Environmental tracers are useful for determining groundwater age and recharge source, yet their application in studies of geogenic Cr(VI) in groundwater has been limited. Environmental tracer data from 166 wells located in the Sacramento Valley, northern California, were interpreted and compared to Cr concentrations to determine the origin and age of groundwater with elevated Cr(VI), and better understand where Cr(VI) becomes mobilized and how it evolves along flowpaths. In addition to major ion and trace element concentrations, the dataset includes δ18O, δ2H, 3H concentration, 14C activity (of dissolved inorganic C), δ13C, 3He/4He ratio, and noble gas concentrations (He, Ne, Ar, Kr, Xe). Noble gas recharge temperatures (NGTs) were computed, and age-related tracers were interpreted in combination to constrain the age distribution in samples and sort them into six different age categories spanning from <60 yr old to >10,000 yr old. Nearly all measured Cr is in the form of Cr(IV). Concentrations range from <1 to 46 μg L−1, with 10% exceeding the state of California’s Cr(VI) maximum contaminant level of 10 μg L−1. Two groups with elevated Cr(VI) (⩾5 μg L−1) were identified. Group 1 samples are from the southern part of the valley and contain modern (<60 yr old) water, have elevated NO3− concentrations (>3 mg L−1), and commonly have δ18O values enriched relative to local precipitation. These samples likely contain irrigation water and are elevated due to accelerated mobilization of Cr(VI) in the unsaturated zone (UZ) in irrigated areas. Group 2 samples are from throughout the valley and typically contain water 1000–10,000 yr old, have δ18O values consistent with local precipitation, and have unexpectedly warm NGTs. Chromium(VI) concentrations in Group 2 samples may be elevated for multiple reasons, but the hypothesis most consistent with all available data (notably, the warm NGTs) is a relatively long UZ residence time due to recharge through a deep UZ near the margin of the basin. A possible explanation for why Cr(VI) may be primarily mobilized in the UZ rather than farther along flowpaths in the oxic portion of the saturated zone is more dynamic cycling of Mn in the UZ due to transient moisture and redox conditions.
\nThis report documents the development of statistical tools used to quantify the hazard presented by the response of sea-level elevation to natural or anthropogenic changes in climate and ocean circulation. A hazard is a physical process (or processes) that, when combined with vulnerability (or susceptibility to the hazard), results in risk. This study presents the development and comparison of new and existing sea-level analysis methods, exploration of the strengths and weaknesses of the methods using synthetic time series, and when appropriate, synthesis of the application of the method to observed sea-level time series. These reports are intended to enhance material presented in peer-reviewed journal articles where it is not always possible to provide the level of detail that might be necessary to fully support or recreate published results.
\nThe purpose of this report is to document and compare three simple methodologies that have previously been used to provide estimates with associated errors of the acceleration of sea-level elevation. These techniques have been used by coastal scientists and planners in assessing coastal risk over a wide range of spatial and temporal scales. Because relative sea-level (SL) elevation time series contain energetic fluctuations at many time scales, extracting what can be relatively small rate and acceleration signals (along with estimates of the error) from much larger “noise” has proven to be both difficult and controversial. Acceleration is a preferred measure of SL response to recent changes in the Earth’s climate because over time scales of 100 years or less slow vertical land motions (such as glacial isostatic adjustment) contribute only to the linear signal and not to acceleration, thus reducing the complexity of the analysis. Hence acceleration is useful if the goal of a study is to characterize and quantify the hazard associated with the changing relative elevation of water with respect to land on decadal time scales. Although in some cases it may be necessary to determine the cause of relative sea level rise, as a first step, it is important to accurately estimate the magnitude of the threat.
\nMost researchers agree that global sea level (GSL) rose persistently through much of the 20th century at about 1.5–2.0 millimeters per year (mm/yr). There is far less agreement about whether the rate of sea-level rise (SLR) is increasing (that is, an acceleration in SL).
\nRecent studies, and most of their predecessors, use tide gage data to quantify SL acceleration, ASL(t). In the current study, three techniques were used to calculate acceleration from tide gage data, and of those examined, it was determined that the two techniques based on sliding a regression window through the time series are more robust compared to the technique that fits a single quadratic form to the entire time series, particularly if there is temporal variation in the magnitude of the acceleration. The single-fit quadratic regression method has been the most commonly used technique in determining acceleration in tide gage data. The inability of the single-fit method to account for time-varying acceleration may explain some of the inconsistent findings between investigators. Properly quantifying ASL(t) from field measurements is of particular importance in evaluating numerical models of past, present, and future SLR resulting from anticipated climate change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151187","issn":"2331-1258","usgsCitation":"Doran, K.S., Howd, P.A., and Sallenger, A.H., Jr., 2015, Detecting sea-level hazards—Simple regression-based methods for calculating the acceleration of sea level: U.S. Geological Survey Open-File Report 2015–1187, 28 p.","productDescription":"v, 28 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-039300","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":313205,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1187/cover.jpg"},{"id":313038,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1187/ofr20151187.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1187"}],"contact":"St. Petersburg Coastal and Marine Science Center
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http://coastal.er.usgs.gov/
Statistical summaries of streamflow data collected at 184 streamgages in Iowa are presented in this report. All streamgages included for analysis have at least 10 years of continuous record collected before or through September 2013. This report is an update to two previously published reports that presented statistical summaries of selected Iowa streamflow data through September 1988 and September 1996. The statistical summaries include (1) monthly and annual flow durations, (2) annual exceedance probabilities of instantaneous peak discharges (flood frequencies), (3) annual exceedance probabilities of high discharges, and (4) annual nonexceedance probabilities of low discharges and seasonal low discharges. Also presented for each streamgage are graphs of the annual mean discharges, mean annual mean discharges, 50-percent annual flow-duration discharges (median flows), harmonic mean flows, mean daily mean discharges, and flow-duration curves. Two sets of statistical summaries are presented for each streamgage, which include (1) long-term statistics for the entire period of streamflow record and (2) recent-term statistics for or during the 30-year period of record from 1984 to 2013. The recent-term statistics are only calculated for streamgages with streamflow records pre-dating the 1984 water year and with at least 10 years of record during 1984–2013. The streamflow statistics in this report are not adjusted for the effects of water use; although some of this water is used consumptively, most of it is returned to the streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151214","collaboration":"Prepared in cooperation with the Iowa Department of Transportation, the Iowa Highway Research Board (Iowa DOT Research Project TR-669), and the U.S. Army Corps of Engineers","usgsCitation":"Eash, D.A., O’Shea, P.S., Weber, J.R., Nguyen, K.T., Montgomery, N.L., and Simonson, A.J., 2015, Statistical summaries of selected Iowa streamflow data through September 2013: U.S. Geological Survey Open-File Report 2015–1214, 18 p., https://dx.doi.org/10.3133/ofr20151214.","productDescription":"Report: vii, 18 p.; Table; Companion File","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1984-01-01","ipdsId":"IP-064768","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":312212,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1214/coverthb.jpg"},{"id":312213,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1214/ofr20151214.pdf","text":"Report","size":"1.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1214"},{"id":312214,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2015/1214/downloads/of20151214_table1.pdf","text":"Table 1","size":"229 kB","description":"OFR 2015-1214 Table 1"},{"id":312216,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1214/downloads/streamgage_summaries_12_2_15.zip","text":"Streamgage Summaries","size":"43.1 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2015-1215 Streamflow statistics"}],"country":"United 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\"}}]}","contact":"Director, Iowa Water Science Center
U.S. Geological Survey
P.O. Box 1230
Iowa City, IA 52244
http://ia.water.usgs.gov
Restoration of degraded ecosystems is an important societal goal, yet inadequate monitoring and the absence of clear performance metrics are common criticisms of many habitat restoration projects. Funding limitations can prevent adequate monitoring, but we suggest that the lack of accepted metrics to address the diversity of restoration objectives also presents a serious challenge to the monitoring of restoration projects. A working group with experience in designing and monitoring oyster reef projects was used to develop standardized monitoring metrics, units, and performance criteria that would allow for comparison among restoration sites and projects of various construction types. A set of four universal metrics (reef areal dimensions, reef height, oyster density, and oyster size–frequency distribution) and a set of three universal environmental variables (water temperature, salinity, and dissolved oxygen) are recommended to be monitored for all oyster habitat restoration projects regardless of their goal(s). In addition, restoration goal-based metrics specific to four commonly cited ecosystem service-based restoration goals are recommended, along with an optional set of seven supplemental ancillary metrics that could provide information useful to the interpretation of prerestoration and postrestoration monitoring data. Widespread adoption of a common set of metrics with standardized techniques and units to assess well-defined goals not only allows practitioners to gauge the performance of their own projects but also allows for comparison among projects, which is both essential to the advancement of the field of oyster restoration and can provide new knowledge about the structure and ecological function of oyster reef ecosystems.
","language":"English","publisher":"Society for Ecological Restoration","doi":"10.1111/rec.12262","usgsCitation":"Baggett, L.P., Powers, S.P., Brumbaugh, R.D., Coen, L.D., DeAngelis, B.M., Greene, J.K., Hancock, B.T., Morlock, S.M., Allen, B.L., Breitburg, D.L., Bushek, D., Grabowski, J., Grizzle, R.E., Grosholz, E., LaPeyre, M.K., Luckenbach, M.W., McGraw, K.A., Piehler, M.F., Westby, S.R., and zu Ermgassen, P., 2015, Guidelines for evaluating performance of oyster habitat restoration: Restoration Ecology, v. 23, no. 6, p. 737-745, https://doi.org/10.1111/rec.12262.","productDescription":"9 p.","startPage":"737","endPage":"745","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056583","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":323274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-02","publicationStatus":"PW","scienceBaseUri":"575941f3e4b04f417c256871","contributors":{"authors":[{"text":"Baggett, Lesley P.","contributorId":171552,"corporation":false,"usgs":false,"family":"Baggett","given":"Lesley","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":637926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powers, Sean P.","contributorId":138867,"corporation":false,"usgs":false,"family":"Powers","given":"Sean","email":"","middleInitial":"P.","affiliations":[{"id":12554,"text":"University of South Alabama and Dauphin Island Sea Lab, Dauphin","active":true,"usgs":false}],"preferred":false,"id":637927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brumbaugh, Robert 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E.","contributorId":171568,"corporation":false,"usgs":false,"family":"zu Ermgassen","given":"Philine S. E.","affiliations":[],"preferred":false,"id":637944,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70173669,"text":"70173669 - 2015 - A guide to Bayesian model selection for ecologists","interactions":[],"lastModifiedDate":"2016-06-08T09:53:32","indexId":"70173669","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"A guide to Bayesian model selection for ecologists","docAbstract":"The steady upward trend in the use of model selection and Bayesian methods in ecological research has made it clear that both approaches to inference are important for modern analysis of models and data. However, in teaching Bayesian methods and in working with our research colleagues, we have noticed a general dissatisfaction with the available literature on Bayesian model selection and multimodel inference. Students and researchers new to Bayesian methods quickly find that the published advice on model selection is often preferential in its treatment of options for analysis, frequently advocating one particular method above others. The recent appearance of many articles and textbooks on Bayesian modeling has provided welcome background on relevant approaches to model selection in the Bayesian framework, but most of these are either very narrowly focused in scope or inaccessible to ecologists. Moreover, the methodological details of Bayesian model selection approaches are spread thinly throughout the literature, appearing in journals from many different fields. Our aim with this guide is to condense the large body of literature on Bayesian approaches to model selection and multimodel inference and present it specifically for quantitative ecologists as neutrally as possible. We also bring to light a few important and fundamental concepts relating directly to model selection that seem to have gone unnoticed in the ecological literature. Throughout, we provide only a minimal discussion of philosophy, preferring instead to examine the breadth of approaches as well as their practical advantages and disadvantages. This guide serves as a reference for ecologists using Bayesian methods, so that they can better understand their options and can make an informed choice that is best aligned with their goals for inference.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/14-0661.1","usgsCitation":"Hooten, M., and Hobbs, N., 2015, A guide to Bayesian model selection for ecologists: Ecological Monographs, v. 85, no. 1, p. 3-28, https://doi.org/10.1890/14-0661.1.","productDescription":"26 p.","startPage":"3","endPage":"28","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052758","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"85","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575941b1e4b04f417c25676b","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":637477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hobbs, N.T.","contributorId":9498,"corporation":false,"usgs":true,"family":"Hobbs","given":"N.T.","email":"","affiliations":[],"preferred":false,"id":637820,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70173688,"text":"70173688 - 2015 - Smartphones reveal angler behavior: A case study of a popular mobile fishing application in Alberta, Canada","interactions":[],"lastModifiedDate":"2018-02-28T14:39:56","indexId":"70173688","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Smartphones reveal angler behavior: A case study of a popular mobile fishing application in Alberta, Canada","docAbstract":"Successfully managing fisheries and controlling the spread of invasive species depends on the ability to describe and predict angler behavior. However, finite resources restrict conventional survey approaches and tend to produce retrospective data that are limited in time or space and rely on intentions or attitudes rather than actual behavior. In this study, we used three years of angler data from a popular mobile fishing application in Alberta, Canada, to determine province-wide, seasonal patterns of (1) lake popularity that were consistent with conventional data and (2) anthropogenic lake connectivity that has not been widely described in North America. Our proof-of-concept analyses showed that mobile apps can be an inexpensive source of high-resolution, real-time data for managing fisheries and invasive species. We also identified key challenges that underscore the need for further research and development in this new frontier that combines big data with increased stakeholder interaction and cooperation.
","language":"English","publisher":"Taylor & Francis Online","doi":"10.1080/03632415.2015.1049693","usgsCitation":"Papenfuss, J.T., Phelps, N., Fulton, D.C., and Venturelli, P.A., 2015, Smartphones reveal angler behavior: A case study of a popular mobile fishing application in Alberta, Canada: Fisheries, v. 40, no. 7, p. 318-327, https://doi.org/10.1080/03632415.2015.1049693.","productDescription":"10 p.","startPage":"318","endPage":"327","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057833","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-01","publicationStatus":"PW","scienceBaseUri":"5757f064e4b04f417c24dd1d","contributors":{"authors":[{"text":"Papenfuss, Jason T.","contributorId":171475,"corporation":false,"usgs":false,"family":"Papenfuss","given":"Jason","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":637567,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phelps, Nicholas","contributorId":171476,"corporation":false,"usgs":false,"family":"Phelps","given":"Nicholas","affiliations":[],"preferred":false,"id":637568,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fulton, David C. 0000-0001-5763-7887 dcf@usgs.gov","orcid":"https://orcid.org/0000-0001-5763-7887","contributorId":2208,"corporation":false,"usgs":true,"family":"Fulton","given":"David","email":"dcf@usgs.gov","middleInitial":"C.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637509,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Venturelli, Paul A.","contributorId":171477,"corporation":false,"usgs":false,"family":"Venturelli","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":637569,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159879,"text":"70159879 - 2015 - Interactive access to LP DAAC satellite data archives through a combination of open-source and custom middleware web services","interactions":[],"lastModifiedDate":"2017-01-18T09:55:15","indexId":"70159879","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1940,"text":"IEEE Geoscience and Remote Sensing Letters","active":true,"publicationSubtype":{"id":10}},"title":"Interactive access to LP DAAC satellite data archives through a combination of open-source and custom middleware web services","docAbstract":"Current methods of searching for and retrieving data from satellite land remote sensing archives do not allow for interactive information extraction. Instead, Earth science data users are required to download files over low-bandwidth networks to local workstations and process data before science questions can be addressed. New methods of extracting information from data archives need to become more interactive to meet user demands for deriving increasingly complex information from rapidly expanding archives. Moving the tools required for processing data to computer systems of data providers, and away from systems of the data consumer, can improve turnaround times for data processing workflows. The implementation of middleware services was used to provide interactive access to archive data. The goal of this middleware services development is to enable Earth science data users to access remote sensing archives for immediate answers to science questions instead of links to large volumes of data to download and process. Exposing data and metadata to web-based services enables machine-driven queries and data interaction. Also, product quality information can be integrated to enable additional filtering and sub-setting. Only the reduced content required to complete an analysis is then transferred to the user.
","language":"English","publisher":"IEEE","doi":"10.1109/MGRS.2015.2505999","usgsCitation":"Davis, B.N., Werpy, J., Friesz, A.M., Impecoven, K., Quenzer, R., Maiersperger, T., and Meyer, D.J., 2015, Interactive access to LP DAAC satellite data archives through a combination of open-source and custom middleware web services: IEEE Geoscience and Remote Sensing Letters, v. 3, no. 4, p. 8-20, https://doi.org/10.1109/MGRS.2015.2505999.","productDescription":"13 p.","startPage":"8","endPage":"20","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065401","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":324689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"577642b0e4b07dd077c87403","contributors":{"authors":[{"text":"Davis, Brian N. bdavis@usgs.gov","contributorId":4720,"corporation":false,"usgs":true,"family":"Davis","given":"Brian","email":"bdavis@usgs.gov","middleInitial":"N.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":580866,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Werpy, Jason jwerpy@usgs.gov","contributorId":4438,"corporation":false,"usgs":true,"family":"Werpy","given":"Jason","email":"jwerpy@usgs.gov","affiliations":[],"preferred":true,"id":641422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friesz, Aaron M. 0000-0003-4096-3824 afriesz@usgs.gov","orcid":"https://orcid.org/0000-0003-4096-3824","contributorId":5943,"corporation":false,"usgs":true,"family":"Friesz","given":"Aaron","email":"afriesz@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":641423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Impecoven, Kevin","contributorId":172619,"corporation":false,"usgs":false,"family":"Impecoven","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":641424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quenzer, Robert 0000-0002-1886-374X rquenzer@usgs.gov","orcid":"https://orcid.org/0000-0002-1886-374X","contributorId":4041,"corporation":false,"usgs":true,"family":"Quenzer","given":"Robert","email":"rquenzer@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":641425,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maiersperger, Tom 0000-0003-3132-6997 tmaiersperger@usgs.gov","orcid":"https://orcid.org/0000-0003-3132-6997","contributorId":3693,"corporation":false,"usgs":true,"family":"Maiersperger","given":"Tom","email":"tmaiersperger@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":641426,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meyer, David J.","contributorId":149174,"corporation":false,"usgs":false,"family":"Meyer","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":641427,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70160156,"text":"70160156 - 2015 - GOES-derived fog and low cloud indices for coastal north and central California ecological analyses","interactions":[],"lastModifiedDate":"2016-06-17T11:21:37","indexId":"70160156","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"GOES-derived fog and low cloud indices for coastal north and central California ecological analyses","docAbstract":"Fog and low cloud cover (FLCC) changes the water, energy, and nutrient flux of coastal ecosystems. Easy-to-use FLCC data are needed to quantify the impacts of FLC on ecosystem dynamics during hot, dry Mediterranean climate summers. FLCC indices were generated from 26,000 hourly night and day FLCC maps derived from Geostationary Environmental Operational Satellite (GOES) data for June, July, August, and September, 1999- 2009 for coastal California, latitude 34.50°N, south of Monterey Bay, to latitude 41.95°N, north of Crescent City. Monthly FLCC average hours per day (h/d) range from < 2 to 18. Average FLCC over the ocean increases from north (9 h/d) to south (14 h/d) whereas FLCC over land is reversed. Over land, FLCC is highest where land juts into the prevailing NW winds and is lowest in the lee of major capes. FLCC advects furthest inland through low-lying NW ocean-facing valleys. At night hours of FLCC is higher more frequently on land than over the ocean. Interannual FLCC coefficient of variation shows long term geographic stability strongly associated with landform position. Contours delineating homogeneous zones of FLCC, derived from average decadal h/d FLCC, provide data to refine the commonly used term ‘fog belt.’ FLCC indices are available for download from the California Landscape Conservation Cooperative Climate Commons website. FLCC indices can be used to improve analyses of biogeographic and bioclimatic species distribution models, meteorological mechanisms driving FLCC patterns, ecohydrological investigations of evapotranspiration, solar energy feasibility studies, agricultural irrigation demand and viticultural ripening models.
","language":"English","publisher":"John Wiley & Sons","publisherLocation":"Hoboken, NJ","doi":"10.1002/2015EA000119","usgsCitation":"Torregrosa, A.A., Combs, C., and Peters, J., 2015, GOES-derived fog and low cloud indices for coastal north and central California ecological analyses: Earth and Space Science, v. 3, no. 2, p. 46-67, https://doi.org/10.1002/2015EA000119.","productDescription":"22 p.","startPage":"46","endPage":"67","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059929","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471785,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015ea000119","text":"Publisher Index Page"},{"id":323876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-04","publicationStatus":"PW","scienceBaseUri":"57651f34e4b07657d19c78a1","contributors":{"authors":[{"text":"Torregrosa, Alicia A. 0000-0001-7361-2241 atorregrosa@usgs.gov","orcid":"https://orcid.org/0000-0001-7361-2241","contributorId":3471,"corporation":false,"usgs":true,"family":"Torregrosa","given":"Alicia","email":"atorregrosa@usgs.gov","middleInitial":"A.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":582024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Combs, Cindy","contributorId":150538,"corporation":false,"usgs":false,"family":"Combs","given":"Cindy","email":"","affiliations":[{"id":18046,"text":"2Cooperative Institute for Research in the Atmosphere; Colorado State University, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":582025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":582026,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176457,"text":"70176457 - 2015 - In-situ arsenic removal during groundwater recharge through unsaturated alluvium","interactions":[],"lastModifiedDate":"2016-09-14T15:52:30","indexId":"70176457","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"In-situ arsenic removal during groundwater recharge through unsaturated alluvium","docAbstract":"OBJECTIVES
The purpose of this study was to determine the feasibility and sustainability of in-situ removal of arsenic from water infiltrated through unsaturated alluvium.
BACKGROUND
Arsenic is naturally present in aquifers throughout the southwestern United States and elsewhere. In January 2006, the U.S. Environmental Protection Agency (EPA) lowered the Maximum Contaminant Level (MCL) for arsenic from 50 to 10 micrograms per liter (g/L). This raised concerns about naturally-occurring arsenic in groundwater. Although commercially available systems using sorbent iron or aluminum oxide resins are available to treat high-arsenic water, these systems are expensive to build and operate, and may generate hazardous waste.
Iron and aluminum oxides occur naturally on the surfaces of mineral grains that compose alluvial aquifers. In areas where alluvial deposits are unsaturated, these oxides may sorb arsenic in the same manner as commercial resins, potentially providing an effective low-cost alternative to commercially engineered treatment systems.
APPROACH
The Antelope Valley within the Mojave Desert of southern California contains a shallow water-table aquifer with arsenic concentrations of 5 g/L, and a deeper aquifer with arsenic concentrations of 30 g/L. Water was pumped from the deep aquifer into a pond and infiltrated through an 80 m-thick unsaturated zone as part of field-scale and laboratory experiments to treat high-arsenic groundwater and recharge the shallow water table aquifer at the site.
The field-scale recharge experiment included the following steps: 1) construction of a recharge pond 2) test drilling for sample collection and instrument installation adjacent to the pond 3) monitoring downward migration of water infiltrated from the pond 4) monitoring changes in selected trace-element concentrations as water infiltrated through the unsaturated zone
Data from instruments within the borehole adjacent to the pond were supplemented with borehole and surface geophysical data to evaluate the lateral spreading of water as it moved downward through the unsaturated zone.
Three laboratory studies were undertaken. Sequential extraction was used to evaluate the abundance of iron, aluminum, and manganese oxides and selected trace elements on operationally defined sites on the surfaces of mineral grains collected before and after infiltration from the pond. Secondly, radio-labeled arsenic-73 microcosm experiments evaluated the potential for incorporation of arsenic sorbed to exchange sites on mineral grains into less reactive crystalline mineral structures with time. Finally, column studies evaluated arsenic sorption and the pH dependence of sorption for selected unsaturated zone materials.
RESULTS/CONCLUSIONS
Between December 2010 and July 2012, more than 120,000 cubic meters (m3 ) (about 97 acre-feet) of high-arsenic groundwater was pumped from the deep aquifer into a 0.11 hectare (about 0.27 acres) pond and infiltrated though an 80-meter (about 260 feet) thick unsaturated zone to recharge a water-table aquifer.
Arsenic concentrations were lowered from 30 to 2 g/L as water infiltrated though the unsaturated zone at the site. Some uranium, possibly associated with past agricultural land use at the site, was mobilized to concentrations as high as 66 g/L within the unsaturated zone during the experiment. Uranium was resorbed and the high uranium concentrations did not reach the water table at the site. Concentrations of other trace elements, including antimony, chromium, vanadium, and selenium were low throughout the study.
Infiltration rates from the pond were as high as 0.4 meters per day (1.1 feet per day, ft/d), and the wetting front moved downward about 25 centimeters per day (cm/d) (0.8 ft/d) to a depth of about 50 m (about 165 feet). Clay layers at that depth slowed the downward movement of the wetting front to about 5 cm/d (0.16 ft/d). Lateral movement of the wetting front was monitored using sequential direct-current (DC) surface and sequential electromagnetic (EM) and DC borehole resistivity. Most lateral movement occurred on a clay layer about 50 m (about 165 feet) below land surface. Infiltrated water reached the water table in January 2013. At the water table, the “wetted footprint” of water infiltrated from the pond, indicated by surface resistivity data, was about 13 hectares (about 32 acres). On the basis of data collected at the site, there is enough sorbent material to operate this pond and treat groundwater having an arsenic concentration of 30 g/L to 2 g/L for about 500 years. Toxicity Characteristic Leaching Procedure (TCLP) data showed arsenic concentrations to be below hazardous levels beneath the pond after the experiment. Pond maintenance may be required to keep infiltration rates high, and prevent accumulation of organic material on the pond bottom, although organic material on the pond bottom may increase removal of other trace elements in infiltrated water including chromium, selenium, and vanadium.
Laboratory results are consistent with the field data and show sorption of arsenic in 10 cm (0.3 feet) columns to about 2 g/L over a pH range of 6 to 8, and at influent arsenic concentrations as high as 300 g/L, without breakthrough in 50 pore volumes. Column results suggest that the insitu treatment may remove arsenic in a range of hydrogeologic settings, and would not necessarily be restricted to alkaline alluvial aquifers common throughout the southwestern United States. Radiolabeled arsenic-73 experiments show that although arsenic is initially weakly sorbed (and potentially mobile), with time arsenic is incorporated into amorphous materials. One year after sorption onto surface exchange sites, most sorbed arsenic is incorporated into crystalline oxide minerals on the surfaces of primary mineral grains and is less mobile.
Results of the study suggest that long-term land use restrictions on sites used for in-situ treatment of arsenic may not be needed to control water applied to surface materials. This minimizes some regulatory concerns about future land use at sites used for in-situ arsenic treatment. However, future land uses that may alter reduction-oxidation conditions in the subsurface should be avoided, such as infiltration of stormwater recharge or recharge with other water having high organic carbon concentrations (including unsewered residential land use, dairy or other confined animal operations).
","language":"English","publisher":"Water Resource Foundation","usgsCitation":"O’Leary, D., Izbicki, J.A., Kim, T., Ajawani, C., Suarez, D., Barnes, T., Kulp, T., Burgess, M.K., and Tseng, I., 2015, In-situ arsenic removal during groundwater recharge through unsaturated alluvium, v. 4299, xix, 59 p.","productDescription":"xix, 59 p.","numberOfPages":"80","ipdsId":"IP-046006","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":328658,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328657,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.waterrf.org/Pages/Projects.aspx?PID=4299"}],"volume":"4299","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57da74b4e4b090824ffb7e4e","contributors":{"authors":[{"text":"O’Leary, David 0000-0001-9888-1739 doleary@usgs.gov","orcid":"https://orcid.org/0000-0001-9888-1739","contributorId":139900,"corporation":false,"usgs":true,"family":"O’Leary","given":"David","email":"doleary@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":648814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Izbicki, John A. 0000-0003-0816-4408 jaizbick@usgs.gov","orcid":"https://orcid.org/0000-0003-0816-4408","contributorId":152474,"corporation":false,"usgs":true,"family":"Izbicki","given":"John","email":"jaizbick@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":648815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kim, T.J.","contributorId":174624,"corporation":false,"usgs":false,"family":"Kim","given":"T.J.","email":"","affiliations":[{"id":27483,"text":"LA County Department of Public Works","active":true,"usgs":false}],"preferred":false,"id":648816,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ajawani, Clark","contributorId":174625,"corporation":false,"usgs":false,"family":"Ajawani","given":"Clark","email":"","affiliations":[{"id":27483,"text":"LA County Department of Public Works","active":true,"usgs":false}],"preferred":false,"id":648817,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Suarez, Donald","contributorId":174626,"corporation":false,"usgs":false,"family":"Suarez","given":"Donald","email":"","affiliations":[{"id":27484,"text":"U.S. Dept. of Agriculture Soil Salinity Laboratory","active":true,"usgs":false}],"preferred":false,"id":648818,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnes, Thomas","contributorId":174627,"corporation":false,"usgs":false,"family":"Barnes","given":"Thomas","email":"","affiliations":[{"id":27485,"text":"Antelope Valley East Kern Water District","active":true,"usgs":false}],"preferred":false,"id":648819,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kulp, Thomas","contributorId":174628,"corporation":false,"usgs":false,"family":"Kulp","given":"Thomas","email":"","affiliations":[{"id":27486,"text":"State University of New York, Binghampton","active":true,"usgs":false}],"preferred":false,"id":648820,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Burgess, Matthew K. 0000-0002-2828-8910 mburgess@usgs.gov","orcid":"https://orcid.org/0000-0002-2828-8910","contributorId":2115,"corporation":false,"usgs":true,"family":"Burgess","given":"Matthew","email":"mburgess@usgs.gov","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":648821,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tseng, Iwen","contributorId":174629,"corporation":false,"usgs":false,"family":"Tseng","given":"Iwen","email":"","affiliations":[{"id":27487,"text":"County of Los Angeles Department of Public Works, Alhambra, CA","active":true,"usgs":false}],"preferred":false,"id":648822,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70173564,"text":"70173564 - 2015 - Breeding habitat associations and predicted distribution of an obligate tundra-breeding bird, Smith's Longspur","interactions":[],"lastModifiedDate":"2016-06-13T15:27:01","indexId":"70173564","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Breeding habitat associations and predicted distribution of an obligate tundra-breeding bird, Smith's Longspur","docAbstract":"Smith's Longspur (Calcarius pictus) is a species of conservation concern which breeds in Arctic habitats that are expected to be especially vulnerable to climate change. We used bird presence and habitat data from point-transect surveys conducted at 12 sites across the Brooks Range, Alaska, 2003–2009, to identify breeding areas, describe local habitat associations, and identify suitable habitat using a predictive model of Smith's Longspur distribution. Smith's Longspurs were observed at seven sites, where they were associated with a variety of sedge–shrub habitats composed primarily of mosses, sedges, tussocks, and dwarf shrubs; erect shrubs were common but sparse. Nonmetric multidimensional scaling ordination of ground cover revealed positive associations of Smith's Longspur presence with sedges and mosses and a negative association with high cover of shrubs. To model predicted distribution, we used boosted regression trees to relate landscape variables to occurrence. Our model predicted that Smith's Longspurs may occur in valleys and foothills of the northeastern and southeastern mountains and in upland plateaus of the western mountains, and farther west than currently documented, over a predicted area no larger than 15% of the Brooks Range. With climate change, shrubs are expected to grow larger and denser, while soil moisture and moss cover are predicted to decrease. These changes may reduce Smith's Longspur habitat quality and limit distribution in the Brooks Range to poorly drained lowlands and alpine plateaus where sedge–shrub tundra is likely to persist. Conversely, northward advance of shrubs into sedge tundra may create suitable habitat, thus supporting a northward longspur distribution shift.
","language":"English","publisher":"Cooper Ornithological Society","doi":"10.1650/CONDOR-14-77.1","usgsCitation":"Wild, T.C., Kendall, S.J., Guldager, N., and Powell, A.N., 2015, Breeding habitat associations and predicted distribution of an obligate tundra-breeding bird, Smith's Longspur: The Condor, v. 117, no. 1, p. 3-17, https://doi.org/10.1650/CONDOR-14-77.1.","productDescription":"15 p.","startPage":"3","endPage":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056888","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575fd92be4b04f417c2baa07","contributors":{"authors":[{"text":"Wild, Teri C.","contributorId":171769,"corporation":false,"usgs":false,"family":"Wild","given":"Teri","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":638597,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, Steven J.","contributorId":30911,"corporation":false,"usgs":false,"family":"Kendall","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":638598,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guldager, Nikki","contributorId":101981,"corporation":false,"usgs":true,"family":"Guldager","given":"Nikki","email":"","affiliations":[],"preferred":false,"id":638599,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powell, Abby N. 0000-0002-9783-134X abby_powell@usgs.gov","orcid":"https://orcid.org/0000-0002-9783-134X","contributorId":171426,"corporation":false,"usgs":true,"family":"Powell","given":"Abby","email":"abby_powell@usgs.gov","middleInitial":"N.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637346,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70134261,"text":"70134261 - 2015 - Developing in situ non-destructive estimates of crop biomass to address issues of scale in remote sensing","interactions":[],"lastModifiedDate":"2016-07-08T12:57:46","indexId":"70134261","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Developing in situ non-destructive estimates of crop biomass to address issues of scale in remote sensing","docAbstract":"Ecologists often fit models to survey data to estimate and explain variation in animal abundance. Such models typically require that animal density remains constant across the landscape where sampling is being conducted, a potentially problematic assumption for animals inhabiting dynamic landscapes or otherwise exhibiting considerable spatiotemporal variation in density. We review several concepts from the burgeoning literature on spatiotemporal statistical models, including the nature of the temporal structure (i.e., descriptive or dynamical) and strategies for dimension reduction to promote computational tractability. We also review several features as they specifically relate to abundance estimation, including boundary conditions, population closure, choice of link function, and extrapolation of predicted relationships to unsampled areas. We then compare a suite of novel and existing spatiotemporal hierarchical models for animal count data that permit animal density to vary over space and time, including formulations motivated by resource selection and allowing for closed populations. We gauge the relative performance (bias, precision, computational demands) of alternative spatiotemporal models when confronted with simulated and real data sets from dynamic animal populations. For the latter, we analyze spotted seal (Phoca largha) counts from an aerial survey of the Bering Sea where the quantity and quality of suitable habitat (sea ice) changed dramatically while surveys were being conducted. Simulation analyses suggested that multiple types of spatiotemporal models provide reasonable inference (low positive bias, high precision) about animal abundance, but have potential for overestimating precision. Analysis of spotted seal data indicated that several model formulations, including those based on a log-Gaussian Cox process, had a tendency to overestimate abundance. By contrast, a model that included a population closure assumption and a scale prior on total abundance produced estimates that largely conformed to our a priori expectation. Although care must be taken to tailor models to match the study population and survey data available, we argue that hierarchical spatiotemporal statistical models represent a powerful way forward for estimating abundance and explaining variation in the distribution of dynamical populations.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/14-0959.1","usgsCitation":"Conn, P.B., Johnson, D.S., Ver Hoef, J.M., Hooten, M., London, J.M., and Boveng, P.L., 2015, Using spatiotemporal statistical models to estimate animal abundance and infer ecological dynamics from survey counts: Ecological Monographs, v. 85, no. 2, p. 235-252, https://doi.org/10.1890/14-0959.1.","productDescription":"18 p.","startPage":"235","endPage":"252","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057148","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"85","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57594238e4b04f417c2569e2","contributors":{"authors":[{"text":"Conn, Paul B.","contributorId":87440,"corporation":false,"usgs":true,"family":"Conn","given":"Paul","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":637825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":167773,"corporation":false,"usgs":false,"family":"Johnson","given":"Devin","email":"","middleInitial":"S.","affiliations":[{"id":24829,"text":"National Marine Mammal Laboratory, Alaska Fisheries Science Center, National Marine Fisheries Service, NOAA, Seattle, Washington","active":true,"usgs":false}],"preferred":false,"id":637826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ver Hoef, Jay M.","contributorId":42504,"corporation":false,"usgs":true,"family":"Ver Hoef","given":"Jay","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":637827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":637475,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"London, Joshua M.","contributorId":171522,"corporation":false,"usgs":false,"family":"London","given":"Joshua","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":637828,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boveng, Peter L.","contributorId":171523,"corporation":false,"usgs":false,"family":"Boveng","given":"Peter","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":637829,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70162211,"text":"70162211 - 2015 - Factors affecting defensive strike behavior in Brown Treesnakes (Boiga irregularis) provoked by humans","interactions":[],"lastModifiedDate":"2016-01-20T13:54:44","indexId":"70162211","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"title":"Factors affecting defensive strike behavior in Brown Treesnakes (Boiga irregularis) provoked by humans","docAbstract":"Striking is a typical antipredator defense exhibited by many species of snakes. While trapping Brown Treesnakes (Boiga irregularis) on Guam, we observed that snakes most frequently struck at an approaching person at a site where snakes had been trapped, marked, and handled in the past. Using a combination of between-sites and within-site comparisons, we assessed if the propensity to strike was correlated with capture histories (both recent and long-term), snake size, body condition (a proxy to nutritional stress), sex, or tail condition (broken or intact), while controlling for confounding variables. We confirmed that propensity to strike was higher at the site where we had been conducting capture-mark-recapture for several years. However, we were unable to demonstrate a correlation between striking tendencies and individual recent or long-term capture histories. The only morphological covariate that had an effect on strike propensity was sex, with females striking more often than males. After removing the site effect from our model, we found that snakes missing parts of their tails were more likely to strike than snakes with intact tails. We have yet to identify the factor(s) that cause the pronounced difference across sites in snake propensity to strike, and data from additional sites might help elucidate any geographical patterns.
","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Spencer, M.M., Lardner, B., Mazurek, M., and Reed, R., 2015, Factors affecting defensive strike behavior in Brown Treesnakes (Boiga irregularis) provoked by humans: Herpetological Conservation and Biology, v. 10, no. 2, p. 703-710.","productDescription":"8 p.","startPage":"703","endPage":"710","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057633","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":314539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":314439,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/contents_vol10_issue2.html"}],"volume":"10","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56a0bdc8e4b0961cf280dc1c","contributors":{"authors":[{"text":"Spencer, McKayka M.","contributorId":152307,"corporation":false,"usgs":false,"family":"Spencer","given":"McKayka","email":"","middleInitial":"M.","affiliations":[{"id":18904,"text":"Cherokee Services Group, Brown Treesnake Project, Dededo, GU 96912","active":true,"usgs":false}],"preferred":false,"id":588867,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lardner, Bjorn lardnerb@usgs.gov","contributorId":5546,"corporation":false,"usgs":true,"family":"Lardner","given":"Bjorn","email":"lardnerb@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":588868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mazurek, M.J.","contributorId":25066,"corporation":false,"usgs":true,"family":"Mazurek","given":"M.J.","affiliations":[],"preferred":false,"id":588869,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reed, Robert N. reedr@usgs.gov","contributorId":1686,"corporation":false,"usgs":true,"family":"Reed","given":"Robert N.","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":588866,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173664,"text":"70173664 - 2015 - On the existence of maximum likelihood estimates for presence-only data","interactions":[],"lastModifiedDate":"2016-06-08T10:10:52","indexId":"70173664","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","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":"On the existence of maximum likelihood estimates for presence-only data","docAbstract":"Historically unprecedented drought in California has brought water issues to the forefront of the nation’s attention. Crucial investigations that concern water policy, management, and research, in turn, require extensive information about the quality and quantity of California’s water. Unfortunately, key sources of pertinent data are unevenly distributed and frequently hard to find. Thankfully, the vital importance of integrating water data across federal, state, and tribal, academic, and private entities, has recently been recognized and addressed through federal initiatives such as the Climate Data Initiative of President Obama’s Climate Action Plan and the Advisory Committee on Water Information’sOpen Water Data Initiative. Here, we demonstrate an application of integrated open water data, visualized and made available online using open source software, for the purpose of exploring the impact of the current California drought. Our collaborative approach and technical tools enabled a rapid, distributed development process. Many positive outcomes have resulted: the application received recognition within and outside of the Federal Government, inspired others to visualize open water data, spurred new collaborations for our group, and strengthened the collaborative relationships within the team of developers. In this article, we describe the technical tools and collaborative process that enabled the success of the application.
","language":"English","usgsCitation":"Read, E.K., Bucknell, M., Hines, M., Kreft, J., Lucido, J., Read, J.S., Schroedl, C., Sibley, D.M., Stephan, S., Suftin, I., Thongsavanh, P., Van Den Hoek, J., Walker, J.I., Wernimont, M.R., Winslow, L., and Yan, A.N., 2015, New insight into California’s drought through open data: BayGEO Journal, v. 8, no. 1, HTML Document.","productDescription":"HTML Document","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065881","costCenters":[],"links":[{"id":323875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":312354,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://journal.baygeo.org/new-insight-into-californias-drought-through-open-data/"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57651f39e4b07657d19c790a","contributors":{"authors":[{"text":"Read, Emily K. 0000-0002-9617-9433 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Analytics","active":false,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":582388,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Winslow, Luke A. lwinslow@usgs.gov","contributorId":150344,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke A.","email":"lwinslow@usgs.gov","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":false,"id":582389,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Yan, Andrew N. ayan@usgs.gov","contributorId":5648,"corporation":false,"usgs":true,"family":"Yan","given":"Andrew","email":"ayan@usgs.gov","middleInitial":"N.","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":582390,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70176497,"text":"70176497 - 2015 - A 2-D process-based model for suspended sediment dynamics: A first step towards ecological modeling","interactions":[],"lastModifiedDate":"2016-09-19T14:35:11","indexId":"70176497","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A 2-D process-based model for suspended sediment dynamics: A first step towards ecological modeling","docAbstract":"In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions.
This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011.
Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.
Hexavalent chromium, Cr(VI), in 918 wells sampled throughout California between 2004 and 2012 by the Groundwater Ambient Monitoring and Assessment-Priority Basin Project (GAMA-PBP) ranged from less than the study reporting limit of 1 microgram per liter (μg/L) to 32 μg/L. Statewide, Cr(VI) was reported in 31 percent of wells and equaled or exceeded the recently established (2014) California Maximum Contaminant Level (MCL) for Cr(VI) of 10 μg/L in 4 percent of wells. Cr(VI) data collected for regulatory purposes overestimated Cr(VI) occurrence compared to spatially-distributed GAMA-PBP data. Ninety percent of chromium was present as Cr(VI), which was detected more frequently and at higher concentrations in alkaline (pH ≥ 8), oxic water; and more frequently in agricultural and urban land uses compared to native land uses. Chemical, isotopic (tritium and carbon-14), and noble-gas data show high Cr(VI) in water from wells in alluvial aquifers in the southern California deserts result from long groundwater-residence times and geochemical reactions such as silicate weathering that increase pH, while oxic conditions persist. High Cr(VI) in water from wells in alluvial aquifers along the west-side of the Central Valley results from high-chromium in source rock eroded to form those aquifers, and areal recharge processes (including irrigation return) that can mobilize chromium from the unsaturated zone. Cr(VI) co-occurred with oxyanions having similar chemistry, including vanadium, selenium, and uranium. Cr(VI) was positively correlated with nitrate, consistent with increased concentrations in areas of agricultural land use and mobilization of chromium from the unsaturated zone by irrigation return.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2015.08.007","usgsCitation":"Izbicki, J.A., Wright, M., Seymour, W.A., McCleskey, R.B., Fram, M.S., Belitz, K., and Esser, B.K., 2015, Cr(VI) occurrence and geochemistry in water from public-supply wells in California: Applied Geochemistry, v. 63, p. 203-217, https://doi.org/10.1016/j.apgeochem.2015.08.007.","productDescription":"15 p.","startPage":"203","endPage":"217","ipdsId":"IP-060886","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":471517,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2015.08.007","text":"Publisher Index Page"},{"id":328634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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The Italian Space Agency’s COSMO–SkyMed Synthetic Aperture Radar (SAR) satellite acquired data over Kathmandu area four days after the earthquake and the Japan Aerospace Exploration Agency’s Advanced Land Observing Satellite-2 SAR satellite for larger area nine days after the mainshock. We used these radar observations and rapidly produced damage proxy maps (DPMs) derived from temporal changes in Interferometric SAR coherence. Our DPMs were qualitatively validated through comparison with independent damage analyses by the National Geospatial-Intelligence Agency and the United Nations Institute for Training and Research’s United Nations Operational Satellite Applications Programme, and based on our own visual inspection of DigitalGlobe’s WorldView optical pre- versus postevent imagery. Our maps were quickly released to responding agencies and the public, and used for damage assessment, determining inspection/imaging priorities, and reconnaissance fieldwork.
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We used data from the North American Breeding Bird Survey (BBS) to document changes in the distributional limits of the western Burrowing Owl (Athene cunicularia hypugaea) from 1967 to 2008. We used logistic regression to model presence probability (p) as a function of longitude, latitude, and year. We modeled a linear trend in logit(p) through time with slope and intercept modeled as a double Fourier series of longitude and latitude. We found that the western Burrowing Owl has experienced an intriguing southward shift in the northern half of its breeding range, contrary to what is predicted by most species niche models and what has been observed for many other species in North America. The breeding range of the Burrowing Owl has been shrinking near its northern, western, and eastern edges. 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","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2014-06-148","usgsCitation":"Jacques, C.N., Jenks, J., Grovenburg, T.W., Klaver, R.W., and Dubay, S.A., 2015, Influence of ecological factors on prevalence of meningeal worm (Parelaphostrongylus tenuis infection in South Dakota, USA: Journal of Wildlife Diseases, v. 51, no. 2, p. 332-340, https://doi.org/10.7589/2014-06-148.","productDescription":"9 p.","startPage":"332","endPage":"340","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051887","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South 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W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637430,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dubay, Shelli A.","contributorId":171437,"corporation":false,"usgs":false,"family":"Dubay","given":"Shelli","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":637434,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173681,"text":"70173681 - 2015 - Evidence from data storage tags for the presence of lunar and semilunar behavioral cycles in spawning Atlantic 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Unfortunately it has proven difficult to comprehensively study the reproductive behavior of broadcast-spawning fishes. The use of electronic data storage tags (DSTs) has the potential to provide insights into the behavior of fishes. These tags allow for data collection over relatively large spatial and temporal scales that can be correlated to predicted environmental conditions and ultimately be used to refine predictions of year class strength. In this paper we present data retrieved from DSTs demonstrating that events putatively identified as Atlantic cod spawning behavior is tied to a lunar cycle with a pronounced semi-lunar cycle within it. Peak activity occurs around the full and new moon with no evidence of relationship with day/night cycles.
","language":"English","publisher":"Springer","doi":"10.1007/s10641-015-0396-2","usgsCitation":"Grabowski, T.B., McAdam, B.J., Thorsteinsson, V., and Marteinsdottir, G., 2015, Evidence from data storage tags for the presence of lunar and semilunar behavioral cycles in spawning Atlantic cod: Environmental Biology of Fishes, v. 98, no. 7, p. 1767-1776, https://doi.org/10.1007/s10641-015-0396-2.","productDescription":"10 p.","startPage":"1767","endPage":"1776","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057832","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":324147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"7","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-20","publicationStatus":"PW","scienceBaseUri":"576a6538e4b07657d1a11d9b","contributors":{"authors":[{"text":"Grabowski, Timothy B. 0000-0001-9763-8948 tgrabowski@usgs.gov","orcid":"https://orcid.org/0000-0001-9763-8948","contributorId":4178,"corporation":false,"usgs":true,"family":"Grabowski","given":"Timothy","email":"tgrabowski@usgs.gov","middleInitial":"B.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":637489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAdam, Bruce J.","contributorId":141038,"corporation":false,"usgs":false,"family":"McAdam","given":"Bruce","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":640107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thorsteinsson, Vilhjalmur","contributorId":49215,"corporation":false,"usgs":true,"family":"Thorsteinsson","given":"Vilhjalmur","email":"","affiliations":[],"preferred":false,"id":640108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marteinsdottir, Gudrun","contributorId":11099,"corporation":false,"usgs":false,"family":"Marteinsdottir","given":"Gudrun","email":"","affiliations":[],"preferred":false,"id":640109,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173741,"text":"70173741 - 2015 - Evaluating multi-level models to test occupancy state responses of Plethodontid salamanders","interactions":[],"lastModifiedDate":"2016-06-08T14:14:24","indexId":"70173741","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating multi-level models to test occupancy state responses of Plethodontid salamanders","docAbstract":"Plethodontid salamanders are diverse and widely distributed taxa and play critical roles in ecosystem processes. Due to salamander use of structurally complex habitats, and because only a portion of a population is available for sampling, evaluation of sampling designs and estimators is critical to provide strong inference about Plethodontid ecology and responses to conservation and management activities. We conducted a simulation study to evaluate the effectiveness of multi-scale and hierarchical single-scale occupancy models in the context of a Before-After Control-Impact (BACI) experimental design with multiple levels of sampling. Also, we fit the hierarchical single-scale model to empirical data collected for Oregon slender and Ensatina salamanders across two years on 66 forest stands in the Cascade Range, Oregon, USA. All models were fit within a Bayesian framework. Estimator precision in both models improved with increasing numbers of primary and secondary sampling units, underscoring the potential gains accrued when adding secondary sampling units. Both models showed evidence of estimator bias at low detection probabilities and low sample sizes; this problem was particularly acute for the multi-scale model. Our results suggested that sufficient sample sizes at both the primary and secondary sampling levels could ameliorate this issue. Empirical data indicated Oregon slender salamander occupancy was associated strongly with the amount of coarse woody debris (posterior mean = 0.74; SD = 0.24); Ensatina occupancy was not associated with amount of coarse woody debris (posterior mean = -0.01; SD = 0.29). Our simulation results indicate that either model is suitable for use in an experimental study of Plethodontid salamanders provided that sample sizes are sufficiently large. However, hierarchical single-scale and multi-scale models describe different processes and estimate different parameters. As a result, we recommend careful consideration of study questions and objectives prior to sampling data and fitting models.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0142903","usgsCitation":"Kroll, A.J., Garcia, T.S., Jones, J., Dugger, K., Murden, B., Johnson, J., Peerman, S., Brintz, B., and Rochelle, M., 2015, Evaluating multi-level models to test occupancy state responses of Plethodontid salamanders: PLoS ONE, v. 10, no. 11, e0142903; 19 p., https://doi.org/10.1371/journal.pone.0142903.","productDescription":"e0142903; 19 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066731","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471514,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0142903","text":"Publisher Index Page"},{"id":323290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-30","publicationStatus":"PW","scienceBaseUri":"575941e1e4b04f417c256833","contributors":{"authors":[{"text":"Kroll, Andrew J.","contributorId":171590,"corporation":false,"usgs":false,"family":"Kroll","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":638044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Tiffany S.","contributorId":171591,"corporation":false,"usgs":false,"family":"Garcia","given":"Tiffany","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":638045,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Jay E.","contributorId":171592,"corporation":false,"usgs":false,"family":"Jones","given":"Jay E.","affiliations":[],"preferred":false,"id":638046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":638037,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murden, Blake","contributorId":171593,"corporation":false,"usgs":false,"family":"Murden","given":"Blake","email":"","affiliations":[],"preferred":false,"id":638047,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Josh","contributorId":171594,"corporation":false,"usgs":false,"family":"Johnson","given":"Josh","email":"","affiliations":[],"preferred":false,"id":638048,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peerman, Summer","contributorId":171595,"corporation":false,"usgs":false,"family":"Peerman","given":"Summer","email":"","affiliations":[],"preferred":false,"id":638049,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brintz, Ben","contributorId":171596,"corporation":false,"usgs":false,"family":"Brintz","given":"Ben","email":"","affiliations":[],"preferred":false,"id":638050,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rochelle, Michael","contributorId":171597,"corporation":false,"usgs":false,"family":"Rochelle","given":"Michael","email":"","affiliations":[],"preferred":false,"id":638051,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70155945,"text":"70155945 - 2015 - Towards forecasting the retreat of California’s coastal cliffs during the 21st century","interactions":[],"lastModifiedDate":"2021-01-14T19:01:27.700656","indexId":"70155945","displayToPublicDate":"2015-12-31T12:56:33","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Towards forecasting the retreat of California’s coastal cliffs during the 21st century","docAbstract":"In California, sea-level rise during the 21st century threatens to accelerate coastal cliff recession rates. To forecast such changes for managers and policymakers, models must play a key role. In this paper, we extend a ~70-year long dataset of measured historic sea cliff retreat rates in Southern California into the 21st century using a suite of simple analytical and empirical models. Ensemble results suggest that coastal cliff recession rates could increase on average by 0.09-0.22 m yr-1 for a 0.5-1.0 m rise in sea level by 2100, 27-67% faster than historical rates. The basic models used herein will serve as a baseline against which more complex, process-based and statistical (Bayesian) forecasts will be compared. The application of different models, with varying levels of detail, to the same geomorphic problem will provide a comprehensive forecast and address the question of how to reduce model complexity while minimizing uncertainty.
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