exposed to alarm cue, but adjusts movement speed and timing","interactions":[],"lastModifiedDate":"2016-09-20T16:38:05","indexId":"70176533","displayToPublicDate":"2016-09-20T17:35:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":770,"text":"Animal Behaviour","active":true,"publicationSubtype":{"id":10}},"title":"A semelparous fish continues upstream migration when exposed to alarm cue, but adjusts movement speed and timing","docAbstract":"Animals make trade-offs between predation risk and pursuit of opportunities such as foraging and reproduction. Trade-offs between antipredator behaviours and foraging are well suited to manipulation in laboratory and field settings and have generated a vast compendium of knowledge. However, much less is known about how animals manage trade-offs between predation risk and pursuit of reproductive opportunities in the absence of the confounding effects of foraging. In the present study, we investigated how the nonfeeding migratory life stage of sea lamprey, Petromyzon marinus, responds to odour from dead conspecifics (a cue that induces avoidance behaviours in laboratory and field studies). We released groups of PIT-tagged sea lamprey 65 m from the shore of Lake Michigan or 287 m upstream in Carp Lake River and used antennas to detect their movements in the river. As the breeding season progressed, sea lamprey initiated upstream movement earlier and were more likely to enter the river. Sea lamprey that began the night in Lake Michigan entered Carp Lake River at higher rates and accelerated upstream when exposed to high concentrations of alarm cue, consistent with animals attempting to minimize time spent in risky areas. Sea lampreys that began the night in the river delayed upstream movement when exposed to alarm cue, consistent with animals sheltering and gathering information about a source of risk. We attribute this context-specific reaction to alarm cue to differences in perceived vulnerability to predation in sheltered positions in the river versus exposed positions in the lake. Once in the river, the vast majority of sea lamprey moved upstream independent of alarm cue or Julian date. Although life-history-induced time and energy budgets place rigid constraints on the direction of migration, sea lamprey attend to predation risk by modifying movement timing and speed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.anbehav.2016.08.007","usgsCitation":"Luhring, T.M., Meckley, T., Johnson, N.S., Siefkes, M.J., Hume, J.B., and Wagner, C.M., 2016, A semelparous fish continues upstream migration when exposed to alarm cue, but adjusts movement speed and timing: Animal Behaviour, v. 121, p. 41-51, https://doi.org/10.1016/j.anbehav.2016.08.007.","productDescription":"11 p.","startPage":"41","endPage":"51","ipdsId":"IP-076381","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":328783,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c63de4b0bc0bec09c878","contributors":{"authors":[{"text":"Luhring, Thomas M","contributorId":150988,"corporation":false,"usgs":false,"family":"Luhring","given":"Thomas","email":"","middleInitial":"M","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":649146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meckley, Trevor D.","contributorId":67417,"corporation":false,"usgs":true,"family":"Meckley","given":"Trevor D.","affiliations":[],"preferred":false,"id":649147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Nicholas S. njohnson@usgs.gov","contributorId":145440,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas","email":"njohnson@usgs.gov","middleInitial":"S.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":649148,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Siefkes, Michael J.","contributorId":36905,"corporation":false,"usgs":true,"family":"Siefkes","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":649149,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hume, John B.","contributorId":150987,"corporation":false,"usgs":false,"family":"Hume","given":"John","email":"","middleInitial":"B.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":649150,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, C. Michael","contributorId":145442,"corporation":false,"usgs":false,"family":"Wagner","given":"C.","email":"","middleInitial":"Michael","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":649151,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176523,"text":"70176523 - 2016 - Observations of nearshore groundwater discharge: Kahekili Beach Park submarine springs, Maui, Hawaii","interactions":[],"lastModifiedDate":"2025-05-13T16:46:33.72118","indexId":"70176523","displayToPublicDate":"2016-09-20T16:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Observations of nearshore groundwater discharge: Kahekili Beach Park submarine springs, Maui, Hawaii","docAbstract":"The study region encompasses the nearshore, coastal waters off west Maui, Hawaii. Here abundant groundwater—that carries with it a strong land-based fingerprint—discharges into the coastal waters and over a coral reef.
Coastal groundwater discharge is a ubiquitous hydrologic feature that has been shown to impact nearshore ecosystems and material budgets. A unique combined geochemical tracer and oceanographic time-series study addressed rates and oceanic forcings of submarine groundwater discharge at a submarine spring site off west Maui, Hawaii.
Estimates of submarine groundwater discharge were derived for a primary vent site and surrounding coastal waters off west Maui, Hawaii using an excess 222Rn (t1/2 = 3.8 d) mass balance model. Such estimates were complemented with a novel thoron (220Rn,t1/2 = 56 s) groundwater discharge tracer application, as well as oceanographic time series and thermal infrared imagery analyses. In combination, this suite of techniques provides new insight into the connectivity of the coastal aquifer with the near-shore ocean and examines the physical drivers of submarine groundwater discharge. Lastly, submarine groundwater discharge derived constituent concentrations were tabulated and compared to surrounding seawater concentrations. Such work has implications for the management of coastal aquifers and downstream nearshore ecosystems that respond to sustained constituent loadings via this submarine route.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2015.12.056","usgsCitation":"Swarzenski, P.W., Dulai, H., Kroeger, K., Smith, C.G., Dimova, N., Storlazzi, C., Prouty, N., Gingerich, S.B., and Glenn, C.R., 2016, Observations of nearshore groundwater discharge: Kahekili Beach Park submarine springs, Maui, Hawaii: Journal of Hydrology: Regional Studies, v. 11, p. 147-165, https://doi.org/10.1016/j.ejrh.2015.12.056.","productDescription":"19 p.","startPage":"147","endPage":"165","ipdsId":"IP-068143","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":328777,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":470561,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2015.12.056","text":"Publisher Index Page"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.69799804687497,\n 20.92604896920106\n ],\n [\n -156.69799804687497,\n 20.94685150573486\n ],\n [\n -156.6826343536377,\n 20.94685150573486\n ],\n [\n -156.6826343536377,\n 20.92604896920106\n ],\n [\n -156.69799804687497,\n 20.92604896920106\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c63de4b0bc0bec09c87c","contributors":{"authors":[{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":649120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dulai, H.","contributorId":174725,"corporation":false,"usgs":false,"family":"Dulai","given":"H.","email":"","affiliations":[],"preferred":false,"id":649121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kroeger, K.D.","contributorId":26060,"corporation":false,"usgs":true,"family":"Kroeger","given":"K.D.","email":"","affiliations":[],"preferred":false,"id":649122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":649123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dimova, N.","contributorId":66051,"corporation":false,"usgs":true,"family":"Dimova","given":"N.","affiliations":[],"preferred":false,"id":649124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Storlazzi, C. D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":127154,"corporation":false,"usgs":true,"family":"Storlazzi","given":"C. D.","affiliations":[],"preferred":false,"id":649125,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prouty, N.G.","contributorId":36766,"corporation":false,"usgs":true,"family":"Prouty","given":"N.G.","email":"","affiliations":[],"preferred":false,"id":649126,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gingerich, S. B.","contributorId":83958,"corporation":false,"usgs":true,"family":"Gingerich","given":"S.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":649127,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Glenn, C. R.","contributorId":174726,"corporation":false,"usgs":false,"family":"Glenn","given":"C.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":649128,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70176512,"text":"70176512 - 2016 - Learning and adaptation in waterfowl conservation: By chance or by design?","interactions":[],"lastModifiedDate":"2016-09-28T16:00:27","indexId":"70176512","displayToPublicDate":"2016-09-20T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Learning and adaptation in waterfowl conservation: By chance or by design?","docAbstract":"The most recent revision of the North American Waterfowl Management Plan seeks to increase the adaptive capacity of the management enterprise to cope with accelerating changes in climate, land-use patterns, agency priorities, and the waterfowl and wetlands constituency. Institutional and cultural changes of the magnitude envisioned are necessarily slow, messy processes, involving many actors who at a minimum must agree on the need for change. Waterfowl conservation now finds itself in the transition zone between business as usual and some new mode of operation. There are at least 2 different perspectives of this transition: one focuses on process, accountability, and planning for change; another focuses on solutions generated from an organic process of creativity, information sharing, and risk-taking. Both of these views have something to contribute, but some in the wildlife management enterprise may tend to focus more on the first view. We suggest that ideas from panarchy theory, especially those related to the behaviors of complex adaptive systems, can help waterfowl managers better understand and foster the institutional changes they seek.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.682","usgsCitation":"Johnson, F.A., Case, D.J., and Humburg, D.H., 2016, Learning and adaptation in waterfowl conservation: By chance or by design?: Wildlife Society Bulletin, v. 40, no. 3, p. 423-427, https://doi.org/10.1002/wsb.682.","productDescription":"5 p.","startPage":"423","endPage":"427","ipdsId":"IP-075263","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":498971,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.682","text":"Publisher Index Page"},{"id":328755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-29","publicationStatus":"PW","scienceBaseUri":"57ed5309e4b090825011d501","contributors":{"authors":[{"text":"Johnson, Fred A. 0000-0002-5854-3695 fjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":2773,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","email":"fjohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":649038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Case, David J.","contributorId":140653,"corporation":false,"usgs":false,"family":"Case","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":13543,"text":"DJ Case & Associates","active":true,"usgs":false}],"preferred":false,"id":649039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Humburg, Dale H.","contributorId":174698,"corporation":false,"usgs":false,"family":"Humburg","given":"Dale","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":649040,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176516,"text":"70176516 - 2016 - Disease introduction is associated with a phase transition in bighorn sheep demographics","interactions":[],"lastModifiedDate":"2018-08-07T12:40:01","indexId":"70176516","displayToPublicDate":"2016-09-20T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Disease introduction is associated with a phase transition in bighorn sheep demographics","docAbstract":"Ecological theory suggests that pathogens are capable of regulating or limiting host population dynamics, and this relationship has been empirically established in several settings. However, although studies of childhood diseases were integral to the development of disease ecology, few studies show population limitation by a disease affecting juveniles. Here, we present empirical evidence that disease in lambs constrains population growth in bighorn sheep (Ovis canadensis) based on 45 years of population-level and 18 years of individual-level monitoring across 12 populations. While populations generally increased (λ = 1.11) prior to disease introduction, most of these same populations experienced an abrupt change in trajectory at the time of disease invasion, usually followed by stagnant-to-declining growth rates (λ = 0.98) over the next 20 years. Disease-induced juvenile mortality imposed strong constraints on population growth that were not observed prior to disease introduction, even as adult survival returned to pre-invasion levels. Simulations suggested that models including persistent disease-induced mortality in juveniles qualitatively matched observed population trajectories, whereas models that only incorporated all-age disease events did not. We use these results to argue that pathogen persistence may pose a lasting, but under-recognized, threat to host populations, particularly in cases where clinical disease manifests primarily in juveniles.
","language":"English","publisher":"Wiley","doi":"10.1002/ecy.1520","usgsCitation":"Manlove, K., Cassirer, E.F., Cross, P.C., Plowright, R., and Hudson, P., 2016, Disease introduction is associated with a phase transition in bighorn sheep demographics: Ecology, v. 97, no. 10, p. 2593-2602, https://doi.org/10.1002/ecy.1520.","productDescription":"10 p.","startPage":"2593","endPage":"2602","ipdsId":"IP-075822","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":470563,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecy.1520","text":"External Repository"},{"id":328752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-19","publicationStatus":"PW","scienceBaseUri":"57f7c63de4b0bc0bec09c884","contributors":{"authors":[{"text":"Manlove, Kezia","contributorId":68204,"corporation":false,"usgs":true,"family":"Manlove","given":"Kezia","affiliations":[],"preferred":false,"id":649059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cassirer, E. Frances","contributorId":23404,"corporation":false,"usgs":true,"family":"Cassirer","given":"E.","email":"","middleInitial":"Frances","affiliations":[],"preferred":false,"id":649060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":649061,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plowright, Raina K.","contributorId":23038,"corporation":false,"usgs":true,"family":"Plowright","given":"Raina K.","affiliations":[],"preferred":false,"id":649062,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hudson, Peter J.","contributorId":85056,"corporation":false,"usgs":true,"family":"Hudson","given":"Peter J.","affiliations":[],"preferred":false,"id":649063,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70175364,"text":"sir20165118 - 2016 - Magnitude, frequency, and trends of floods at gaged and ungaged sites in Washington, based on data through water year 2014","interactions":[],"lastModifiedDate":"2019-03-14T14:54:40","indexId":"sir20165118","displayToPublicDate":"2016-09-20T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5118","title":"Magnitude, frequency, and trends of floods at gaged and ungaged sites in Washington, based on data through water year 2014","docAbstract":"An investigation into the magnitude and frequency of floods in Washington State computed the annual exceedance probability (AEP) statistics for 648 U.S. Geological Survey unregulated streamgages in and near the borders of Washington using the recorded annual peak flows through water year 2014. This is an updated report from a previous report published in 1998 that used annual peak flows through the water year 1996. New in this report, a regional skew coefficient was developed for the Pacific Northwest region that includes areas in Oregon, Washington, Idaho and western Montana within the Columbia River drainage basin south of the United States-Canada border, the coastal areas of Oregon and western Washington, and watersheds draining into Puget Sound, Washington. The skew coefficient is an important term in the Log Pearson Type III equation used to define the distribution of the log-transformed annual peaks. The Expected Moments Algorithm was used to fit historical and censored peak-flow data to the log Pearson Type III distribution. A Multiple Grubb-Beck test was employed to censor low outliers of annual peak flows to improve on the frequency distribution. This investigation also includes a section on observed trends in annual peak flows that showed significant trends (p-value < 0.05) in 21 of 83 long-term sites, but with small magnitude Kendall tau values suggesting a limited monotonic trend in the time series of annual peaks. Most of the sites with a significant trend in western Washington were positive and all the sites with significant trends (three sites) in eastern Washington were negative.
Multivariate regression analysis with measured basin characteristics and the AEP statistics at long-term, unregulated, and un-urbanized (defined as drainage basins with less than 5 percent impervious land cover for this investigation) streamgages within Washington and some in Idaho and Oregon that are near the Washington border was used to develop equations to estimate AEP statistics at ungaged basins. Washington was divided into four regions to improve the accuracy of the regression equations; a set of equations for eight selected AEPs and for each region were constructed. Selected AEP statistics included the annual peak flows that equaled or exceeded 50, 20, 10, 4, 2, 1, 0.5 and 0.2 percent of the time equivalent to peak flows for peaks with a 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively. Annual precipitation and drainage area were the significant basin characteristics in the regression equations for all four regression regions in Washington and forest cover was significant for the two regression regions in eastern Washington. Average standard error of prediction for the regional regression equations ranged from 70.19 to 125.72 percent for Regression Regions 1 and 2 on the eastern side of the Cascade Mountains and from 43.22 to 58.04 percent for Regression Regions 3 and 4 on the western side of the Cascade Mountains. The pseudo coefficient of determination (where a value of 100 signifies a perfect regression model) ranged from 68.39 to 90.68 for Regression Regions 1 and 2, and 92.35 to 95.44 for Regions 3 and 4.
The calculated AEP statistics for the streamgages and the regional regression equations are expected to be incorporated into StreamStats after the publication of this report. StreamStats is the interactive Web-based map tool created by the U.S. Geological Survey to allow the user to choose a streamgage and obtain published statistics or choose ungaged locations where the program automatically applies the regional regression equations and computes the estimates of the AEP statistics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165118","collaboration":"Prepared in cooperation with the Washington State Department of Transportation and the Washington State Department of Ecology","usgsCitation":"Mastin, M.C., Konrad, C.P., Veilleux, A.G., and Tecca, A.E., 2016, Magnitude, frequency, and trends of floods at gaged and ungaged sites in Washington, based on data through water year 2014 (ver 1.2, November 2017): U.S. Geological Survey Scientific Investigations Report 2016–5118, 70 p., https://dx.doi.org/10.3133/sir20165118.","productDescription":"Report: vi, 69 p.; 3 Tables","numberOfPages":"80","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-075256","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":329272,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5118/versionHist.txt","size":"3 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\"}}]}","edition":"Version 1.0: Originally post September 20, 2016; Version 1.1: October 4, 2016; Version 1.2: November 2017","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
We present results of population genetic analyses performed on Oregon silverspot butterflies (OSB; Speyeria zerene hippolyta) in western Oregon and northwestern California. We used DNA sequences from a 561-base pair region of the mitochondrial cytochrome oxidase subunit I (COI) gene for a dataset comprised of 112 S. z. hippolyta and 32 S. z. gloriosa individuals collected at 9 locations in western Oregon and northwestern California. The most pertinent findings thus far are summarized as follows:
Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
Data acquired by Harris Corporation’s (Melbourne, FL, USA) Geiger-mode IntelliEarth™ sensor and Sigma Space Corporation’s (Lanham-Seabrook, MD, USA) Single Photon HRQLS sensor were evaluated and compared to accepted 3D Elevation Program (3DEP) data and survey ground control to assess the suitability of these new technologies for the 3DEP. While not able to collect data currently to meet USGS lidar base specification, this is partially due to the fact that the specification was written for linear-mode systems specifically. With little effort on part of the manufacturers of the new lidar systems and the USGS Lidar specifications team, data from these systems could soon serve the 3DEP program and its users. Many of the shortcomings noted in this study have been reported to have been corrected or improved upon in the next generation sensors.
","language":"English","publisher":"MDPI","doi":"10.3390/rs8090767","usgsCitation":"Stoker, J.M., Abdullah, Q., Nayegandhi, A., and Winehouse, J., 2016, Evaluation of single photon and Geiger mode Lidar for the 3D Elevation Program: Remote Sensing, v. 8, no. 9, Article 767; 16 p., https://doi.org/10.3390/rs8090767.","productDescription":"Article 767; 16 p.","ipdsId":"IP-077259","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":470564,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs8090767","text":"Publisher Index Page"},{"id":328736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-19","publicationStatus":"PW","scienceBaseUri":"57f7c63de4b0bc0bec09c88e","contributors":{"authors":[{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":649023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abdullah, Qassim","contributorId":174668,"corporation":false,"usgs":false,"family":"Abdullah","given":"Qassim","email":"","affiliations":[{"id":27496,"text":"Woolpert","active":true,"usgs":false}],"preferred":false,"id":649024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nayegandhi, Amar","contributorId":37292,"corporation":false,"usgs":true,"family":"Nayegandhi","given":"Amar","affiliations":[],"preferred":false,"id":649025,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winehouse, Jayna","contributorId":174696,"corporation":false,"usgs":false,"family":"Winehouse","given":"Jayna","email":"","affiliations":[],"preferred":false,"id":649026,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176493,"text":"70176493 - 2016 - Evidence for shallow megathrust slip across the Unalaska seismic gap during the great 1957 Andreanof Islands earthquake, eastern Aleutian Islands, Alaska","interactions":[],"lastModifiedDate":"2018-08-21T16:19:39","indexId":"70176493","displayToPublicDate":"2016-09-19T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for shallow megathrust slip across the Unalaska seismic gap during the great 1957 Andreanof Islands earthquake, eastern Aleutian Islands, Alaska","docAbstract":"We reassess the slip distribution of the 1957 Andreanof Islands earthquake in the eastern part of the aftershock zone where published slip models infer little or no slip. Eyewitness reports, tide gauge data, and geological evidence for 9–23 m tsunami runups imply seafloor deformation offshore Unalaska Island in 1957, in contrast with previous studies that labeled the area a seismic gap. Here, we simulate tsunami dynamics for a suite of deformation models that vary in depth and amount of megathrust slip. Tsunami simulations show that a shallow (5–15 km deep) rupture with ~20 m of slip most closely reproduces the 1957 Dutch Harbor marigram and nearby >18 m runup at Sedanka Island marked by stranded drift logs. Models that place slip >20 km predict waves that arrive too soon. Our results imply that shallow slip on the megathrust in 1957 extended east into an area that presently creeps.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016GL070704","usgsCitation":"Nicolsky, D., Freymueller, J., Witter, R., Suleimani, E.N., and Koehler, R., 2016, Evidence for shallow megathrust slip across the Unalaska seismic gap during the great 1957 Andreanof Islands earthquake, eastern Aleutian Islands, Alaska: Geophysical Research Letters, v. 43, no. 19, p. 10328-10337, https://doi.org/10.1002/2016GL070704.","productDescription":"10 p.","startPage":"10328","endPage":"10337","ipdsId":"IP-079549","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":490016,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl070704","text":"Publisher Index Page"},{"id":328733,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"19","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-06","publicationStatus":"PW","scienceBaseUri":"57f7c63ee4b0bc0bec09c892","chorus":{"doi":"10.1002/2016gl070704","url":"http://dx.doi.org/10.1002/2016gl070704","publisher":"Wiley-Blackwell","authors":"Nicolsky D. J., Freymueller J. T., Witter R. C., Suleimani E. N., Koehler R. D.","journalName":"Geophysical Research Letters","publicationDate":"10/6/2016","auditedOn":"12/1/2016"},"contributors":{"authors":[{"text":"Nicolsky, D. J.","contributorId":174684,"corporation":false,"usgs":false,"family":"Nicolsky","given":"D. J.","affiliations":[{"id":13662,"text":"Geophysical Institute, University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":649017,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freymueller, J.T.","contributorId":51482,"corporation":false,"usgs":true,"family":"Freymueller","given":"J.T.","email":"","affiliations":[],"preferred":false,"id":649018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":649019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suleimani, E. N.","contributorId":174695,"corporation":false,"usgs":false,"family":"Suleimani","given":"E.","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":649020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koehler, R.D.","contributorId":55925,"corporation":false,"usgs":true,"family":"Koehler","given":"R.D.","email":"","affiliations":[],"preferred":false,"id":649021,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174983,"text":"sir20165108 - 2016 - Flood-inundation map library for the Licking River and South Fork Licking River near Falmouth, Kentucky","interactions":[],"lastModifiedDate":"2016-09-19T13:57:31","indexId":"sir20165108","displayToPublicDate":"2016-09-19T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5108","title":"Flood-inundation map library for the Licking River and South Fork Licking River near Falmouth, Kentucky","docAbstract":"Digital flood inundation maps for a 17-mile reach of Licking River and 4-mile reach of South Fork Licking River near Falmouth, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with Pendleton County and the U.S. Army Corps of Engineers–Louisville District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://wim.usgs.gov/FIMI/FloodInundationMapper.html, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Licking River at Catawba, Ky., (station 03253500) and the USGS streamgage on the South Fork Licking River at Hayes, Ky., (station 03253000). Current conditions (2015) for the USGS streamgages may be obtained online at the USGS National Water Information System site (http://waterdata.usgs.gov/nwis). In addition, the streamgage information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http:/water.weather.gov/ahps/). The flood hydrograph forecasts provided by the NWS are usually collocated with USGS streamgages. The forecasted peak-stage information, also available on the NWS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.
In this study, flood profiles were computed for the Licking River reach and South Fork Licking River reach by using a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current (2015) stage-discharge relations for the Licking River at Catawba, Ky., and the South Fork Licking River at Hayes, Ky., USGS streamgages. The calibrated model was then used to calculate 60 water-surface profiles for a sequence of flood stages, at 2-foot intervals, referenced to the streamgage datum and ranging from an elevation near bankfull to the elevation associated with a major flood that occurred in the region in 1997. To delineate the flooded area at each interval flood stage, the simulated water-surface profiles were combined with a digital elevation model of the study area by using geographic information system software.
The availability of these flood inundation maps for Falmouth, Ky., along with online information regarding current stages from the USGS streamgages and forecasted stages from the NWS, provides emergency management personnel and local residents with information that is critical for flood response activities such as evacuations, road closures, and post-flood recovery efforts.
Director, USGS Indiana-Kentucky Water Science Center
9818 Bluegrass Parkway
Louisville, KY 40299
Between 2010 and 2014, the U.S. Geological Survey completed a series of laboratory and field experiments designed to develop methodology to support the National Park Service’s long-term atmospheric pollutant monitoring efforts in parklands of Arctic Alaska. The goals of this research were to develop passive sampling methods that could be used for long-term monitoring of inorganic pollutants in remote areas of arctic parklands and characterize relations between wet and dry deposition of atmospheric pollutants to that of concentrations accumulated by mosses, specifically the stair-step, splendid feather moss, Hylocomium splendens. Mosses and lichens have been used by National Park Service managers as atmospheric pollutant biomonitors since about 1990; however, additional research is needed to better characterize the dynamics of moss bioaccumulation for various classes of atmospheric pollutants. To meet these research goals, the U.S. Geological Survey investigated the use of passive ionexchange collectors (IECs) that were adapted from the design of Fenn and others (2004). Using a modified IEC configuration, mulitple experiments were completed that included the following: (a) preliminary laboratory and development testing of IECs, (b) pilot-scale validation field studies during 2012 with IECs at sites with instrumental monitoring stations, and (c) deployment of IECs in 2014 at sites in Alaska having known or suspected regional sources of atmospheric pollutants where samples of Hylocomium splendens moss also could be collected for comparison. The targeted substances primarily included ammonium, nitrate, and sulfate ions, and certain toxicologically important trace metals, including cadmium, cobalt, copper, nickel, lead, and zinc.
Deposition of atmospheric pollutants is comparatively low throughout most of Alaska; consequently, modifications of the original IEC design were needed. The most notable modification was conversion from a single-stage mixed-bed column to a two-stage arrangement. With the modified IEC design, ammonium, nitrate, and sulfate ions were determined with a precision of between 5 and 10 percent relative standard deviation for the low loads that happen in remote areas of Alaska. Results from 2012 field studies demonstrated that the targeted ions were stable and fully retained on the IEC during field deployment and could be fully recovered by extraction in the laboratory. Importantly, measurements of annual loads determined by combining snowpack and IEC sampling at sites near National Atmospheric Deposition Program monitoring stations was comparable to results obtained by the National Atmospheric Deposition Program.
Field studies completed in 2014 included snowpack and IEC samples to measure depositional loads; the results were compared to concentrations of similar substances in co-located moss samples. Analyses of constituents in snow and IECs included ammonium, nitrate, and sulfate ions; and a suite of trace metals. Constituent measurements in Hylocomium splendens moss included total nitrogen, phosphorous, and sulfur, and trace metals. To recover ammonium ions and metal ions from the upper cation-exchange column, a two-step extraction procedure was developed from laboratory spiking experiments. The 2014 studies determined that concentrations of certain metals, nitrogen, and sulfur in tissues of Hylocomium splendens moss reflected differences in presumptive deposition from local atmospheric sources. Moss tissues collected from two sites farthest from urban locales had the lowest levels of total nitrogen and sulfur, whereas tissues collected from three of the urban sites had the greatest concentrations of many of the trace metals. Moss tissue concentrations of three trace metals (cobalt, chromium, and nickel) were strongly (positively) Spearman’s rank correlated (p<0.05) with annual depositional loads of those metals. In addition, moss sulfur concentrations were positively rank correlated with annual depositional loads of sulfate (p<0.07). Exploratory models indicated linear uptake of the three metals by Hylocomium splendens moss and nonlinear uptake of sulfur from sulfate.
Our results provided useful preliminary models for several of the targeted substances; however, our ability to characterize relations between concentrations in moss and loadings for many of the metals was precluded by several factors. The few test sites, small concentration gradients, and generally low concentrations hampered model developments. In addition, the weather was unusually warm throughout Alaska during the winter of 2013–14, which caused intermittent melting of the snowpack at some of the test sites; consequently, our measurements of overwinter loads based on snowpack samples (obtained in late March) probably underestimated the actual loads. Regardless of these potential limitations, these studies have established a foundation to support further studies that can improve our understanding of how mosses accumulate inorganic substances and ultimately how mosses might be used as biomonitors of atmospheric pollutants; moreover, the successful development and validation of the IECs during this research documents how the methodology can be used for future monitoring efforts in remote regions of Alaska and elsewhere.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165096","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Brumbaugh, W.G., Arms, J.W., Linder, G.L., and Melton, V.D., 2016, Development of ion-exchange collectors for monitoring atmospheric deposition of inorganic pollutants in Alaska parklands: U.S. Geological Survey Scientific Investigations Report 2016–5096, 43 p., https://dx.doi.org/10.3133/sir20165096.","productDescription":"Report: ix, 42 p.; Appendixes: 1-3","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072869","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":328418,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5096/sir20165096_appendix_1.pdf","text":"Appendix 1","size":"903 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5096 Appendix 1"},{"id":328416,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5096/sir20165096.pdf","text":"Report","size":"1.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5096"},{"id":328419,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5096/sir20165096_appendix_2.pdf","text":"Appendix 2","size":"136 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5096 Appendix 2"},{"id":328420,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5096/sir20165096_appendix_3.xlsx","text":"Appendix 3","size":"53 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5096 Appendix 3"},{"id":328415,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5096/coverthb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.17510986328125,\n 63.83370500705902\n ],\n [\n -149.17510986328125,\n 63.91956769533998\n ],\n [\n -148.8599395751953,\n 63.91956769533998\n ],\n [\n -148.8599395751953,\n 63.83370500705902\n ],\n [\n -149.17510986328125,\n 63.83370500705902\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.0679931640625,\n 64.55434119440012\n ],\n [\n -149.0679931640625,\n 65.35424113333515\n ],\n [\n -146.53289794921875,\n 65.35424113333515\n ],\n [\n -146.53289794921875,\n 64.55434119440012\n ],\n [\n -149.0679931640625,\n 64.55434119440012\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
A growing number of ungulate populations are living within or near the wildland–urban interface. When resources at the interface are of greater quality than that of adjacent natural habitat, wildlife can be attracted to these developed areas. Little is known about how use of the wildland–urban interface by wildlife may affect vital rates. Under natural conditions, recruitment by desert bighorn sheep (Ovis canadensis nelsoni) correlates with variation in the timing and amount of rainfall that initiates and enhances growth of annual plant species. However, for populations that forage in developed areas, this relationship may become decoupled. In the River Mountains of Nevada, USA, desert bighorn sheep have been feeding in a municipal park at the wildland–urban interface since its establishment in 1985. Approximately one-third of the population now uses the park during summer months when nutritional content of natural forage is low. We hypothesized that use of this municipal area, with its abundant vegetation and water resources, may have decoupled the previous relationship between precipitation and lamb recruitment. We assessed variables known to affect lamb recruitment before (1971–1986) and after (1987–2006) establishment of the park using linear regression models. Our top candidate model for the pre-park period indicated that total November precipitation was the greatest driver of lamb recruitment in this population. After park establishment, this relationship became decoupled because lamb recruitment was no longer driven by weather variables. These results raise questions about the effects of decoupling drivers of population growth and maintaining natural populations near urban areas.
","language":"English","publisher":"Wildlife Society","publisherLocation":"Washington, D.C.","doi":"10.1002/wsb.679","usgsCitation":"Longshore, K.M., Lowrey, C.E., and Cummings, P., 2016, Foraging at the wildland–urban interface decouples weather as a driver of recruitment for desert bighorn sheep: Wildlife Society Bulletin, v. 40, no. 3, p. 494-499, https://doi.org/10.1002/wsb.679.","productDescription":"6 p.","startPage":"494","endPage":"499","ipdsId":"IP-072045","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":500052,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/4ab750e0d2274a96a5325257b601991a","text":"External Repository"},{"id":328690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Lake Mead National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.97707366943358,\n 35.97272720799364\n ],\n [\n -114.97707366943358,\n 36.0410487010891\n ],\n [\n -114.8339080810547,\n 36.0410487010891\n ],\n [\n -114.8339080810547,\n 35.97272720799364\n ],\n [\n -114.97707366943358,\n 35.97272720799364\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-12","publicationStatus":"PW","scienceBaseUri":"57ed48b1e4b090825011d4d5","contributors":{"authors":[{"text":"Longshore, Kathleen M. 0000-0001-6621-1271 longshore@usgs.gov","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":2677,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"longshore@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":648874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowrey, Chris E. 0000-0001-5084-7275 clowrey@usgs.gov","orcid":"https://orcid.org/0000-0001-5084-7275","contributorId":3225,"corporation":false,"usgs":true,"family":"Lowrey","given":"Chris","email":"clowrey@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":648875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cummings, Patrick","contributorId":174650,"corporation":false,"usgs":false,"family":"Cummings","given":"Patrick","email":"","affiliations":[{"id":27489,"text":"Nevada Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":648876,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176475,"text":"70176475 - 2016 - Inter-population differences in salinity tolerance and osmoregulation of juvenile wild and hatchery-born Sacramento splittail","interactions":[],"lastModifiedDate":"2016-09-16T14:59:12","indexId":"70176475","displayToPublicDate":"2016-09-16T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3919,"text":"Conservation Physiology","onlineIssn":"2051-1434","active":true,"publicationSubtype":{"id":10}},"title":"Inter-population differences in salinity tolerance and osmoregulation of juvenile wild and hatchery-born Sacramento splittail","docAbstract":"The Sacramento splittail (Pogonichthys macrolepidotus) is a minnow endemic to the highly modified San Francisco Estuary of California, USA and its associated rivers and tributaries. This species is composed of two genetically distinct populations, which, according to field observations and otolith strontium signatures, show largely allopatric distribution patterns as recently hatched juveniles. Juvenile Central Valley splittail are found primarily in the nearly fresh waters of the Sacramento and San Joaquin rivers and their tributaries, whereas San Pablo juveniles are found in the typically higher-salinity waters (i.e. up to 10‰) of the Napa and Petaluma Rivers. As the large salinity differences between young-of-year habitats may indicate population-specific differences in salinity tolerance, we hypothesized that juvenile San Pablo and Central Valley splittail populations differ in their response to salinity. In hatchery-born and wild-caught juvenile San Pablo splittail, we found upper salinity tolerances, where mortalities occurred within 336 h of exposure to 16‰ or higher, which was higher than the upper salinity tolerance of 14‰ for wild-caught juvenile Central Valley splittail. This, in conjunction with slower recovery of plasma osmolality, but not ion levels, muscle moisture or gill Na+,K+-ATPase activity, in Central Valley relative to San Pablo splittail during osmoregulatory disturbance provides some support for our hypothesis of inter-population variation in salinity tolerance and osmoregulation. The modestly improved salinity tolerance of San Pablo splittail is consistent with its use of higher-salinity habitats. Although confirmation of the putative adaptive difference through further studies is recommended, this may highlight the need for population-specific management considerations.
","language":"English","publisher":"Society for Experimental Biology","publisherLocation":"Oxford","doi":"10.1093/conphys/cov063","usgsCitation":"Verhille, C.E., Dabruzzi, T.F., Cocherell, D.E., Mahardja, B., Feyrer, F.V., Foin, T.C., Baerwald, M.R., and Fangue, N.A., 2016, Inter-population differences in salinity tolerance and osmoregulation of juvenile wild and hatchery-born Sacramento splittail: Conservation Physiology, v. 4, no. 1, 12 p., https://doi.org/10.1093/conphys/cov063.","productDescription":"12 p.","ipdsId":"IP-078718","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":462079,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/cov063","text":"Publisher Index Page"},{"id":328689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7008056640625,\n 37.212831514455964\n ],\n [\n -122.7008056640625,\n 39.80853604144591\n ],\n [\n -120.49255371093749,\n 39.80853604144591\n ],\n [\n -120.49255371093749,\n 37.212831514455964\n ],\n [\n -122.7008056640625,\n 37.212831514455964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-16","publicationStatus":"PW","scienceBaseUri":"57f7c63fe4b0bc0bec09c8a3","contributors":{"authors":[{"text":"Verhille, Christine E.","contributorId":174642,"corporation":false,"usgs":false,"family":"Verhille","given":"Christine","email":"","middleInitial":"E.","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":648877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dabruzzi, Theresa F.","contributorId":174643,"corporation":false,"usgs":false,"family":"Dabruzzi","given":"Theresa","email":"","middleInitial":"F.","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":648878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cocherell, Dennis E.","contributorId":174644,"corporation":false,"usgs":false,"family":"Cocherell","given":"Dennis","email":"","middleInitial":"E.","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":648879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mahardja, Brian","contributorId":174645,"corporation":false,"usgs":false,"family":"Mahardja","given":"Brian","email":"","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":648880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":5901,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":648881,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foin, Theodore C.","contributorId":174646,"corporation":false,"usgs":false,"family":"Foin","given":"Theodore","email":"","middleInitial":"C.","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":648882,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Baerwald, Melinda R.","contributorId":171890,"corporation":false,"usgs":false,"family":"Baerwald","given":"Melinda","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":648868,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fangue, Nann A.","contributorId":152479,"corporation":false,"usgs":false,"family":"Fangue","given":"Nann","email":"","middleInitial":"A.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":648883,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70176456,"text":"70176456 - 2016 - Vegetative response to water availability on the San Carlos Apache Reservation","interactions":[],"lastModifiedDate":"2016-09-14T16:02:53","indexId":"70176456","displayToPublicDate":"2016-09-14T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Vegetative response to water availability on the San Carlos Apache Reservation","docAbstract":"On the San Carlos Apache Reservation in east-central Arizona, U.S.A., vegetation types such as ponderosa pine forests, pinyon-juniper woodlands, and grasslands have significant ecological, cultural, and economic value for the Tribe. This value extends beyond the tribal lands and across the Western United States. Vegetation across the Southwestern United States is susceptible to drought conditions and fluctuating water availability. Remotely sensed vegetation indices can be used to measure and monitor spatial and temporal vegetative response to fluctuating water availability conditions. We used the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived Modified Soil Adjusted Vegetation Index II (MSAVI2) to measure the condition of three dominant vegetation types (ponderosa pine forest, woodland, and grassland) in response to two fluctuating environmental variables: precipitation and the Standardized Precipitation Evapotranspiration Index (SPEI). The study period covered 2002 through 2014 and focused on a region within the San Carlos Apache Reservation. We determined that grassland and woodland had a similar moderate to strong, year-round, positive relationship with precipitation as well as with summer SPEI. This suggests that these vegetation types respond negatively to drought conditions and are more susceptible to initial precipitation deficits. Ponderosa pine forest had a comparatively weaker relationship with monthly precipitation and summer SPEI, indicating that it is more buffered against short-term drought conditions. This research highlights the response of multiple, dominant vegetation types to seasonal and inter-annual water availability. This research demonstrates that multi-temporal remote sensing imagery can be an effective tool for the large scale detection of vegetation response to adverse impacts from climate change and support potential management practices such as increased monitoring and management of drought-affected areas. Different vegetation types displayed various responses to water availability, further highlighting the need for individual management plans for forest and woodland, especially considering the projected drier conditions in the Southwest U.S. and other arid or semi-arid regions around the world.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2016.07.012","usgsCitation":"Petrakis, R., Wu, Z., McVay, J., Middleton, B.R., Dye, D.G., and Vogel, J.M., 2016, Vegetative response to water availability on the San Carlos Apache Reservation: Forest Ecology and Management, v. 378, p. 14-23, https://doi.org/10.1016/j.foreco.2016.07.012.","productDescription":"10 p.","startPage":"14","endPage":"23","ipdsId":"IP-076045","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":462081,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2016.07.012","text":"Publisher Index Page"},{"id":328660,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"San Carlos Apache Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.30,\n 33\n ],\n [\n -110.30,\n 34.0\n ],\n [\n -109.30,\n 34.0\n ],\n [\n -109.30,\n 33\n ],\n [\n -110.30,\n 33\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"378","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57da66a6e4b090824ffb164e","contributors":{"authors":[{"text":"Petrakis, Roy E. 0000-0001-8932-077X rpetrakis@usgs.gov","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":174623,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy","email":"rpetrakis@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":648813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":648812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McVay, Jason jcmcvay@usgs.gov","contributorId":140042,"corporation":false,"usgs":true,"family":"McVay","given":"Jason","email":"jcmcvay@usgs.gov","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":648842,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Middleton, Barry R. 0000-0001-8924-4121 bmiddleton@usgs.gov","orcid":"https://orcid.org/0000-0001-8924-4121","contributorId":3947,"corporation":false,"usgs":true,"family":"Middleton","given":"Barry","email":"bmiddleton@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":648843,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dye, Dennis G. 0000-0002-7100-272X ddye@usgs.gov","orcid":"https://orcid.org/0000-0002-7100-272X","contributorId":4233,"corporation":false,"usgs":true,"family":"Dye","given":"Dennis","email":"ddye@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":648844,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vogel, John M. 0000-0002-8226-1188 jvogel@usgs.gov","orcid":"https://orcid.org/0000-0002-8226-1188","contributorId":3167,"corporation":false,"usgs":true,"family":"Vogel","given":"John","email":"jvogel@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":648845,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176453,"text":"70176453 - 2016 - Prerequisites for understanding climate-change impacts on northern prairie wetlands","interactions":[],"lastModifiedDate":"2017-01-03T16:13:01","indexId":"70176453","displayToPublicDate":"2016-09-14T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Prerequisites for understanding climate-change impacts on northern prairie wetlands","docAbstract":"The Prairie Pothole Region (PPR) contains ecosystems that are typified by an extensive matrix of grasslands and depressional wetlands, which provide numerous ecosystem services. Over the past 150 years the PPR has experienced numerous landscape modifications resulting in agricultural conversion of 75–99 % of native prairie uplands and drainage of 50–90 % of wetlands. There is concern over how and where conservation dollars should be spent within the PPR to protect and restore wetland basins to support waterbird populations that will be robust to a changing climate. However, while hydrological impacts of landscape modifications appear substantial, they are still poorly understood. Previous modeling efforts addressing impacts of climate change on PPR wetlands have yet to fully incorporate interacting or potentially overshadowing impacts of landscape modification. We outlined several information needs for building more informative models to predict climate change effects on PPR wetlands. We reviewed how landscape modification influences wetland hydrology and present a conceptual model to describe how modified wetlands might respond to climate variability. We note that current climate projections do not incorporate cyclical variability in climate between wet and dry periods even though such dynamics have shaped the hydrology and ecology of PPR wetlands. We conclude that there are at least three prerequisite steps to making meaningful predictions about effects of climate change on PPR wetlands. Those evident to us are: 1) an understanding of how physical and watershed characteristics of wetland basins of similar hydroperiods vary across temperature and moisture gradients; 2) a mechanistic understanding of how wetlands respond to climate across a gradient of anthropogenic modifications; and 3) improved climate projections for the PPR that can meaningfully represent potential changes in climate variability including intensity and duration of wet and dry periods. Once these issues are addressed, we contend that modeling efforts will better inform and quantify ecosystem services provided by wetlands to meet needs of waterbird conservation and broader societal interests such as flood control and water quality.","language":"English","publisher":"Springer","doi":"10.1007/s13157-016-0811-2","usgsCitation":"Anteau, M.J., Wiltermuth, M.T., Post van der Burg, M., and Pearse, A.T., 2016, Prerequisites for understanding climate-change impacts on northern prairie wetlands: Wetlands, v. 36, no. s2, p. 299-307, https://doi.org/10.1007/s13157-016-0811-2.","productDescription":"9 p.","startPage":"299","endPage":"307","ipdsId":"IP-073902","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":328661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"s2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-08","publicationStatus":"PW","scienceBaseUri":"57da66a5e4b090824ffb164c","chorus":{"doi":"10.1007/s13157-016-0811-2","url":"http://dx.doi.org/10.1007/s13157-016-0811-2","publisher":"Springer Nature","authors":"Anteau Michael J., Wiltermuth Mark T., van der Burg Max Post, Pearse Aaron T.","journalName":"Wetlands","publicationDate":"9/8/2016","auditedOn":"2/15/2017","publiclyAccessibleDate":"9/8/2016"},"contributors":{"authors":[{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":648803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiltermuth, Mark T. 0000-0002-8871-2816 mwiltermuth@usgs.gov","orcid":"https://orcid.org/0000-0002-8871-2816","contributorId":708,"corporation":false,"usgs":true,"family":"Wiltermuth","given":"Mark","email":"mwiltermuth@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":648804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":648805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":648806,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176448,"text":"ofr20161159 - 2016 - Water temperature effects from simulated dam operations and structures in the Middle Fork Willamette River, western Oregon","interactions":[],"lastModifiedDate":"2016-09-15T08:09:53","indexId":"ofr20161159","displayToPublicDate":"2016-09-14T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1159","title":"Water temperature effects from simulated dam operations and structures in the Middle Fork Willamette River, western Oregon","docAbstract":"Streamflow and water temperature in the Middle Fork Willamette River (MFWR), western Oregon, have been regulated and altered since the construction of Lookout Point, Dexter, and Hills Creek Dams in 1954 and 1961, respectively. Each year, summer releases from the dams typically are cooler than pre-dam conditions, with the reverse (warmer than pre-dam conditions) occurring in autumn. This pattern has been detrimental to habitat of endangered Upper Willamette River (UWR) Chinook salmon (Oncorhynchus tshawytscha) and UWR winter steelhead (O. mykiss) throughout multiple life stages. In this study, scenarios testing different dam-operation strategies and hypothetical dam-outlet structures were simulated using CE-QUAL-W2 hydrodynamic/temperature models of the MFWR system from Hills Creek Lake (HCR) to Lookout Point (LOP) and Dexter (DEX) Lakes to explore and understand the efficacy of potential flow and temperature mitigation options.
Model scenarios were run in constructed wet, normal, and dry hydrologic calendar years, and designed to minimize the effects of Hills Creek and Lookout Point Dams on river temperature by prioritizing warmer lake surface releases in May–August and cooler, deep releases in September–December. Operational scenarios consisted of a range of modified release rate rules, relaxation of power-generation constraints, variations in the timing of refill and drawdown, and maintenance of different summer maximum lake levels at HCR and LOP. Structural scenarios included various combinations of hypothetical floating outlets near the lake surface and hypothetical new outlets at depth. Scenario results were compared to scenarios using existing operational rules that give temperature management some priority (Base), scenarios using pre-2012 operational rules that prioritized power generation over temperature management (NoBlend), and estimated temperatures from a without-dams condition (WoDams).
Results of the tested model scenarios led to the following conclusions:
Director, Oregon Water Science Center
U.S. Geological Survey
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Portland, Oregon 97201
http://or.water.usgs.gov