A new disturbance automated reference toolset (DART) was developed to monitor human land surface impacts using soil-type and ecological context. DART identifies reference areas with similar soils, topography, and geology; and compares the disturbance condition to the reference area condition using a quantile-based approach based on a satellite vegetation index. DART was able to represent 26–55% of variation of relative differences in bare ground and 26–41% of variation in total foliar cover when comparing sites with nearby ecological reference areas using the Soil Adjusted Total Vegetation Index (SATVI). Assessment of ecological recovery at oil and gas pads on the Colorado Plateau with DART revealed that more than half of well-pads were below the 25th percentile of reference areas. Machine learning trend analysis of poorly recovering well-pads (quantile < 0.23) had out-of-bag error rates between 37 and 40% indicating moderate association with environmental and management variables hypothesized to influence recovery. Well-pads in grasslands (median quantile [MQ] = 13%), blackbrush (Coleogyne ramosissima) shrublands (MQ = 18%), arid canyon complexes (MQ = 18%), warmer areas with more summer-dominated precipitation, and state administered areas (MQ = 12%) had low recovery rates. Results showcase the usefulness of DART for assessing discrete surface land disturbances, and highlight the need for more targeted rehabilitation efforts at oil and gas well-pads in the arid southwest US.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.01.034","usgsCitation":"Nauman, T.W., Duniway, M.C., Villarreal, M.L., and Poitras, T.B., 2017, Disturbance automated reference toolset (DART): Assessing patterns in ecological recovery from energy development on the Colorado Plateau: Science of the Total Environment, v. 584-585, p. 476-488, https://doi.org/10.1016/j.scitotenv.2017.01.034.","productDescription":"13 p.","startPage":"476","endPage":"488","ipdsId":"IP-077123","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469920,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2017.01.034","text":"Publisher Index Page"},{"id":344368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado Plateau","volume":"584-585","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5979aa55e4b0ec1a488b8c09","contributors":{"authors":[{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":706444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":706445,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":706446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poitras, Travis B. 0000-0001-8677-1743 tpoitras@usgs.gov","orcid":"https://orcid.org/0000-0001-8677-1743","contributorId":195168,"corporation":false,"usgs":true,"family":"Poitras","given":"Travis","email":"tpoitras@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":706447,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186776,"text":"ofr20171026 - 2017 - Potential effects of existing and proposed groundwater withdrawals on water levels and natural groundwater discharge in Snake Valley and surrounding areas, Utah and Nevada","interactions":[],"lastModifiedDate":"2017-04-17T15:35:48","indexId":"ofr20171026","displayToPublicDate":"2017-04-14T00:00:00","publicationYear":"2017","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":"2017-1026","title":"Potential effects of existing and proposed groundwater withdrawals on water levels and natural groundwater discharge in Snake Valley and surrounding areas, Utah and Nevada","docAbstract":"Several U.S. Department of Interior (DOI) agencies are concerned about the cumulative effects of groundwater development on groundwater resources managed by, and other groundwater resources of interest to, these agencies in Snake Valley and surrounding areas. The new water uses that potentially concern the DOI agencies include 12 water-right applications filed in 2005, totaling approximately 8,864 acre-feet per year. To date, only one of these applications has been approved and partially developed. In addition, the DOI agencies are interested in the potential effects of three new water-right applications (UT 18-756, UT 18-758, and UT 18-759) and one water-right change application (UT a40687), which were the subject of a water-right hearing on April 19, 2016.
This report presents a hydrogeologic analysis of areas in and around Snake Valley to assess potential effects of existing and future groundwater development on groundwater resources, specifically groundwater discharge sites, of interest to the DOI agencies. A previously developed steady-state numerical groundwater-flow model was modified to transient conditions with respect to well withdrawals and used to quantify drawdown and capture (withdrawals that result in depletion) of natural discharge from existing and proposed groundwater withdrawals. The original steady-state model simulates and was calibrated to 2009 conditions. To investigate the potential effects of existing and proposed groundwater withdrawals on the groundwater resources of interest to the DOI agencies, 10 withdrawal scenarios were simulated. All scenarios were simulated for periods of 5, 10, 15, 30, 55, and 105 years from the start of 2010; additionally, all scenarios were simulated to a new steady state to determine the ultimate long-term effects of the withdrawals. Capture maps were also constructed as part of this analysis. The simulations used to develop the capture maps test the response of the system, specifically the reduction of natural discharge, to future stresses at a point in the area represented by the model. In this way, these maps can be used as a tool to determine the source of water to, and potential effects at specific areas from, future well withdrawals.
Downward trends in water levels measured in wells indicate that existing groundwater withdrawals in Snake Valley are affecting water levels. The numerical model simulates similar downward trends in water levels; simulated drawdowns in the model, however, are generally less than observed water-level declines. At the groundwater discharge sites of interest to the DOI agencies, simulated drawdowns from existing well withdrawals (projected into the future) range from 0 to about 50 feet. Following the addition of the proposed withdrawals, simulated drawdowns at some sites increase by 25 feet. Simulated drawdown resulting from the proposed withdrawals began in as few as 5 years after 2014 at several of the sites. At the groundwater discharge sites of interest to the DOI agencies, simulated capture of natural discharge resulting from the existing withdrawals ranged from 0 to 87 percent. Following the addition of the proposed withdrawals, simulated capture at several of the sites reached 100 percent, indicating that groundwater discharge at that site would cease. Simulated capture following the addition of the proposed withdrawals increased in as few as 5 years after 2014 at several of the sites.
Director, Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, UT 84119-2047
801 908-5000
http://ut.water.usgs.gov/
Stable isotopes encode and integrate the origin of matter; thus, their analysis offers tremendous potential to address questions across diverse scientific disciplines (1, 2). Indeed, the broad applicability of stable isotopes, coupled with advancements in high-throughput analysis, have created a scientific field that is growing exponentially, and generating data at a rate paralleling the explosive rise of DNA sequencing and genomics (3). Centralized data repositories, such as GenBank, have become increasingly important as a means for archiving information, and “Big Data” analytics of these resources are revolutionizing science and everyday life.
","language":"English","publisher":"PNAS","doi":"10.1073/pnas.1701742114","usgsCitation":"Pauli, J.N., Newsome, S.D., Cook, J.A., Harrod, C., Steffan, S.A., Baker, C., Ben-David, M., Bloom, D., Bowen, G.J., Cerling, T.E., Cicero, C., Cook, C., Dohm, M., Dharampal, P.S., Graves, G., Gropp, R., Hobson, K.A., Jordan, C., MacFadden, B., Pilaar Birch, S., Poelen, J., Ratnasingham, S., Russell, L., Stricker, C.A., Uhen, M.D., Yarnes, C.T., and Hayden, B., 2017, Opinion: Why we need a centralized repository for isotopic data: Proceedings of the National Academy of Sciences of the United States of America, v. 114, no. 12, p. 2997-3001, https://doi.org/10.1073/pnas.1701742114.","productDescription":"5 p.","startPage":"2997","endPage":"3001","ipdsId":"IP-081710","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469923,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1701742114","text":"Publisher Index Page"},{"id":339749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"114","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-21","publicationStatus":"PW","scienceBaseUri":"58f1e0c6e4b08144348b7ddc","contributors":{"authors":[{"text":"Pauli, Jonathan N.","contributorId":190897,"corporation":false,"usgs":false,"family":"Pauli","given":"Jonathan","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":691033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newsome, Seth D.","contributorId":81640,"corporation":false,"usgs":false,"family":"Newsome","given":"Seth","email":"","middleInitial":"D.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":691034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cook, Joseph A.","contributorId":8323,"corporation":false,"usgs":false,"family":"Cook","given":"Joseph","email":"","middleInitial":"A.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":691035,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harrod, Chris","contributorId":190898,"corporation":false,"usgs":false,"family":"Harrod","given":"Chris","email":"","affiliations":[],"preferred":false,"id":691036,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Steffan, Shawn A.","contributorId":190899,"corporation":false,"usgs":false,"family":"Steffan","given":"Shawn","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":691037,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baker, Christopher J. O.","contributorId":190900,"corporation":false,"usgs":false,"family":"Baker","given":"Christopher J. O.","affiliations":[],"preferred":false,"id":691038,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ben-David, Merav","contributorId":190901,"corporation":false,"usgs":false,"family":"Ben-David","given":"Merav","email":"","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":691039,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bloom, David","contributorId":190902,"corporation":false,"usgs":false,"family":"Bloom","given":"David","email":"","affiliations":[],"preferred":false,"id":691040,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bowen, Gabriel J.","contributorId":138889,"corporation":false,"usgs":false,"family":"Bowen","given":"Gabriel","email":"","middleInitial":"J.","affiliations":[{"id":12566,"text":"Department of Geology and Geophysics, Unviersity of Utah","active":true,"usgs":false}],"preferred":false,"id":691041,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cerling, Thure E.","contributorId":22822,"corporation":false,"usgs":true,"family":"Cerling","given":"Thure","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":691042,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cicero, Carla","contributorId":145565,"corporation":false,"usgs":false,"family":"Cicero","given":"Carla","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":691043,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Cook, Craig","contributorId":190904,"corporation":false,"usgs":false,"family":"Cook","given":"Craig","email":"","affiliations":[],"preferred":false,"id":691044,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dohm, Michelle","contributorId":190905,"corporation":false,"usgs":false,"family":"Dohm","given":"Michelle","email":"","affiliations":[],"preferred":false,"id":691045,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Dharampal, Prarthana S.","contributorId":190906,"corporation":false,"usgs":false,"family":"Dharampal","given":"Prarthana","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":691046,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Graves, Gary","contributorId":190907,"corporation":false,"usgs":false,"family":"Graves","given":"Gary","affiliations":[],"preferred":false,"id":691047,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Gropp, Robert","contributorId":190908,"corporation":false,"usgs":false,"family":"Gropp","given":"Robert","email":"","affiliations":[],"preferred":false,"id":691048,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Hobson, Keith A.","contributorId":190909,"corporation":false,"usgs":false,"family":"Hobson","given":"Keith","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":691049,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Jordan, Chris","contributorId":190910,"corporation":false,"usgs":false,"family":"Jordan","given":"Chris","affiliations":[],"preferred":false,"id":691050,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"MacFadden, Bruce","contributorId":190911,"corporation":false,"usgs":false,"family":"MacFadden","given":"Bruce","email":"","affiliations":[],"preferred":false,"id":691051,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Pilaar Birch, Suzanne","contributorId":190912,"corporation":false,"usgs":false,"family":"Pilaar Birch","given":"Suzanne","affiliations":[],"preferred":false,"id":691052,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Poelen, Jorrit","contributorId":190913,"corporation":false,"usgs":false,"family":"Poelen","given":"Jorrit","email":"","affiliations":[],"preferred":false,"id":691053,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Ratnasingham, Sujeevan","contributorId":190914,"corporation":false,"usgs":false,"family":"Ratnasingham","given":"Sujeevan","email":"","affiliations":[],"preferred":false,"id":691054,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Russell, Laura","contributorId":190915,"corporation":false,"usgs":false,"family":"Russell","given":"Laura","email":"","affiliations":[],"preferred":false,"id":691055,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":691032,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Uhen, Mark D.","contributorId":171936,"corporation":false,"usgs":false,"family":"Uhen","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":691056,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Yarnes, Christopher T.","contributorId":190916,"corporation":false,"usgs":false,"family":"Yarnes","given":"Christopher","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":691057,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Hayden, Brian","contributorId":190917,"corporation":false,"usgs":false,"family":"Hayden","given":"Brian","email":"","affiliations":[],"preferred":false,"id":691058,"contributorType":{"id":1,"text":"Authors"},"rank":27}]}} ,{"id":70186921,"text":"70186921 - 2017 - The effects of drought and fire in the extirpation of an abundant semi-aquatic turtle from a lacustrine environment in the southwestern USA","interactions":[],"lastModifiedDate":"2017-04-14T13:02:13","indexId":"70186921","displayToPublicDate":"2017-04-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2585,"text":"Knowledge and Management of Aquatic Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"The effects of drought and fire in the extirpation of an abundant semi-aquatic turtle from a lacustrine environment in the southwestern USA","docAbstract":"We documented a significant mortality event affecting a southwestern pond turtle (Actinemys pallida) population living in a lake in southern California, USA. The area around the lake was impacted by a large wildland fire in 2013 that occurred during a protracted drought. As the mortality event was still unfolding, we collected data in 2014 on water quality, demographic structure, and short-term survivorship of the population. Water quality was poor with low levels of dissolved oxygen and high salinity of up to 45.90 ppt. Many turtles were severely emaciated and coated with a pale mineralized layer on their shells and skin. Estimated survival rate was low leading to a projected 90% decline in 134 days and a high probability of extirpation within a year. The lake was dry in September 2015 with no evidence of live turtles. Necropsies and low volumetric body condition indices suggested death by starvation. Although this semi-aquatic species has the ability to aestivate in upland habitats during periods of low water or move to other nearby water bodies, it is unlikely that many were able to do so because of their extremely poor condition and the severity of the drought conditions throughout the area.
","language":"English","publisher":"EDP Sciences","doi":"10.1051/kmae/2017008","usgsCitation":"Lovich, J.E., Quillman, M., Zitt, B., Schroeder, A., Green, D.E., Yackulic, C.B., Gibbons, P., and Goode, E., 2017, The effects of drought and fire in the extirpation of an abundant semi-aquatic turtle from a lacustrine environment in the southwestern USA: Knowledge and Management of Aquatic Ecosystems, v. 418, p. 1-11, https://doi.org/10.1051/kmae/2017008.","productDescription":"Article number 18; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-071578","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":461639,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1051/kmae/2017008","text":"Publisher Index Page"},{"id":438371,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FN154F","text":"USGS data release","linkHelpText":"Southern Pacific Pond Turtle Data, Elizabeth Lake, Los Angeles County, California, USA"},{"id":339735,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"418","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-10","publicationStatus":"PW","scienceBaseUri":"58f1e0c7e4b08144348b7de5","contributors":{"authors":[{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":691001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quillman, Mari","contributorId":190889,"corporation":false,"usgs":false,"family":"Quillman","given":"Mari","email":"","affiliations":[],"preferred":false,"id":691002,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zitt, Brian","contributorId":190890,"corporation":false,"usgs":false,"family":"Zitt","given":"Brian","email":"","affiliations":[],"preferred":false,"id":691003,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schroeder, Adam","contributorId":190891,"corporation":false,"usgs":false,"family":"Schroeder","given":"Adam","email":"","affiliations":[],"preferred":false,"id":691004,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Green, David E. 0000-0002-7663-1832 degreen@usgs.gov","orcid":"https://orcid.org/0000-0002-7663-1832","contributorId":3715,"corporation":false,"usgs":true,"family":"Green","given":"David","email":"degreen@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":691005,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":691006,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gibbons, Paul","contributorId":190892,"corporation":false,"usgs":false,"family":"Gibbons","given":"Paul","affiliations":[],"preferred":false,"id":691007,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goode, Eric","contributorId":190893,"corporation":false,"usgs":false,"family":"Goode","given":"Eric","email":"","affiliations":[],"preferred":false,"id":691008,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70186910,"text":"70186910 - 2017 - Community disruptions and business costs for distant tsunami evacuations using maximum versus scenario-based zones","interactions":[],"lastModifiedDate":"2017-04-14T09:27:18","indexId":"70186910","displayToPublicDate":"2017-04-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Community disruptions and business costs for distant tsunami evacuations using maximum versus scenario-based zones","docAbstract":"Well-executed evacuations are key to minimizing loss of life from tsunamis, yet they also disrupt communities and business productivity in the process. Most coastal communities implement evacuations based on a previously delineated maximum-inundation zone that integrates zones from multiple tsunami sources. To support consistent evacuation planning that protects lives but attempts to minimize community disruptions, we explore the implications of scenario-based evacuation procedures and use the California (USA) coastline as our case study. We focus on the land in coastal communities that is in maximum-evacuation zones, but is not expected to be flooded by a tsunami generated by a Chilean earthquake scenario. Results suggest that a scenario-based evacuation could greatly reduce the number of residents and employees that would be advised to evacuate for 24–36 h (178,646 and 159,271 fewer individuals, respectively) and these reductions are concentrated primarily in three counties for this scenario. Private evacuation spending is estimated to be greater than public expenditures for operating shelters in the area of potential over-evacuations ($13 million compared to $1 million for a 1.5-day evacuation). Short-term disruption costs for businesses in the area of potential over-evacuation are approximately $122 million for a 1.5-day evacuation, with one-third of this cost associated with manufacturing, suggesting that some disruption costs may be recouped over time with increased short-term production. There are many businesses and organizations in this area that contain individuals with limited mobility or access and functional needs that may have substantial evacuation challenges. This study demonstrates and discusses the difficulties of tsunami-evacuation decision-making for relatively small to moderate events faced by emergency managers, not only in California but in coastal communities throughout the world.
","language":"English","publisher":"Springer","doi":"10.1007/s11069-016-2709-y","usgsCitation":"Wood, N.J., Wilson, R.I., Ratliff, J.L., Peters, J., MacMullan, E., Krebs, T., Shoaf, K., and Miller, K., 2017, Community disruptions and business costs for distant tsunami evacuations using maximum versus scenario-based zones: Natural Hazards, v. 86, no. 2, p. 619-643, https://doi.org/10.1007/s11069-016-2709-y.","productDescription":"25 p.","startPage":"619","endPage":"643","ipdsId":"IP-076947","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469922,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1007/s11069-016-2709-y","text":"External Repository"},{"id":339725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-16","publicationStatus":"PW","scienceBaseUri":"58f1e0c8e4b08144348b7de9","contributors":{"authors":[{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":690972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Rick I.","contributorId":56138,"corporation":false,"usgs":false,"family":"Wilson","given":"Rick","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":690973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ratliff, Jamie L. 0000-0002-9967-3314 jratliff@usgs.gov","orcid":"https://orcid.org/0000-0002-9967-3314","contributorId":665,"corporation":false,"usgs":true,"family":"Ratliff","given":"Jamie","email":"jratliff@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":690974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peters, Jeff 0000-0003-4312-0590 jpeters@usgs.gov","orcid":"https://orcid.org/0000-0003-4312-0590","contributorId":4711,"corporation":false,"usgs":true,"family":"Peters","given":"Jeff","email":"jpeters@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":690975,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"MacMullan, Ed","contributorId":190879,"corporation":false,"usgs":false,"family":"MacMullan","given":"Ed","email":"","affiliations":[],"preferred":false,"id":690976,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Krebs, Tessa","contributorId":190880,"corporation":false,"usgs":false,"family":"Krebs","given":"Tessa","email":"","affiliations":[],"preferred":false,"id":690977,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shoaf, Kimberley","contributorId":190881,"corporation":false,"usgs":false,"family":"Shoaf","given":"Kimberley","email":"","affiliations":[],"preferred":false,"id":690978,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Kevin","contributorId":178815,"corporation":false,"usgs":false,"family":"Miller","given":"Kevin","affiliations":[],"preferred":false,"id":690979,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70186759,"text":"sir20175024 - 2017 - Developing flood-inundation maps for Johnson Creek, Portland, Oregon","interactions":[],"lastModifiedDate":"2017-04-20T11:18:36","indexId":"sir20175024","displayToPublicDate":"2017-04-14T00:00:00","publicationYear":"2017","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":"2017-5024","title":"Developing flood-inundation maps for Johnson Creek, Portland, Oregon","docAbstract":"Digital flood-inundation maps were created for a 12.9‑mile reach of Johnson Creek by the U.S. Geological Survey (USGS). The flood-inundation maps depict estimates of water depth and areal extent of flooding from the mouth of Johnson Creek to just upstream of Southeast 174th Avenue in Portland, Oregon. Each flood-inundation map is based on a specific water level and associated streamflow at the USGS streamgage, Johnson Creek at Sycamore, Oregon (14211500), which is located near the upstream boundary of the maps. The maps produced by the USGS, and the forecasted flood hydrographs produced by National Weather Service River Forecast Center can be accessed through the USGS Flood Inundation Mapper Web site (http://wimcloud.usgs.gov/apps/FIM/FloodInundationMapper.html).
Water-surface elevations were computed for Johnson Creek using a combined one-dimensional and two‑dimensional unsteady hydraulic flow model. The model was calibrated using data collected from the flood of December 2015 (including the calculated streamflows at two USGS streamgages on Johnson Creek) and validated with data from the flood of January 2009. Results were typically within 0.6 foot (ft) of recorded or measured water-surface elevations from the December 2015 flood, and within 0.8 ft from the January 2009 flood. Output from the hydraulic model was used to create eight flood inundation maps ranging in stage from 9 to 16 ft. Boundary condition hydrographs were identical in shape to those from the December 2015 flood event, but were scaled up or down to produce the amount of streamflow corresponding to a specific water-surface elevation at the Sycamore streamgage (14211500). Sensitivity analyses using other hydrograph shapes, and a version of the model in which the peak flow is maintained for an extended period of time, showed minimal variation, except for overbank areas near the Foster Floodplain Natural Area.
Simulated water-surface profiles were combined with light detection and ranging (lidar) data collected in 2014 to delineate water-surface extents for each of the eight modeled stages. The availability of flood-inundation maps in conjunction with real-time data from the USGS streamgages along Johnson Creek and forecasted hydrographs from the National Weather Service Northwest River Forecast Center will provide residents of the watershed and emergency management personnel with valuable information that may aid in flood response, including potential evacuations, road closures, and mitigation efforts. In addition, these maps may be used for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175024","collaboration":"Prepared in cooperation with the City of Portland Bureau of Environmental Services","usgsCitation":"Stonewall, A.J., and Beal, B.A., 2017, Developing flood-Inundation maps for Johnson Creek, Portland, Oregon: U.S. Geological Survey Scientific Investigations Report 2017–5024, 26 p., https://doi.org/10.3133/sir20175024.","productDescription":"v, 26 p.","onlineOnly":"Y","ipdsId":"IP-080503","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":339976,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75X273G","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood inundation mapping data for Johnson Creek near Sycamore, Oregon"},{"id":339738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5024/coverthb.jpg"},{"id":339739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5024/sir20175024.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5024"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Johnson Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.655556,\n 45.506944\n ],\n [\n -122.472222,\n 45.506944\n ],\n [\n -122.472222,\n 45.408333\n ],\n [\n -122.655556,\n 45.408333\n ],\n [\n -122.655556,\n 45.506944\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
Carbon dioxide (CO2) emissions from rivers and other inland waters are thought to be a major component of regional and global carbon cycling. In large managed rivers such as the Columbia River, contemporary ecosystem changes such as damming, nutrient enrichment, and increased water residence times may lead to reduced CO2 concentrations (and emissions) due to increased primary production, as has been shown in another large North American river (Upper Mississippi). In this work, spatial patterns of water quality, including dissolved CO2 concentrations, were assessed in the Lower Columbia River (LCR) and major tributaries using underway measurements from a small research vessel during July 2016. We observed near-equilibrium CO2 conditions and overall weak supersaturation of CO2 in the main channel (average 133.8% saturation) and tributaries. We observed only weak correlations between CO2 saturation, chlorophyll a fluorescence, and turbidity, thus not strongly supporting our hypothesis of primary productivity controls. In general, the LCR was clear (low turbidity, mean = 1.48 FNU) and had low chlorophyll fluorescence (mean = 0.177 RFU) during the sampling period. As a whole, the LCR was homogeneous with respect to biogeochemical conditions and showed low spatial variability at >100 km scales. Overall, we find that the LCR is likely a weak summertime source of CO2 to the atmosphere, in line with findings from other altered rivers such as the Upper Mississippi.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/20442041.2017.1366487","usgsCitation":"Crawford, J.T., Butman, D., Loken, L.C., Stadler, P., Catherine Kuhn, and Striegl, R.G., 2017, Spatial variability of CO2 concentrations and biogeochemistry in the Lower Columbia River: Inland Waters, v. 7, no. 4, p. 417-427, https://doi.org/10.1080/20442041.2017.1366487.","productDescription":"11 p.","startPage":"417","endPage":"427","ipdsId":"IP-085407","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":361274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Columbia River","volume":"7","issue":"4","noUsgsAuthors":false,"publicationDate":"2017-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Crawford, John T. 0000-0003-4440-6945 jtcrawford@usgs.gov","orcid":"https://orcid.org/0000-0003-4440-6945","contributorId":4081,"corporation":false,"usgs":true,"family":"Crawford","given":"John","email":"jtcrawford@usgs.gov","middleInitial":"T.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":757324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Butman, David 0000-0003-3520-7426 dbutman@usgs.gov","orcid":"https://orcid.org/0000-0003-3520-7426","contributorId":174187,"corporation":false,"usgs":true,"family":"Butman","given":"David","email":"dbutman@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":757439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757325,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stadler, Philipp","contributorId":195601,"corporation":false,"usgs":false,"family":"Stadler","given":"Philipp","email":"","affiliations":[],"preferred":false,"id":757440,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Catherine Kuhn","contributorId":195602,"corporation":false,"usgs":false,"family":"Catherine Kuhn","affiliations":[],"preferred":false,"id":757441,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":757331,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70184202,"text":"fs20173016 - 2017 - Assessment of undiscovered oil and gas resources in the Haynesville Formation, U.S. Gulf Coast, 2016","interactions":[],"lastModifiedDate":"2018-02-15T14:56:33","indexId":"fs20173016","displayToPublicDate":"2017-04-13T09:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3016","title":"Assessment of undiscovered oil and gas resources in the Haynesville Formation, U.S. Gulf Coast, 2016","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 1.1 billion barrels of conventional oil and 195.8 trillion cubic feet of gas in the Upper Jurassic Haynesville Formation in onshore lands and State waters of the U.S. Gulf Coast region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173016","usgsCitation":"Paxton, S.T., Pitman, J.K., Kinney, S.A., Gianoutsos, N.J., Pearson, O.N., Whidden, K.J., Dubiel, R.F., Schenk, C.J., Burke, L.A., Klett, T.R., Leathers-Miller, H.M., Mercier, T.J., Haines, S.S., Varela, B.A., Le, P.A., Finn, T.M., Gaswirth, S.B., Hawkins, S.J., Marra, K.R., and Tennyson, M.E., 2017, Assessment of undiscovered oil and gas resources in the Haynesville Formation, U.S. Gulf Coast, 2016: U.S. Geological Survey Fact Sheet 2017–3016, 2 p., https://doi.org/10.3133/fs20173016.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-081350","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":438373,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DN439P","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Gulf Coast Mesozoic Province, Haynesville Formation Assessment Units"},{"id":339615,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20173015","text":"Fact Sheet 2017–3015","linkHelpText":"Assessment of undiscovered oil and gas resources in the Bossier Formation, U.S. Gulf Coast, 2016"},{"id":338414,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3016/coverthb2.jpg"},{"id":338415,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3016/fs20173016.pdf","text":"Report","size":"712 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3016"}],"country":"United States","state":"Alabama, Arkansas, Florida, Louisiana, Mississippi, Oklahoma, Texas","otherGeospatial":"Gulf Coast, Haynesville Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102,\n 25\n ],\n [\n -84,\n 25\n ],\n [\n -84,\n 35\n ],\n [\n -102,\n 35\n ],\n [\n -102,\n 25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 2.9 billion barrels of conventional oil and 108.6 trillion cubic feet of natural gas in the Upper Jurassic Bossier Formation in onshore lands and State waters of the U.S. Gulf Coast region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173015","usgsCitation":"Paxton, S.T., Pitman, J.K., Kinney, S.A., Gianoutsos, N.J., Pearson, O.N., Whidden, K.J., Dubiel, R.F., Schenk, C.J., Burke, L.A., Klett, T.R., Leathers-Miller, H.M., Mercier, T.J., Haines, S.S., Varela, B.A., Le, P.A., Finn, T.M., Gaswirth, S.B., Hawkins, S.J., Marra, K.R., and Tennyson, M.E., 2017, Assessment of undiscovered oil and gas resources in the Bossier Formation, U.S. Gulf Coast, 2016: U.S. Geological Survey Fact Sheet 2017–3015, 2 p., https://doi.org/10.3133/fs20173015.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-081349","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":438372,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7707ZP0","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Gulf Coast Mesozoic Province, Bossier Formation Assessment Units"},{"id":339614,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20173016","text":"Fact Sheet 2017-3016","linkHelpText":"- Assessment of undiscovered oil and gas resources in the Haynesville Formation, U.S. Gulf Coast, 2016"},{"id":338407,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3015/coverthb2.jpg"},{"id":338408,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3015/fs20173015.pdf","text":"Report","size":"648 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3015"}],"country":"United States","state":"Alabama, Arkansas, Florida, Louisiana, Mississippi, Oklahoma, Texas","otherGeospatial":"Gulf Coast, Upper Jurassic Bossier Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102,\n 25\n ],\n [\n -84,\n 25\n ],\n [\n -84,\n 35\n ],\n [\n -102,\n 35\n ],\n [\n -102,\n 25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
Evidence indicates that competition with invasive barred owls (Strix varia) is causing rapid declines in populations of northern spotted owls (S. occidentalis caurina), and that the long-term persistence of spotted owls may be in question without additional management intervention. A pilot study in California showed that removal of barred owls in combination with habitat conservation may be able to slow or even reverse population declines of spotted owls at local scales, but it remains unknown whether similar results can be obtained in areas with different forest conditions and a greater density of barred owls. In 2015, we implemented a before-after-control-impact (BACI) experimental design on three study areas in Oregon and Washington with at least 20 years of pre-treatment demographic data on spotted owls to determine if removal of barred owls can improve localized population trends of spotted owls. Here, we report on research accomplishments and preliminary results from the first 21 months (March 2015–December 2016) of the planned 5-year experiment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171040","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service, Bureau of Land Management, and U.S. Forest Service","usgsCitation":"Wiens, J.D., Dugger, K.M., Lewicki, K.E., and Simon, D.C., 2017, Effects of experimental removal of barred owls on population demography of northern spotted owls in Washington and Oregon—2016 progress report: U.S. Geological Survey Open-File Report 2017-1040, 23 p., https://doi.org/10.3133/ofr20171040.","productDescription":"iv, 23 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-084885","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":339711,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1040/coverthb.jpg"},{"id":339712,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1040/ofr20171040.pdf","text":"Report","size":"5.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1040"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.94775390625,\n 42.4234565179383\n ],\n [\n -120.10253906249999,\n 42.4234565179383\n ],\n [\n -120.10253906249999,\n 47.945786463687185\n ],\n [\n -123.94775390625,\n 47.945786463687185\n ],\n [\n -123.94775390625,\n 42.4234565179383\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
Clouds are a pervasive and unavoidable issue in satellite-borne optical imagery. Accurate, well-documented, and automated cloud detection algorithms are necessary to effectively leverage large collections of remotely sensed data. The Landsat project is uniquely suited for comparative validation of cloud assessment algorithms because the modular architecture of the Landsat ground system allows for quick evaluation of new code, and because Landsat has the most comprehensive manual truth masks of any current satellite data archive. Currently, the Landsat Level-1 Product Generation System (LPGS) uses separate algorithms for determining clouds, cirrus clouds, and snow and/or ice probability on a per-pixel basis. With more bands onboard the Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) satellite, and a greater number of cloud masking algorithms, the U.S. Geological Survey (USGS) is replacing the current cloud masking workflow with a more robust algorithm that is capable of working across multiple Landsat sensors with minimal modification. Because of the inherent error from stray light and intermittent data availability of TIRS, these algorithms need to operate both with and without thermal data. In this study, we created a workflow to evaluate cloud and cloud shadow masking algorithms using cloud validation masks manually derived from both Landsat 7 Enhanced Thematic Mapper Plus (ETM +) and Landsat 8 OLI/TIRS data. We created a new validation dataset consisting of 96 Landsat 8 scenes, representing different biomes and proportions of cloud cover. We evaluated algorithm performance by overall accuracy, omission error, and commission error for both cloud and cloud shadow. We found that CFMask, C code based on the Function of Mask (Fmask) algorithm, and its confidence bands have the best overall accuracy among the many algorithms tested using our validation data. The Artificial Thermal-Automated Cloud Cover Algorithm (AT-ACCA) is the most accurate nonthermal-based algorithm. We give preference to CFMask for operational cloud and cloud shadow detection, as it is derived from a priori knowledge of physical phenomena and is operable without geographic restriction, making it useful for current and future land imaging missions without having to be retrained in a machine-learning environment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2017.03.026","usgsCitation":"Foga, S.C., Scaramuzza, P., Guo, S., Zhu, Z., Dilley, R., Beckmann, T., Schmidt, G.L., Dwyer, J.L., Hughes, M., and Laue, B., 2017, Cloud detection algorithm comparison and validation for operational Landsat data products: Remote Sensing of Environment, v. 194, p. 379-390, https://doi.org/10.1016/j.rse.2017.03.026.","productDescription":"12 p.","startPage":"379","endPage":"390","ipdsId":"IP-076780","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":469926,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2017.03.026","text":"Publisher Index Page"},{"id":339659,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"194","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f08e5ee4b06911a29fa842","contributors":{"authors":[{"text":"Foga, Steven Curtis 0000-0003-1835-1987 sfoga@usgs.gov","orcid":"https://orcid.org/0000-0003-1835-1987","contributorId":5703,"corporation":false,"usgs":true,"family":"Foga","given":"Steven","email":"sfoga@usgs.gov","middleInitial":"Curtis","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":690805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scaramuzza, Pat 0000-0002-2616-8456 pscar@usgs.gov","orcid":"https://orcid.org/0000-0002-2616-8456","contributorId":3970,"corporation":false,"usgs":true,"family":"Scaramuzza","given":"Pat","email":"pscar@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":690806,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guo, Song 0000-0001-8823-188X sguo@usgs.gov","orcid":"https://orcid.org/0000-0001-8823-188X","contributorId":5245,"corporation":false,"usgs":true,"family":"Guo","given":"Song","email":"sguo@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":690807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhe 0000-0001-8283-6407","orcid":"https://orcid.org/0000-0001-8283-6407","contributorId":190828,"corporation":false,"usgs":false,"family":"Zhu","given":"Zhe","affiliations":[],"preferred":false,"id":690808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dilley, Ronald 0000-0002-6960-1125 ronald.dilley.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-6960-1125","contributorId":190829,"corporation":false,"usgs":true,"family":"Dilley","given":"Ronald","email":"ronald.dilley.ctr@usgs.gov","affiliations":[],"preferred":false,"id":690809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beckmann, Tim 0000-0002-2557-0638 tim.beckmann.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-2557-0638","contributorId":190830,"corporation":false,"usgs":true,"family":"Beckmann","given":"Tim","email":"tim.beckmann.ctr@usgs.gov","affiliations":[],"preferred":false,"id":690811,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidt, Gail L. 0000-0002-9684-8158 gschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-9684-8158","contributorId":3475,"corporation":false,"usgs":true,"family":"Schmidt","given":"Gail","email":"gschmidt@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":690810,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dwyer, John L. 0000-0002-8281-0896 dwyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-0896","contributorId":3481,"corporation":false,"usgs":true,"family":"Dwyer","given":"John","email":"dwyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":690812,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hughes, MJ","contributorId":190831,"corporation":false,"usgs":false,"family":"Hughes","given":"MJ","email":"","affiliations":[],"preferred":false,"id":690813,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Laue, Brady 0000-0002-4559-3618 brady.laue.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-4559-3618","contributorId":190832,"corporation":false,"usgs":true,"family":"Laue","given":"Brady","email":"brady.laue.ctr@usgs.gov","affiliations":[],"preferred":false,"id":690814,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70186886,"text":"70186886 - 2017 - Integrated species distribution models: combining presence-background data and site-occupancy data with imperfect detection","interactions":[],"lastModifiedDate":"2017-04-13T11:31:34","indexId":"70186886","displayToPublicDate":"2017-04-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Integrated species distribution models: combining presence-background data and site-occupancy data with imperfect detection","docAbstract":"The organic composition of groundwater along the Carrizo-Wilcox aquifer in East Texas (USA), sampled from rural wells in May and September 2015, was examined as part of a larger study of the potential health and environmental effects of organic compounds derived from low-rank coals. The quality of water from the low-rank coal-bearing Carrizo-Wilcox aquifer is a potential environmental concern and no detailed studies of the organic compounds in this aquifer have been published. Organic compounds identified in the water samples included: aliphatics and their fatty acid derivatives, phenols, biphenyls, N-, O-, and S-containing heterocyclic compounds, polycyclic aromatic hydrocarbons (PAHs), aromatic amines, and phthalates. Many of the identified organic compounds (aliphatics, phenols, heterocyclic compounds, PAHs) are geogenic and originated from groundwater leaching of young and unmetamorphosed low-rank coals. Estimated concentrations of individual compounds ranged from about 3.9 to 0.01 μg/L. In many rural areas in East Texas, coal strata provide aquifers for drinking water wells. Organic compounds observed in groundwater are likely to be present in drinking water supplied from wells that penetrate the coal. Some of the organic compounds identified in the water samples are potentially toxic to humans, but at the estimated levels in these samples, the compounds are unlikely to cause acute health problems. The human health effects of low-level chronic exposure to coal-derived organic compounds in drinking water in East Texas are currently unknown, and continuing studies will evaluate possible toxicity.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-016-1508-6","usgsCitation":"Chakraborty, J., Varonka, M.S., Orem, W.H., Finkelman, R.B., and Manton, W., 2017, Geogenic organic contaminants in the low-rank coal-bearing Carrizo-Wilcox aquifer of East Texas, USA: Hydrogeology Journal, v. 25, no. 4, p. 1219-1228, https://doi.org/10.1007/s10040-016-1508-6.","productDescription":"10 p.","startPage":"1219","endPage":"1228","ipdsId":"IP-076592","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":339690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Carrizo-Wilcox Aquifer","volume":"25","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-07","publicationStatus":"PW","scienceBaseUri":"58f08e5ee4b06911a29fa83e","contributors":{"authors":[{"text":"Chakraborty, Jayeeta","contributorId":190842,"corporation":false,"usgs":false,"family":"Chakraborty","given":"Jayeeta","email":"","affiliations":[],"preferred":false,"id":690860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Varonka, Matthew S. 0000-0003-3620-5262 mvaronka@usgs.gov","orcid":"https://orcid.org/0000-0003-3620-5262","contributorId":4726,"corporation":false,"usgs":true,"family":"Varonka","given":"Matthew","email":"mvaronka@usgs.gov","middleInitial":"S.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":690859,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":690861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Finkelman, Robert B.","contributorId":85951,"corporation":false,"usgs":true,"family":"Finkelman","given":"Robert","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":690862,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Manton, William","contributorId":190844,"corporation":false,"usgs":false,"family":"Manton","given":"William","email":"","affiliations":[],"preferred":false,"id":690863,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70186890,"text":"70186890 - 2017 - Geomorphic process from topographic form: automating the interpretation of repeat survey data in river valleys","interactions":[],"lastModifiedDate":"2017-09-18T15:43:24","indexId":"70186890","displayToPublicDate":"2017-04-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphic process from topographic form: automating the interpretation of repeat survey data in river valleys","docAbstract":"The ability to quantify the processes driving geomorphic change in river valley margins is vital to geomorphologists seeking to understand the relative role of transport mechanisms (e.g. fluvial, aeolian, and hillslope processes) in landscape dynamics. High-resolution, repeat topographic data are becoming readily available to geomorphologists. By contrasting digital elevation models derived from repeat surveys, the transport processes driving topographic changes can be inferred, a method termed ‘mechanistic segregation.’ Unfortunately, mechanistic segregation largely relies on subjective and time consuming manual classification, which has implications both for its reproducibility and the practical scale of its application. Here we present a novel computational workflow for the mechanistic segregation of geomorphic transport processes in geospatial datasets. We apply the workflow to seven sites along the Colorado River in the Grand Canyon, where geomorphic transport is driven by a diverse suite of mechanisms. The workflow performs well when compared to field observations, with an overall predictive accuracy of 84% across 113 validation points. The approach most accurately predicts changes due to fluvial processes (100% accuracy) and aeolian processes (96%), with reduced accuracy in predictions of alluvial and colluvial processes (64% and 73%, respectively). Our workflow is designed to be applicable to a diversity of river systems and will likely provide a rapid and objective understanding of the processes driving geomorphic change at the reach and network scales. We anticipate that such an understanding will allow insight into the response of geomorphic transport processes to external forcings, such as shifts in climate, land use, or river regulation, with implications for process-based river management and restoration.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.4143","usgsCitation":"Kasprak, A., Caster, J.J., Bangen, S.G., and Sankey, J.B., 2017, Geomorphic process from topographic form: automating the interpretation of repeat survey data in river valleys: Earth Surface Processes and Landforms, v. 42, no. 12, p. 1872-1883, https://doi.org/10.1002/esp.4143.","productDescription":"12 p.","startPage":"1872","endPage":"1883","ipdsId":"IP-079655","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":438376,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73776X6","text":"USGS data release","linkHelpText":"Geomorphic Process from Topographic FormData & Models"},{"id":339687,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.8787841796875,\n 35.67068501330236\n ],\n [\n -111.258544921875,\n 35.67068501330236\n ],\n [\n -111.258544921875,\n 37.077093191754436\n ],\n [\n -113.8787841796875,\n 37.077093191754436\n ],\n [\n -113.8787841796875,\n 35.67068501330236\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-10","publicationStatus":"PW","scienceBaseUri":"58f08e5de4b06911a29fa83c","contributors":{"authors":[{"text":"Kasprak, Alan 0000-0001-8184-6128 akasprak@usgs.gov","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":190848,"corporation":false,"usgs":true,"family":"Kasprak","given":"Alan","email":"akasprak@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":690869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caster, Joshua J. 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":131114,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":690902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bangen, Sara G.","contributorId":190858,"corporation":false,"usgs":false,"family":"Bangen","given":"Sara","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":690903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":690904,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187075,"text":"70187075 - 2017 - δ13C and d15N in the endangered Kemp’s ridley sea turtle Lepidochelys kempii after the Deepwater Horizon oil spill","interactions":[],"lastModifiedDate":"2020-12-16T16:53:18.789724","indexId":"70187075","displayToPublicDate":"2017-04-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"δ13C and d15N in the endangered Kemp’s ridley sea turtle Lepidochelys kempii after the Deepwater Horizon oil spill","title":"δ13C and d15N in the endangered Kemp’s ridley sea turtle Lepidochelys kempii after the Deepwater Horizon oil spill","docAbstract":"The Deepwater Horizon explosion in April 2010 and subsequent oil spill released 3.19 × 106 barrels (5.07 × 108 L) of MC252 crude oil into important foraging areas of the endangered Kemp’s ridley sea turtle Lepidochelys kempii (Lk) in the northern Gulf of Mexico (GoM). We measured δ13C and δ15N in scute biopsy samples from 33 Lk nesting in Texas during 2010–-12. Of these, 27 were equipped with satellite transmitters and were tracked to traditional foraging areas in the northern GoM after the spill. Differences in δ13C between the oldest and newest scute layers from 2010 nesters were not significantly different, but δ13C in the newest layers from 2011 and 2012 nesters was significantly lower compared to 2010. δ15N differences were not statistically significant. Collectively, the stable isotope and tracking data indicate that the lower δ13C values reflect the incorporation of oil rather than changes in diet or foraging area. Discriminant analysis indicated that 51.5% of the turtles sampled had isotope signatures indicating oil exposure. Growth of the Lk population slowed in the years following the spill. The involvement of oil exposure in recent population trends is unknown, but long-term effects may not be evident for many years. Our results indicate that C isotope signatures in scutes may be useful biomarkers of sea turtle exposure to oil.
","language":"English","publisher":"Inter-Research","publisherLocation":"Oldendorf/Luhe","doi":"10.3354/esr00819","usgsCitation":"Reich, K.J., Lopez-Castro, M.C., Shaver, D.J., Iseton, C., Hart, K.M., Hooper, M.J., and Schmitt, C.J., 2017, δ13C and d15N in the endangered Kemp’s ridley sea turtle Lepidochelys kempii after the Deepwater Horizon oil spill: Endangered Species Research, v. 33, p. 281-289, https://doi.org/10.3354/esr00819.","productDescription":"9 p.","startPage":"281","endPage":"289","ipdsId":"IP-076594","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":469928,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00819","text":"Publisher Index Page"},{"id":438375,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70C4SXJ","text":"USGS data release","linkHelpText":"Data tables in support of manuscript "​δ13C and δ15N in the Endangered Kemp's Ridley Sea Turtle Lepidochelys kempii After the Deepwater Horizon Oil Spill""},{"id":340065,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98,\n 25\n ],\n [\n -84,\n 25\n ],\n [\n -84,\n 31\n ],\n [\n -98,\n 31\n ],\n [\n -98,\n 25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58fb1a4be4b0c3010a8087b5","contributors":{"authors":[{"text":"Reich, Kimberly J.","contributorId":175452,"corporation":false,"usgs":false,"family":"Reich","given":"Kimberly","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":692331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lopez-Castro, Melania C.","contributorId":191185,"corporation":false,"usgs":false,"family":"Lopez-Castro","given":"Melania","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":692332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaver, Donna J.","contributorId":191186,"corporation":false,"usgs":false,"family":"Shaver","given":"Donna","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":692333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iseton, Claire","contributorId":191187,"corporation":false,"usgs":false,"family":"Iseton","given":"Claire","email":"","affiliations":[],"preferred":false,"id":692334,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":692335,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hooper, Michael J. 0000-0002-4161-8961 mhooper@usgs.gov","orcid":"https://orcid.org/0000-0002-4161-8961","contributorId":3251,"corporation":false,"usgs":true,"family":"Hooper","given":"Michael","email":"mhooper@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":692336,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmitt, Christopher J. 0000-0001-6804-2360 cjschmitt@usgs.gov","orcid":"https://orcid.org/0000-0001-6804-2360","contributorId":491,"corporation":false,"usgs":true,"family":"Schmitt","given":"Christopher","email":"cjschmitt@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":692330,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70186907,"text":"70186907 - 2017 - Benefits of the destinations, not costs of the journeys, shape partial migration patterns","interactions":[],"lastModifiedDate":"2017-06-14T11:48:54","indexId":"70186907","displayToPublicDate":"2017-04-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Benefits of the destinations, not costs of the journeys, shape partial migration patterns","docAbstract":"1. The reasons that lead some animals to seasonally migrate, and others to remain in the same area year-round, are poorly understood. Associations between traits, such as body size, and migration provide clues. For example, larger species and individuals are more likely to migrate.
2. One explanation for this size bias in migration is that larger animals are capable of moving faster (movement hypothesis). However, body size is linked to many other biological processes. For instance, the energetic balances of larger animals are generally more sensitive to variation in food density because of body size effects on foraging and metabolism and this sensitivity could drive migratory decisions (forage hypothesis).
3. Identifying the primary selective forces that drive migration ultimately requires quantifying fitness impacts over the full annual migratory cycle. Here, we develop a full annual migratory cycle model from metabolic and foraging theory to compare the importance of the forage and movement hypotheses. We parameterize the model for Galapagos tortoises, which were recently discovered to be size-dependent altitudinal migrants.
4. The model predicts phenomena not included in model development including maximum body sizes, the body size at which individuals begin to migrate, and the seasonal timing of migration and these predictions generally agree with available data. Scenarios strongly support the forage hypothesis over the movement hypothesis. Furthermore, male Galapagos tortoises on Santa Cruz Island would be unable to grow to their enormous sizes without access to both highlands and lowlands.
5. Whereas recent research has focused on links between traits and the migratory phases of the migratory cycle, we find that effects of body size on the non-migratory phases are far more important determinants of the propensity to migrate. Larger animals are more sensitive to changing forage conditions than smaller animals with implications for maintenance of migration and body size in the face of environmental change.
","language":"English","publisher":"Wiley","doi":"10.1111/1365-2656.12679","usgsCitation":"Yackulic, C.B., Blake, S., and Bastille-Rousseau, G., 2017, Benefits of the destinations, not costs of the journeys, shape partial migration patterns: Journal of Animal Ecology, v. 86, no. 4, p. 972-982, https://doi.org/10.1111/1365-2656.12679.","productDescription":"11 p.","startPage":"972","endPage":"982","ipdsId":"IP-065801","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469927,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.12679","text":"Publisher Index Page"},{"id":438374,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7154F7P","text":"USGS data release","linkHelpText":"Full Annual Cycle Bioenergetics model of migration applied to Galapagos tortoisesData"},{"id":339709,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-15","publicationStatus":"PW","scienceBaseUri":"58f08e5ce4b06911a29fa836","contributors":{"authors":[{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":690957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blake, Stephen","contributorId":65339,"corporation":false,"usgs":false,"family":"Blake","given":"Stephen","email":"","affiliations":[{"id":12472,"text":"Max Planck Institute for Ornithology","active":true,"usgs":false},{"id":30787,"text":"Saint Louis University","active":true,"usgs":false}],"preferred":false,"id":690958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bastille-Rousseau, Guillaume 0000-0001-6799-639X","orcid":"https://orcid.org/0000-0001-6799-639X","contributorId":190877,"corporation":false,"usgs":false,"family":"Bastille-Rousseau","given":"Guillaume","email":"","affiliations":[{"id":40724,"text":"Cooperative Wildlife Research Laboratory and Department of Forestry, Southern Illinois University, 251 Life Science II, Mail Code 6504, Carbondale, Illinois 62901 USA","active":true,"usgs":false}],"preferred":false,"id":690959,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70186894,"text":"70186894 - 2017 - Low-pathogenic influenza A viruses in North American diving ducks contribute to the emergence of a novel highly pathogenic influenza A(H7N8) virus","interactions":[],"lastModifiedDate":"2018-08-16T21:28:28","indexId":"70186894","displayToPublicDate":"2017-04-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2497,"text":"Journal of Virology","active":true,"publicationSubtype":{"id":10}},"title":"Low-pathogenic influenza A viruses in North American diving ducks contribute to the emergence of a novel highly pathogenic influenza A(H7N8) virus","docAbstract":"Introductions of low-pathogenic avian influenza (LPAI) viruses of subtypes H5 and H7 into poultry from wild birds have the potential to mutate to highly pathogenic avian influenza (HPAI) viruses, but such viruses' origins are often unclear. In January 2016, a novel H7N8 HPAI virus caused an outbreak in turkeys in Indiana, USA. To determine the virus's origin, we sequenced the genomes of 441 wild-bird origin influenza A viruses (IAVs) from North America and subjected them to evolutionary analyses. The results showed that the H7N8 LPAI virus most likely circulated among diving ducks in the Mississippi flyway during autumn 2015 and was subsequently introduced to Indiana turkeys, in which it evolved high pathogenicity. Preceding the outbreak, an isolate with six gene segments (PB2, PB1, PA, HA, NA, and NS) sharing >99% sequence identity with those of H7N8 turkey isolates was recovered from a diving duck sampled in Kentucky, USA. H4N8 IAVs from other diving ducks possessed five H7N8-like gene segments (PB2, PB1, NA, MP, and NS; >98% sequence identity). Our findings suggest that viral gene constellations circulating among diving ducks can contribute to the emergence of IAVs that affect poultry. Therefore, diving ducks may serve an important and understudied role in the maintenance, diversification, and transmission of IAVs in the wild-bird reservoir.
","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/JVI.02208-16","usgsCitation":"Xu, Y., Ramey, A.M., Bowman, A.S., DeLiberto, T.J., Killian, M.L., Krauss, S., Nolting, J.M., Torchetti, M.K., Reeves, A.B., Webby, R.J., Stallknecht, D.E., and Wan, X., 2017, Low-pathogenic influenza A viruses in North American diving ducks contribute to the emergence of a novel highly pathogenic influenza A(H7N8) virus: Journal of Virology, v. 91, no. 9, e02208-16, https://doi.org/10.1128/JVI.02208-16.","productDescription":"e02208-16","ipdsId":"IP-080329","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":469924,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1128/jvi.02208-16","text":"External 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Kim","contributorId":190856,"corporation":false,"usgs":false,"family":"Torchetti","given":"Mia","email":"","middleInitial":"Kim","affiliations":[],"preferred":false,"id":690898,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":690891,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Webby, Richard J.","contributorId":190857,"corporation":false,"usgs":false,"family":"Webby","given":"Richard","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":690899,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stallknecht, David E.","contributorId":14323,"corporation":false,"usgs":false,"family":"Stallknecht","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":690900,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wan, Xiu-Feng","contributorId":173959,"corporation":false,"usgs":false,"family":"Wan","given":"Xiu-Feng","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":690901,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70189161,"text":"70189161 - 2017 - The Nitrogen Footprint Tool network: A multi-institution program to reduce nitrogen pollution","interactions":[],"lastModifiedDate":"2017-07-05T09:21:09","indexId":"70189161","displayToPublicDate":"2017-04-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3504,"text":"Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"The Nitrogen Footprint Tool network: A multi-institution program to reduce nitrogen pollution","docAbstract":"Anthropogenic sources of reactive nitrogen have local and global impacts on air and water quality and detrimental effects on human and ecosystem health. This paper uses the nitrogen footprint tool (NFT) to determine the amount of nitrogen (N) released as a result of institutional consumption. The sectors accounted for include food (consumption and upstream production), energy, transportation, fertilizer, research animals, and agricultural research. The NFT is then used for scenario analysis to manage and track reductions, which are driven by the consumption behaviors of both the institution itself and its constituent individuals. In this paper, the first seven completed institution nitrogen footprint results are presented. The institution NFT network aims to develop footprints for many institutions to encourage widespread upper-level management strategies that will create significant reductions in reactive nitrogen released to the environment. Energy use and food purchases are the two largest sectors contributing to institution nitrogen footprints. Ongoing efforts by institutions to reduce greenhouse gas emissions also help to reduce the nitrogen footprint, but the impact of food production on nitrogen pollution has not been directly addressed by the higher-ed sustainability community. The NFT Network found that institutions could reduce their nitrogen footprints by optimizing food purchasing to reduce consumption of animal products and minimize food waste, as well as reducing dependence on fossil fuels for energy.","language":"English","publisher":"Mary Ann Liebert, Inc","doi":"10.1089/sus.2017.29098.eac","usgsCitation":"Castner, E.A., Leah, A.M., Leary, N., Baron, J., Compton, J.E., Galloway, J.N., Hastings, M.G., Kimiecik, J., Lantz-Trissel, J., de la Riguera, E., and Ryals, R., 2017, The Nitrogen Footprint Tool network: A multi-institution program to reduce nitrogen pollution: Sustainability, v. 10, no. 2, p. 79-88, https://doi.org/10.1089/sus.2017.29098.eac.","productDescription":"10 p. ","startPage":"79","endPage":"88","ipdsId":"IP-084847","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469925,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1089/sus.2017.29098.eac","text":"Publisher Index Page"},{"id":343283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595ca913e4b0d1f9f054ca14","contributors":{"authors":[{"text":"Castner, Elizabeth A.","contributorId":194131,"corporation":false,"usgs":false,"family":"Castner","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":703276,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leah, Allison M.","contributorId":194132,"corporation":false,"usgs":false,"family":"Leah","given":"Allison","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":703277,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leary, Neal","contributorId":194133,"corporation":false,"usgs":false,"family":"Leary","given":"Neal","email":"","affiliations":[],"preferred":false,"id":703278,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":703275,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Compton, Jana E.","contributorId":194134,"corporation":false,"usgs":false,"family":"Compton","given":"Jana","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":703279,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Galloway, James N.","contributorId":194135,"corporation":false,"usgs":false,"family":"Galloway","given":"James","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":703280,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hastings, Meredith G.","contributorId":194136,"corporation":false,"usgs":false,"family":"Hastings","given":"Meredith","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":703281,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kimiecik, Jacob","contributorId":194125,"corporation":false,"usgs":false,"family":"Kimiecik","given":"Jacob","email":"","affiliations":[],"preferred":false,"id":703282,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lantz-Trissel, Jonathan","contributorId":194137,"corporation":false,"usgs":false,"family":"Lantz-Trissel","given":"Jonathan","email":"","affiliations":[],"preferred":false,"id":703283,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"de la Riguera, Elizabeth","contributorId":194138,"corporation":false,"usgs":false,"family":"de la Riguera","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":703284,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ryals, Rebecca","contributorId":194139,"corporation":false,"usgs":false,"family":"Ryals","given":"Rebecca","affiliations":[],"preferred":false,"id":703285,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70190047,"text":"70190047 - 2017 - A new model for turbidity current behavior based on integration of flow monitoring and precision coring in a submarine canyon","interactions":[],"lastModifiedDate":"2017-08-07T17:09:12","indexId":"70190047","displayToPublicDate":"2017-04-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"A new model for turbidity current behavior based on integration of flow monitoring and precision coring in a submarine canyon","docAbstract":"Submarine turbidity currents create some of the largest sediment accumulations on Earth, yet there are few direct measurements of these flows. Instead, most of our understanding of turbidity currents results from analyzing their deposits in the sedimentary record. However, the lack of direct flow measurements means that there is considerable debate regarding how to interpret flow properties from ancient deposits. This novel study combines detailed flow monitoring with unusually precisely located cores at different heights, and multiple locations, within the Monterey submarine canyon, offshore California, USA. Dating demonstrates that the cores include the time interval that flows were monitored in the canyon, albeit individual layers cannot be tied to specific flows. There is good correlation between grain sizes collected by traps within the flow and grain sizes measured in cores from similar heights on the canyon walls. Synthesis of flow and deposit data suggests that turbidity currents sourced from the upper reaches of Monterey Canyon comprise three flow phases. Initially, a thin (38–50 m) powerful flow in the upper canyon can transport, tilt, and break the most proximal moorings and deposit chaotic sands and gravel on the canyon floor. The initially thin flow front then thickens and deposits interbedded sands and silty muds on the canyon walls as much as 62 m above the canyon floor. Finally, the flow thickens along its length, thus lofting silty mud and depositing it at greater altitudes than the previous deposits and in excess of 70 m altitude.","language":"English","publisher":"Geological Society of America","doi":"10.1130/G38764.1","usgsCitation":"Symons, W.O., Sumner, E.J., Paull, C.K., Cartigny, M.J., Xu, J., Maier, K., Lorenson, T., and Talling, P.J., 2017, A new model for turbidity current behavior based on integration of flow monitoring and precision coring in a submarine canyon: Geology, v. 45, no. 4, p. 367-370, https://doi.org/10.1130/G38764.1.","productDescription":"4 p.","startPage":"367","endPage":"370","ipdsId":"IP-075966","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469934,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g38764.1","text":"Publisher Index Page"},{"id":344623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-01","publicationStatus":"PW","scienceBaseUri":"59897c15e4b09fa1cb0c2c04","contributors":{"authors":[{"text":"Symons, William O.","contributorId":195511,"corporation":false,"usgs":false,"family":"Symons","given":"William","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":707308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sumner, Esther J.","contributorId":195512,"corporation":false,"usgs":false,"family":"Sumner","given":"Esther","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":707309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paull, Charles K. 0000-0001-5940-3443","orcid":"https://orcid.org/0000-0001-5940-3443","contributorId":55825,"corporation":false,"usgs":false,"family":"Paull","given":"Charles","email":"","middleInitial":"K.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":true,"id":707310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cartigny, Matthieu J.B.","contributorId":195513,"corporation":false,"usgs":false,"family":"Cartigny","given":"Matthieu","email":"","middleInitial":"J.B.","affiliations":[],"preferred":false,"id":707311,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xu, Jingping","contributorId":195514,"corporation":false,"usgs":false,"family":"Xu","given":"Jingping","affiliations":[],"preferred":false,"id":707312,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maier, Katherine L.","contributorId":91411,"corporation":false,"usgs":true,"family":"Maier","given":"Katherine L.","affiliations":[],"preferred":false,"id":707307,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lorenson, Thomas 0000-0001-7669-2873 tlorenson@usgs.gov","orcid":"https://orcid.org/0000-0001-7669-2873","contributorId":174599,"corporation":false,"usgs":true,"family":"Lorenson","given":"Thomas","email":"tlorenson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":707313,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Talling, Peter J.","contributorId":195515,"corporation":false,"usgs":false,"family":"Talling","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":707314,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70186868,"text":"70186868 - 2017 - Simulation of rapid ecological change in Lake Ontario","interactions":[],"lastModifiedDate":"2017-09-11T12:54:47","indexId":"70186868","displayToPublicDate":"2017-04-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Simulation of rapid ecological change in Lake Ontario","docAbstract":"Lower trophic level processes are integral to proper functioning of large aquatic ecosystems and have been disturbed in Lake Ontario by various stressors including exotic species. The invasion of benthic habitats by dreissenid mussels has led to systemic changes and native faunal declines. Size-dependent physiological rates, spatial differences and connectivity, competition, and differential population dynamics among invertebrate groups contributed to the change and system complexity. We developed a spatially explicit, individual-based mechanistic model of the benthic ecosystem in Lake Ontario, with coupling to the pelagic system, to examine ecosystem dynamics and effects of dreissenid mussel invasion and native fauna losses. Benthic organisms were represented by functional groups; filter-feeders (i.e., dreissenid mussels), surface deposit-feeders (e.g., native amphipod Diporeia spp.), and deposit-feeders (e.g., oligochaetes and other burrowers). The model was stable, represented ecological structure and function effectively, and reproduced observed effects of the mussel invasion. Two hypotheses for causes of Diporeia loss, competition or disease-like mortality, were tested. Simple competition for food did not explain observed declines in native surface deposit-feeders during the filter-feeder invasion. However, the elevated mortality scenario supports a disease-like cause for loss of the native amphipod, with population changes in various lake areas and altered benthic biomass transfers. Stabilization of mussel populations and possible recovery of the native, surface-deposit feeding amphipod were predicted. Although further research is required on forcing functions, model parameters, and natural conditions, the model provides a valuable tool to help managers understand the benthic system and plan for response to future disruptions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2017.03.008","usgsCitation":"McKenna, J., Chalupnicki, M., Dittman, D.E., and Watkins, J.M., 2017, Simulation of rapid ecological change in Lake Ontario: Journal of Great Lakes Research, v. 43, no. 5, p. 871-889, https://doi.org/10.1016/j.jglr.2017.03.008.","productDescription":"19 p.","startPage":"871","endPage":"889","ipdsId":"IP-064471","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469931,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2017.03.008","text":"Publisher Index Page"},{"id":339623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.9530029296875,\n 43.17313537107136\n ],\n [\n -76.0858154296875,\n 43.17313537107136\n ],\n [\n -76.0858154296875,\n 44.27273816279087\n ],\n [\n -79.9530029296875,\n 44.27273816279087\n ],\n [\n -79.9530029296875,\n 43.17313537107136\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ef3da7e4b0eed1ab8e3bc6","chorus":{"doi":"10.1016/j.jglr.2017.03.008","url":"http://dx.doi.org/10.1016/j.jglr.2017.03.008","publisher":"Elsevier BV","authors":"McKenna James E., Chalupnicki Marc, Dittman Dawn, Watkins James M.","journalName":"Journal of Great Lakes Research","publicationDate":"4/2017"},"contributors":{"authors":[{"text":"McKenna, James E. Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":190798,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","suffix":"Jr.","email":"jemckenna@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":690734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chalupnicki, Marc 0000-0002-3792-9345 mchalupnicki@usgs.gov","orcid":"https://orcid.org/0000-0002-3792-9345","contributorId":173643,"corporation":false,"usgs":true,"family":"Chalupnicki","given":"Marc","email":"mchalupnicki@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":690735,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dittman, Dawn E. 0000-0002-0711-3732 ddittman@usgs.gov","orcid":"https://orcid.org/0000-0002-0711-3732","contributorId":2762,"corporation":false,"usgs":true,"family":"Dittman","given":"Dawn","email":"ddittman@usgs.gov","middleInitial":"E.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":690736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watkins, James M.","contributorId":189286,"corporation":false,"usgs":false,"family":"Watkins","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":690737,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186865,"text":"70186865 - 2017 - Occurrence and in vitro bioactivity of estrogen, androgen, and glucocorticoid compounds in a nationwide screen of United States stream waters","interactions":[],"lastModifiedDate":"2017-07-12T16:07:27","indexId":"70186865","displayToPublicDate":"2017-04-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence and in vitro bioactivity of estrogen, androgen, and glucocorticoid compounds in a nationwide screen of United States stream waters","docAbstract":"In vitro bioassays are sensitive, effect-based tools used to quantitatively screen for chemicals with nuclear receptor activity in environmental samples. We measured in vitro estrogen (ER), androgen (AR), and glucocorticoid receptor (GR) activity, along with a broad suite of chemical analytes, in streamwater from 35 well-characterized sites (3 reference and 32 impacted) across 24 states and Puerto Rico. ER agonism was the most frequently detected with nearly all sites (34/35) displaying activity (range, 0.054–116 ng E2Eq L–1). There was a strong linear relationship (r2 = 0.917) between in vitro ER activity and concentrations of steroidal estrogens after correcting for the in vitro potency of each compound. AR agonism was detected in 5/35 samples (range, 1.6–4.8 ng DHTEq L–1) but concentrations of androgenic compounds were largely unable to account for the in vitro activity. Similarly, GR agonism was detected in 9/35 samples (range, 6.0–43 ng DexEq L–1); however, none of the recognized GR-active compounds on the target-chemical analyte list were detected. The utility of in vitro assays in water quality monitoring was evident from both the quantitative agreement between ER activity and estrogen concentrations, as well as the detection of AR and GR activity for which there were limited or no corresponding target-chemical detections to explain the bioactivity. Incorporation of in vitro bioassays as complements to chemical analyses in standard water quality monitoring efforts would allow for more complete assessment of the chemical mixtures present in many surface waters.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.6b06515","usgsCitation":"Conley, J.M., Evans, N., Cardon, M.C., Rosenblum, L., Iwanowicz, L.R., Hartig, P.C., Schenck, K.M., Bradley, P.M., and Wilson, V.S., 2017, Occurrence and in vitro bioactivity of estrogen, androgen, and glucocorticoid compounds in a nationwide screen of United States stream waters: Environmental Science & Technology, v. 51, no. 9, p. 4781-4791, https://doi.org/10.1021/acs.est.6b06515.","productDescription":"11 p.","startPage":"4781","endPage":"4791","ipdsId":"IP-083493","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":469930,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11247474","text":"External Repository"},{"id":339593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"51","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-12","publicationStatus":"PW","scienceBaseUri":"58ef3da7e4b0eed1ab8e3bc8","contributors":{"authors":[{"text":"Conley, Justin M.","contributorId":184086,"corporation":false,"usgs":false,"family":"Conley","given":"Justin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":690714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Nicola","contributorId":184087,"corporation":false,"usgs":false,"family":"Evans","given":"Nicola","email":"","affiliations":[],"preferred":false,"id":690715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cardon, Mary C.","contributorId":190792,"corporation":false,"usgs":false,"family":"Cardon","given":"Mary","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":690716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosenblum, Laura","contributorId":184089,"corporation":false,"usgs":false,"family":"Rosenblum","given":"Laura","email":"","affiliations":[],"preferred":false,"id":690717,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":190787,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke","email":"liwanowicz@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":690718,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hartig, Phillip C.","contributorId":190793,"corporation":false,"usgs":false,"family":"Hartig","given":"Phillip","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":690719,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schenck, Kathleen M.","contributorId":184136,"corporation":false,"usgs":false,"family":"Schenck","given":"Kathleen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":690720,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":690713,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wilson, Vickie S. 0000-0003-1661-8481","orcid":"https://orcid.org/0000-0003-1661-8481","contributorId":184092,"corporation":false,"usgs":false,"family":"Wilson","given":"Vickie","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":690721,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70186864,"text":"70186864 - 2017 - Expanded target-chemical analysis reveals extensive mixed-organic-contaminant exposure in USA streams","interactions":[],"lastModifiedDate":"2018-09-13T13:52:56","indexId":"70186864","displayToPublicDate":"2017-04-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Expanded target-chemical analysis reveals extensive mixed-organic-contaminant exposure in USA streams","docAbstract":"Surface water from 38 streams nationwide was assessed using 14 target-organic methods (719 compounds). Designed-bioactive anthropogenic contaminants (biocides, pharmaceuticals) comprised 57% of 406 organics detected at least once. The 10 most-frequently detected anthropogenic-organics included eight pesticides (desulfinylfipronil, AMPA, chlorpyrifos, dieldrin, metolachlor, atrazine, CIAT, glyphosate) and two pharmaceuticals (caffeine, metformin) with detection frequencies ranging 66–84% of all sites. Detected contaminant concentrations varied from less than 1 ng L–1 to greater than 10 μg L–1, with 77 and 278 having median detected concentrations greater than 100 ng L–1 and 10 ng L–1, respectively. Cumulative detections and concentrations ranged 4–161 compounds (median 70) and 8.5–102 847 ng L–1, respectively, and correlated significantly with wastewater discharge, watershed development, and toxic release inventory metrics. Log10 concentrations of widely monitored HHCB, triclosan, and carbamazepine explained 71–82% of the variability in the total number of compounds detected (linear regression; p-values: < 0.001–0.012), providing a statistical inference tool for unmonitored contaminants. Due to multiple modes of action, high bioactivity, biorecalcitrance, and direct environment application (pesticides), designed-bioactive organics (median 41 per site at μg L–1 cumulative concentrations) in developed watersheds present aquatic health concerns, given their acknowledged potential for sublethal effects to sensitive species and lifecycle stages at low ng L–1.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.7b00012","usgsCitation":"Bradley, P.M., Journey, C.A., Romanok, K.M., Barber, L.B., Buxton, H.T., Foreman, W.T., Furlong, E.T., Glassmeyer, S.T., Hladik, M., Iwanowicz, L., Jones, D.K., Kolpin, D.W., Kuivila, K.M., Loftin, K.A., Mills, M.A., Meyer, M.T., Orlando, J.L., Reilly, T.J., Smalling, K., and Villeneuve, D.L., 2017, Expanded target-chemical analysis reveals extensive mixed-organic-contaminant exposure in USA streams: Environmental Science & Technology, v. 51, no. 9, p. 4792-4802, https://doi.org/10.1021/acs.est.7b00012.","productDescription":"11 p.","startPage":"4792","endPage":"4802","ipdsId":"IP-080387","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":469933,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5695041","text":"Publisher Index Page"},{"id":438377,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70863G5","text":"USGS data release","linkHelpText":"Targeted-Organic-Chemical Analysis Concentration Data for Surface-Water Samples Collected from 38 Stream Sites across the USA during 2012-2014"},{"id":339592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"51","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-12","publicationStatus":"PW","scienceBaseUri":"58ef3da8e4b0eed1ab8e3bca","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":690692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":189681,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":690693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanok, Kristin M. 0000-0002-8472-8765 kromanok@usgs.gov","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":189680,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin","email":"kromanok@usgs.gov","middleInitial":"M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":690694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":690695,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buxton, Herbert T.","contributorId":178698,"corporation":false,"usgs":false,"family":"Buxton","given":"Herbert","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":690697,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foreman, William T. 0000-0002-2530-3310 wforeman@usgs.gov","orcid":"https://orcid.org/0000-0002-2530-3310","contributorId":190786,"corporation":false,"usgs":true,"family":"Foreman","given":"William","email":"wforeman@usgs.gov","middleInitial":"T.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":690698,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":690699,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Glassmeyer, Susan T.","contributorId":184135,"corporation":false,"usgs":false,"family":"Glassmeyer","given":"Susan","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":690700,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hladik, Michelle L. 0000-0002-0891-2712 mhladik@usgs.gov","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":189904,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle L.","email":"mhladik@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":690701,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":150383,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R. 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","email":"ksmall@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":690731,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Villeneuve, Daniel L.","contributorId":32091,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Daniel","email":"","middleInitial":"L.","affiliations":[{"id":13485,"text":"U.S. Environmental Protection Agency, Duluth, MN","active":true,"usgs":false}],"preferred":false,"id":690732,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70186880,"text":"70186880 - 2017 - Quantifying the demographic cost of human-related mortality to a raptor population","interactions":[],"lastModifiedDate":"2017-11-22T16:58:07","indexId":"70186880","displayToPublicDate":"2017-04-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the demographic cost of human-related mortality to a raptor population","docAbstract":"Raptors are exposed to a wide variety of human-related mortality agents, and yet population-level effects are rarely quantified. Doing so requires modeling vital rates in the context of species life-history, behavior, and population dynamics theory. In this paper, we explore the details of such an analysis by focusing on the demography of a resident, tree-nesting population of golden eagles (Aquila chrysaetos) in the vicinity of an extensive (142 km2) windfarm in California. During 1994–2000, we tracked the fates of >250 radio-marked individuals of four life-stages and conducted five annual surveys of territory occupancy and reproduction. Collisions with wind turbines accounted for 41% of 88 uncensored fatalities, most of which were subadults and nonbreeding adults (floaters). A consistent overall male preponderance in the population meant that females were the limiting sex in this territorial, monogamous species. Estimates of potential population growth rate and associated variance indicated a stable breeding population, but one for which any further decrease in vital rates would require immigrant floaters to fill territory vacancies. Occupancy surveys 5 and 13 years later (2005 and 2013) showed that the nesting population remained intact, and no upward trend was apparent in the proportion of subadult eagles as pair members, a condition that would have suggested a deficit of adult replacements. However, the number of golden eagle pairs required to support windfarm mortality was large. We estimated that the entire annual reproductive output of 216–255 breeding pairs would have been necessary to support published estimates of 55–65 turbine blade-strike fatalities per year. Although the vital rates forming the basis for these calculations may have changed since the data were collected, our approach should be useful for gaining a clearer understanding of how anthropogenic mortality affects the health of raptor populations, particularly those species with delayed maturity and naturally low reproductive rates.
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