{"pageNumber":"640","pageRowStart":"15975","pageSize":"25","recordCount":46677,"records":[{"id":70046804,"text":"70046804 - 2012 - Analysis options for estimating status and trends in long-term monitoring","interactions":[],"lastModifiedDate":"2013-08-28T13:30:39","indexId":"70046804","displayToPublicDate":"2012-01-01T13:23:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Analysis options for estimating status and trends in long-term monitoring","docAbstract":"This chapter describes methods for estimating long-term trends in ecological parameters. Other chapters in this volume discuss more advanced methods for analyzing monitoring data, but these methods may be relatively inaccessible to some readers. Therefore, this chapter provides an introduction to trend analysis for managers and biologists while also discussing general issues relevant to trend assessment in any long-term monitoring program.\n\nFor simplicity, we focus on temporal trends in population size across years. We refer to the survey results for each year as the “annual means” (e.g. mean per transect, per plot, per time period). The methods apply with little or no modification, however, to formal estimates of population size, other temporal units (e.g. a month), to spatial or other dimensions such as elevation or a north–south gradient, and to other quantities such as chemical or geological parameters. The chapter primarily discusses methods for estimating population-wide parameters rather than studying variation in trend within the population, which can be examined using methods presented in other chapters (e.g. Chapters 7, 12, 20). We begin by reviewing key concepts related to trend analysis. We then describe how to evaluate potential bias in trend estimates. An overview of the statistical models used to quantify trends is then presented. We conclude by showing ways to estimate trends using simple methods that can be implemented with spreadsheets.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Design and Analysis of Long-term Ecological Monitoring Studies","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Cambridge University Press","publisherLocation":"Cambridge, UK","doi":"10.1017/CBO9781139022422.016","isbn":"9781139022422","usgsCitation":"Bart, J., and Beyer, H.L., 2012, Analysis options for estimating status and trends in long-term monitoring, chap. <i>of</i> Design and Analysis of Long-term Ecological Monitoring Studies, p. 253-278, https://doi.org/10.1017/CBO9781139022422.016.","productDescription":"26 p.","startPage":"253","endPage":"278","numberOfPages":"26","ipdsId":"IP-029100","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":277107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277106,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1017/CBO9781139022422.016"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521f1be2e4b0f8bf2b0760ce","contributors":{"authors":[{"text":"Bart, Jonathan jon_bart@usgs.gov","contributorId":57025,"corporation":false,"usgs":true,"family":"Bart","given":"Jonathan","email":"jon_bart@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":480303,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beyer, Hawthorne L.","contributorId":99871,"corporation":false,"usgs":true,"family":"Beyer","given":"Hawthorne","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":480304,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70037937,"text":"70037937 - 2012 - Relating management practices and nutrient export in agricultural watersheds of the United States","interactions":[],"lastModifiedDate":"2013-08-05T13:30:51","indexId":"70037937","displayToPublicDate":"2012-01-01T13:22:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Relating management practices and nutrient export in agricultural watersheds of the United States","docAbstract":"Relations between riverine export (load) of total nitrogen (N) and total phosphorus (P) from 133 large agricultural watersheds in the United States and factors affecting nutrient transport were evaluated using empirical regression models. After controlling for anthropogenic inputs and other landscape factors affecting nutrient transport-such as runoff, precipitation, slope, number of reservoirs, irrigated area, and area with subsurface tile drains-the relations between export and the area in the Conservation Reserve Program (CRP) (N) and conservation tillage (P) were positive. Additional interaction terms indicated that the relations between export and the area in conservation tillage (N) and the CRP (P) progressed from being clearly positive when soil erodibility was low or moderate, to being close to zero when soil erodibility was higher, to possibly being slightly negative only at the 90th to 95th percentile of soil erodibility values. Possible explanations for the increase in nutrient export with increased area in management practices include greater transport of soluble nutrients from areas in conservation tillage; lagged response of stream quality to implementation of management practices because of nitrogen transport in groundwater, time for vegetative cover to mature, and/or prior accumulation of P in soils; or limitations in the management practice and stream monitoring data sets. If lags are occurring, current nutrient export from agricultural watersheds may still be reflecting the influence of agricultural land-use practices that were in place before the implementation of these management practices.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Environmental Quality","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Agronomy","doi":"10.2134/jeq2012.0073","usgsCitation":"Sprague, L.A., and Gronberg, J., 2012, Relating management practices and nutrient export in agricultural watersheds of the United States: Journal of Environmental Quality, v. 41, no. 6, p. 1939-1950, https://doi.org/10.2134/jeq2012.0073.","productDescription":"12 p.","startPage":"1939","endPage":"1950","numberOfPages":"12","ipdsId":"IP-036746","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":276041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276040,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2134/jeq2012.0073"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","volume":"41","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-11-01","publicationStatus":"PW","scienceBaseUri":"5200c967e4b009d47a4c23c5","contributors":{"authors":[{"text":"Sprague, Lori A. 0000-0003-2832-6662 lsprague@usgs.gov","orcid":"https://orcid.org/0000-0003-2832-6662","contributorId":726,"corporation":false,"usgs":true,"family":"Sprague","given":"Lori","email":"lsprague@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":463109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gronberg, Jo Ann M.","contributorId":18342,"corporation":false,"usgs":true,"family":"Gronberg","given":"Jo Ann M.","affiliations":[],"preferred":false,"id":463110,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043302,"text":"70043302 - 2012 - Future opportunities and challenges in remote sensing of drought","interactions":[],"lastModifiedDate":"2022-04-01T22:49:50.479918","indexId":"70043302","displayToPublicDate":"2012-01-01T13:20:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Future opportunities and challenges in remote sensing of drought","docAbstract":"The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and global efforts such as the Famine and Early Warning System (FEWS), National Integrated Drought Information System (NIDIS), and Group on Earth Observations (GEO), as well as the establishment of regional drought centers (e.g., European Drought Observatory) and geospatial visualization and monitoring systems (e.g, NASA SERVIR) have been undertaken to improve drought monitoring and early warning systems throughout the world. The suite of innovative remote sensing tools that have recently emerged will be looked upon to fill important data and knowledge gaps (NIDIS, 2007; NRC, 2007) to address a wide range of drought-related issues including food security, water scarcity, and human health.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Remote sensing of drought: innovative monitoring approaches","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","publisherLocation":"Boca Raton, FL","doi":"10.1201/b11863-23","usgsCitation":"Wardlow, B.D., Anderson, M.C., Sheffield, J., Doorn, B., Verdin, J., Zhan, X., and Rodell, M., 2012, Future opportunities and challenges in remote sensing of drought, chap. <i>of</i> Remote sensing of drought: innovative monitoring approaches, p. 389-410, https://doi.org/10.1201/b11863-23.","productDescription":"22 p.","startPage":"389","endPage":"410","ipdsId":"IP-031383","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474601,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2060/20120003712","text":"External Repository"},{"id":276693,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"520f49e1e4b0fc50304bc4b4","contributors":{"editors":[{"text":"Wardlow, Brian D.","contributorId":75845,"corporation":false,"usgs":true,"family":"Wardlow","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":509193,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Anderson, Martha C.","contributorId":96579,"corporation":false,"usgs":false,"family":"Anderson","given":"Martha","email":"","middleInitial":"C.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":509194,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Verdin, James P. 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":720,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":509192,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Wardlow, Brian D.","contributorId":75845,"corporation":false,"usgs":true,"family":"Wardlow","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":473339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Martha C.","contributorId":96579,"corporation":false,"usgs":false,"family":"Anderson","given":"Martha","email":"","middleInitial":"C.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":473341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheffield, Justin","contributorId":69462,"corporation":false,"usgs":true,"family":"Sheffield","given":"Justin","affiliations":[],"preferred":false,"id":473337,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doorn, Brad","contributorId":74288,"corporation":false,"usgs":true,"family":"Doorn","given":"Brad","email":"","affiliations":[],"preferred":false,"id":473338,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Verdin, James 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":145830,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":839357,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhan, Xiwu","contributorId":41323,"corporation":false,"usgs":true,"family":"Zhan","given":"Xiwu","email":"","affiliations":[],"preferred":false,"id":473336,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rodell, Matt","contributorId":93806,"corporation":false,"usgs":true,"family":"Rodell","given":"Matt","email":"","affiliations":[],"preferred":false,"id":473340,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70042665,"text":"70042665 - 2012 - Western pond turtle: Biology, sampling techniques, inventory and monitoring, conservation, and management: Northwest Fauna No. 7","interactions":[],"lastModifiedDate":"2013-08-14T12:55:32","indexId":"70042665","displayToPublicDate":"2012-01-01T12:52:27","publicationYear":"2012","noYear":false,"publicationType":{"id":4,"text":"Book"},"title":"Western pond turtle: Biology, sampling techniques, inventory and monitoring, conservation, and management: Northwest Fauna No. 7","docAbstract":"One of only two native, freshwater turtle species in the western United States, western pond turtles are declining in portions of their original range. Declines are mostly due to habitat loss, introduction of non-native species, pollution, and lack of connectivity among populations. USGS zoologist R. Bruce Bury and colleagues from the U.S. Forest Service, California State University, and other agencies compiled and edited a new review and field manual of this charismatic species. Objectives were to determine its current distribution and abundance, summarize and evaluate population features, review techniques to detect population and habitat changes, and improve monitoring for long-term trends. Methods described in the manual should improve consistency, efficiency, and accuracy of survey data, resulting in improved management and conservation efforts.","language":"English","publisher":"The Society for Northwestern Vertebrate Biology","usgsCitation":"2012, Western pond turtle: Biology, sampling techniques, inventory and monitoring, conservation, and management: Northwest Fauna No. 7, 128 p.","productDescription":"128 p.","ipdsId":"IP-029121","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":276602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"520ca6e9e4b081fa6136d420","contributors":{"editors":[{"text":"Bury, R.B.","contributorId":25497,"corporation":false,"usgs":true,"family":"Bury","given":"R.B.","email":"","affiliations":[],"preferred":false,"id":509166,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Welsh, Hartwell H. Jr.","contributorId":9980,"corporation":false,"usgs":true,"family":"Welsh","given":"Hartwell","suffix":"Jr.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":509165,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Germano, David J.","contributorId":91815,"corporation":false,"usgs":true,"family":"Germano","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":509167,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Ashton, Donald T.","contributorId":112537,"corporation":false,"usgs":true,"family":"Ashton","given":"Donald","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":509168,"contributorType":{"id":2,"text":"Editors"},"rank":4}]}}
,{"id":70125779,"text":"70125779 - 2012 - Tools for quantifying isotopic niche space and dietary variation at the individual and population level.","interactions":[],"lastModifiedDate":"2014-09-18T12:48:01","indexId":"70125779","displayToPublicDate":"2012-01-01T12:46:49","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Tools for quantifying isotopic niche space and dietary variation at the individual and population level.","docAbstract":"Ecologists are increasingly using stable isotope analysis to inform questions about variation in resource and habitat use from the individual to community level. In this study we investigate data sets from 2 California sea otter (<i>Enhydra lutris nereis</i>) populations to illustrate the advantages and potential pitfalls of applying various statistical and quantitative approaches to isotopic data. We have subdivided these tools, or metrics, into 3 categories: IsoSpace metrics, stable isotope mixing models, and DietSpace metrics. IsoSpace metrics are used to quantify the spatial attributes of isotopic data that are typically presented in bivariate (e.g., δ<sup>13</sup>C versus δ<sup>15</sup>N) 2-dimensional space. We review IsoSpace metrics currently in use and present a technique by which uncertainty can be included to calculate the convex hull area of consumers or prey, or both. We then apply a Bayesian-based mixing model to quantify the proportion of potential dietary sources to the diet of each sea otter population and compare this to observational foraging data. Finally, we assess individual dietary specialization by comparing a previously published technique, variance components analysis, to 2 novel DietSpace metrics that are based on mixing model output. As the use of stable isotope analysis in ecology continues to grow, the field will need a set of quantitative tools for assessing isotopic variance at the individual to community level. Along with recent advances in Bayesian-based mixing models, we hope that the IsoSpace and DietSpace metrics described here will provide another set of interpretive tools for ecologists.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Mammalogy","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Mammalogists","publisherLocation":"Provo, UT","doi":"10.1644/11-MAMM-S-187.1","usgsCitation":"Newsome, S.D., Yeakel, J.D., Wheatley, P.V., and Tinker, M.T., 2012, Tools for quantifying isotopic niche space and dietary variation at the individual and population level.: Journal of Mammalogy, v. 93, no. 2, p. 329-341, https://doi.org/10.1644/11-MAMM-S-187.1.","productDescription":"13 p.","startPage":"329","endPage":"341","numberOfPages":"13","ipdsId":"IP-029015","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":294155,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294080,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1644/11-MAMM-S-187.1"},{"id":294081,"type":{"id":15,"text":"Index Page"},"url":"https://www.bioone.org/doi/full/10.1644/11-MAMM-S-187.1"}],"volume":"93","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-04-30","publicationStatus":"PW","scienceBaseUri":"541bf45de4b0e96537ddf8dc","contributors":{"authors":[{"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":501661,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yeakel, Justin D.","contributorId":81418,"corporation":false,"usgs":true,"family":"Yeakel","given":"Justin","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":501660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wheatley, Patrick V.","contributorId":99057,"corporation":false,"usgs":true,"family":"Wheatley","given":"Patrick","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":501662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501659,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043300,"text":"70043300 - 2012 - Advances in spectroscopic methods for quantifying soil carbon","interactions":[],"lastModifiedDate":"2021-03-16T17:45:05.164699","indexId":"70043300","displayToPublicDate":"2012-01-01T12:46:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Advances in spectroscopic methods for quantifying soil carbon","docAbstract":"The current gold standard for soil carbon (C) determination is elemental C analysis using dry combustion. However, this method requires expensive consumables, is limited by the number of samples that can be processed (~100/d), and is restricted to the determination of total carbon. With increased interest in soil C sequestration, faster methods of analysis are needed, and there is growing interest in methods based on diffuse reflectance spectroscopy in the visible, near-infrared or mid-infrared spectral ranges. These spectral methods can decrease analytical requirements and speed sample processing, be applied to large landscape areas using remote sensing imagery, and be used to predict multiple analytes simultaneously. However, the methods require localized calibrations to establish the relationship between spectral data and reference analytical data, and also have additional, specific problems. For example, remote sensing is capable of scanning entire watersheds for soil carbon content but is limited to the surface layer of tilled soils and may require difficult and extensive field sampling to obtain proper localized calibration reference values. The objective of this chapter is to discuss the present state of spectroscopic methods for determination of soil carbon.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Managing agricultural greenhouse gases","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","publisherLocation":"Walthham, MA","doi":"10.1016/B978-0-12-386897-8.00020-6","usgsCitation":"Reeves, J.B., McCarty, G.W., Calderon, F., and Hively, W., 2012, Advances in spectroscopic methods for quantifying soil carbon, chap. <i>of</i> Managing agricultural greenhouse gases, p. 345-366, https://doi.org/10.1016/B978-0-12-386897-8.00020-6.","productDescription":"22 p.","startPage":"345","endPage":"366","numberOfPages":"22","ipdsId":"IP-028957","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":276686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"520f49dfe4b0fc50304bc49c","contributors":{"authors":[{"text":"Reeves, James B. III","contributorId":40693,"corporation":false,"usgs":true,"family":"Reeves","given":"James","suffix":"III","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":473330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarty, Gregory W.","contributorId":78861,"corporation":false,"usgs":true,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":473332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Calderon, Francisco","contributorId":66160,"corporation":false,"usgs":true,"family":"Calderon","given":"Francisco","email":"","affiliations":[],"preferred":false,"id":473331,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":9391,"corporation":false,"usgs":true,"family":"Hively","given":"W. Dean","affiliations":[],"preferred":false,"id":473329,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70118554,"text":"70118554 - 2012 - Molecular dynamics simulation of nitric oxide in myoglobin","interactions":[],"lastModifiedDate":"2014-07-29T11:41:30","indexId":"70118554","displayToPublicDate":"2012-01-01T11:35:50","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2423,"text":"Journal of Physical Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Molecular dynamics simulation of nitric oxide in myoglobin","docAbstract":"The infrared (IR) spectroscopy and ligand migration of photodissociated nitric oxide (NO) in and around the active sites in myoglobin (Mb) are investigated. A distributed multipolar model for open-shell systems is developed and used, which allows one to realistically describe the charge distribution around the diatomic probe molecule. The IR spectra were computed from the trajectories for two conformational substates at various temperatures. The lines are narrow (width of 3–7 cm<sup>–1</sup> at 20–100 K), in agreement with the experimental observations where they have widths of 4–5 cm<sup>–1</sup> at 4 K. It is found that within one conformational substate (B or C) the splitting of the spectrum can be correctly described compared with recent experiments. Similar to photodissociated CO in Mb, additional substates exist for NO in Mb, which are separated by barriers below 1 kcal/mol. Contrary to full quantum mechanical calculations, however, the force field and mixed QM/MM simulations do not correctly describe the relative shifts between the B- and C-states relative to gas-phase NO. Free energy simulations establish that NO preferably localizes in the distal site and the barrier for migration to the neighboring Xe4 pocket is Δ<i>G</i><sub>B→C</sub> = 1.7–2.0 kcal/mol. The reverse barrier is Δ<i>G</i><sub>B←C</sub> = 0.7 kcal/mol, which agrees well with the experimental value of 0.7 kcal/mol, estimated from kinetic data.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Physical Chemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Chemical Society","publisherLocation":"Easton, PA","doi":"10.1021/jp212112f","usgsCitation":"Lee, M.W., and Meuwly, M., 2012, Molecular dynamics simulation of nitric oxide in myoglobin: Journal of Physical Chemistry, v. 116, no. 14, p. 4154-4162, https://doi.org/10.1021/jp212112f.","productDescription":"9 p.","startPage":"4154","endPage":"4162","numberOfPages":"9","costCenters":[],"links":[{"id":291291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291289,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/jp212112f"}],"volume":"116","issue":"14","noUsgsAuthors":false,"publicationDate":"2012-03-28","publicationStatus":"PW","scienceBaseUri":"57f7f556e4b0bc0bec0a15ad","contributors":{"authors":[{"text":"Lee, Myung Won","contributorId":58950,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"","middleInitial":"Won","affiliations":[],"preferred":false,"id":496997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meuwly, Markus","contributorId":79408,"corporation":false,"usgs":true,"family":"Meuwly","given":"Markus","email":"","affiliations":[],"preferred":false,"id":496998,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70048257,"text":"70048257 - 2012 - Extreme events, trends, and variability in Northern Hemisphere lake-ice phenology (1855-2005)","interactions":[],"lastModifiedDate":"2013-09-19T11:38:41","indexId":"70048257","displayToPublicDate":"2012-01-01T11:33:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Extreme events, trends, and variability in Northern Hemisphere lake-ice phenology (1855-2005)","docAbstract":"Often extreme events, more than changes in mean conditions, have the greatest impact on the environment and human well-being. Here we examine changes in the occurrence of extremes in the timing of the annual formation and disappearance of lake ice in the Northern Hemisphere. Both changes in the mean condition and in variability around the mean condition can alter the probability of extreme events. Using long-term ice phenology data covering two periods 1855–6 to 2004–5 and 1905–6 to 2004–5 for a total of 75 lakes, we examined patterns in long-term trends and variability in the context of understanding the occurrence of extreme events. We also examined patterns in trends for a 30-year subset (1975–6 to 2004–5) of the 100-year data set. Trends for ice variables in the recent 30-year period were steeper than those in the 100- and 150-year periods, and trends in the 150-year period were steeper than in the 100-year period. Ranges of rates of change (days per decade) among time periods based on linear regression were 0.3−1.6 later for freeze, 0.5−1.9 earlier for breakup, and 0.7−4.3 shorter for duration. Mostly, standard deviation did not change, or it decreased in the 150-year and 100-year periods. During the recent 50-year period, standard deviation calculated in 10-year windows increased for all ice measures. For the 150-year and 100-year periods changes in the mean ice dates rather than changes in variability most strongly influenced the significant increases in the frequency of extreme lake ice events associated with warmer conditions and decreases in the frequency of extreme events associated with cooler conditions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Climatic Change","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10584-011-0212-8","usgsCitation":"Benson, B.J., Magnuson, J., Jensen, O.P., Card, V.M., Hodgkins, G., Korhonen, J., Livingstone, D., Stewart, K.M., Weyhenmeyer, G., and Granin, N., 2012, Extreme events, trends, and variability in Northern Hemisphere lake-ice phenology (1855-2005): Climatic Change, v. 112, no. 2, p. 299-323, https://doi.org/10.1007/s10584-011-0212-8.","productDescription":"25 p.","startPage":"299","endPage":"323","numberOfPages":"25","temporalStart":"1854-12-31","temporalEnd":"2005-12-31","ipdsId":"IP-024690","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":277859,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277858,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10584-011-0212-8"}],"otherGeospatial":"Northern Hemisphere","volume":"112","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-09-15","publicationStatus":"PW","scienceBaseUri":"523c1ce8e4b024b60d4072b9","contributors":{"authors":[{"text":"Benson, Barbara J.","contributorId":75058,"corporation":false,"usgs":true,"family":"Benson","given":"Barbara","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":484198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magnuson, John J.","contributorId":72699,"corporation":false,"usgs":true,"family":"Magnuson","given":"John J.","affiliations":[],"preferred":false,"id":484197,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jensen, Olaf P.","contributorId":92159,"corporation":false,"usgs":false,"family":"Jensen","given":"Olaf","email":"","middleInitial":"P.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":484199,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Card, Virginia M.","contributorId":56146,"corporation":false,"usgs":true,"family":"Card","given":"Virginia","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":484196,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hodgkins, Glenn","contributorId":29481,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","affiliations":[],"preferred":false,"id":484193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Korhonen, Johanna","contributorId":34036,"corporation":false,"usgs":true,"family":"Korhonen","given":"Johanna","affiliations":[],"preferred":false,"id":484194,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Livingstone, David M.","contributorId":36843,"corporation":false,"usgs":true,"family":"Livingstone","given":"David M.","affiliations":[],"preferred":false,"id":484195,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stewart, Kenton M.","contributorId":97810,"corporation":false,"usgs":true,"family":"Stewart","given":"Kenton","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":484201,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Weyhenmeyer, Gesa A.","contributorId":95381,"corporation":false,"usgs":true,"family":"Weyhenmeyer","given":"Gesa A.","affiliations":[],"preferred":false,"id":484200,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Granin, Nick G.","contributorId":21856,"corporation":false,"usgs":true,"family":"Granin","given":"Nick G.","affiliations":[],"preferred":false,"id":484192,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70118547,"text":"70118547 - 2012 - Well log characterization of natural gas-hydrates","interactions":[],"lastModifiedDate":"2014-07-29T11:13:16","indexId":"70118547","displayToPublicDate":"2012-01-01T11:09:22","publicationYear":"2012","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":12,"text":"Conference publication"},"title":"Well log characterization of natural gas-hydrates","docAbstract":"In the last 25 years there have been significant advancements in the use of well-logging tools to acquire detailed information on the occurrence of gas hydrates in nature: whereas wireline electrical resistivity and acoustic logs were formerly used to identify gas-hydrate occurrences in wells drilled in Arctic permafrost environments, more advanced wireline and logging-while-drilling (LWD) tools are now routinely used to examine the petrophysical nature of gas-hydrate reservoirs and the distribution and concentration of gas hydrates within various complex reservoir systems. Resistivity- and acoustic-logging tools are the most widely used for estimating the gas-hydrate content (i.e., reservoir saturations) in various sediment types and geologic settings. Recent integrated sediment coring and well-log studies have confirmed that electrical-resistivity and acoustic-velocity data can yield accurate gas-hydrate saturations in sediment grain-supported (isotropic) systems such as sand reservoirs, but more advanced log-analysis models are required to characterize gas hydrate in fractured (anisotropic) reservoir systems. New well-logging tools designed to make directionally oriented acoustic and propagation-resistivity log measurements provide the data needed to analyze the acoustic and electrical anisotropic properties of both highly interbedded and fracture-dominated gas-hydrate reservoirs. Advancements in nuclear magnetic resonance (NMR) logging and wireline formation testing (WFT) also allow for the characterization of gas hydrate at the pore scale. Integrated NMR and formation testing studies from northern Canada and Alaska have yielded valuable insight into how gas hydrates are physically distributed in sediments and the occurrence and nature of pore fluids(i.e., free water along with clay- and capillary-bound water) in gas-hydrate-bearing reservoirs. Information on the distribution of gas hydrate at the pore scale has provided invaluable insight on the mechanisms controlling the formation and occurrence of gas hydrate in nature along with data on gas-hydrate reservoir properties (i.e., porosities and permeabilities) needed to accurately predict gas production rates for various gas-hydrate production schemes.","conferenceTitle":"Society of Petrophysicists and Well-Log Analysts","conferenceDate":"2012-06-16T00:00:00","conferenceLocation":"Cartagena, Columbia","language":"English","publisher":"Society of Petrophysicists and Well-Log Analysts","publisherLocation":"Houston, TX","usgsCitation":"Collett, T.S., and Lee, M.W., 2012, Well log characterization of natural gas-hydrates, 20 p.","productDescription":"20 p.","numberOfPages":"20","costCenters":[],"links":[{"id":291279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f556e4b0bc0bec0a15b1","contributors":{"authors":[{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":496983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Myung W. mlee@usgs.gov","contributorId":779,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"mlee@usgs.gov","middleInitial":"W.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":496982,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70199592,"text":"70199592 - 2012 - Geostatistical population-mixture approach to unconventional-resource assessment with an application to the Woodford Gas Shale, Arkoma Basin, eastern Oklahoma","interactions":[],"lastModifiedDate":"2018-09-24T10:54:25","indexId":"70199592","displayToPublicDate":"2012-01-01T10:54:18","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5755,"text":"SPE Reservoir Evaluation & Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Geostatistical population-mixture approach to unconventional-resource assessment with an application to the Woodford Gas Shale, Arkoma Basin, eastern Oklahoma","docAbstract":"<p><span>Evaluation of resources such as tight sands and gas shales requires the formulation of assessment models that are different from those used for the inference of conventional resources. Formulations in present use are based in classical statistics that ignore the partly organized and partly random geographical variation of attributes related to the occurrence of hydrocarbons. This paper is the third in a series of methodological tests aimed at enhancing the assessment of unconventional resources through more-effective use of implicit and explicit information contained in the data, more-accurate evaluation of resources, and more-informative display of results. Reprocessing of estimated-ultimate-recovery (EUR) data at the Woodford gas shale in Oklahoma shows that subdivision of the play into areas as homogeneous as possible can produce results comparable to those obtained using several variables correlated to local productivity.</span></p>","language":"English","publisher":"Society of Petroleum Engineers","doi":"10.2118/163049-PA","usgsCitation":"Olea, R., Charpentier, R., Cook, T.A., Houseknecht, D.W., and Garrity, C.P., 2012, Geostatistical population-mixture approach to unconventional-resource assessment with an application to the Woodford Gas Shale, Arkoma Basin, eastern Oklahoma: SPE Reservoir Evaluation & Engineering, v. 15, no. 5, p. 554-562, https://doi.org/10.2118/163049-PA.","productDescription":"9 p.","startPage":"554","endPage":"562","ipdsId":"IP-038213","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357660,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Arkoma Basin","volume":"15","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2012-09-04","publicationStatus":"PW","scienceBaseUri":"5c10bf3de4b034bf6a7f0c7b","contributors":{"editors":[{"text":"Houseknecht, David W. 0000-0002-9633-6910 dhouse@usgs.gov","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":645,"corporation":false,"usgs":true,"family":"Houseknecht","given":"David","email":"dhouse@usgs.gov","middleInitial":"W.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":745916,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Charpentier, Ronald R.","contributorId":208099,"corporation":false,"usgs":false,"family":"Charpentier","given":"Ronald R.","affiliations":[{"id":37715,"text":"Ex-USGS, now retired","active":true,"usgs":false}],"preferred":false,"id":745917,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":47873,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":745915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Charpentier, Ronald charpentier@usgs.gov","contributorId":150415,"corporation":false,"usgs":true,"family":"Charpentier","given":"Ronald","email":"charpentier@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":746098,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cook, Troy A.","contributorId":52519,"corporation":false,"usgs":true,"family":"Cook","given":"Troy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":746099,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Houseknecht, David W. 0000-0002-9633-6910 dhouse@usgs.gov","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":645,"corporation":false,"usgs":true,"family":"Houseknecht","given":"David","email":"dhouse@usgs.gov","middleInitial":"W.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":746100,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garrity, Christopher P. 0000-0002-5565-1818 cgarrity@usgs.gov","orcid":"https://orcid.org/0000-0002-5565-1818","contributorId":644,"corporation":false,"usgs":true,"family":"Garrity","given":"Christopher","email":"cgarrity@usgs.gov","middleInitial":"P.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":746101,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70038199,"text":"70038199 - 2012 - Root zone water quality model (RZWQM2): Model use, calibration and validation","interactions":[],"lastModifiedDate":"2021-01-05T18:56:01.036463","indexId":"70038199","displayToPublicDate":"2012-01-01T10:16:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3619,"text":"Transactions of the ASABE","active":true,"publicationSubtype":{"id":10}},"title":"Root zone water quality model (RZWQM2): Model use, calibration and validation","docAbstract":"The Root Zone Water Quality Model (RZWQM2) has been used widely for simulating agricultural management effects on crop production and soil and water quality. Although it is a one-dimensional model, it has many desirable features for the modeling community. This article outlines the principles of calibrating the model component by component with one or more datasets and validating the model with independent datasets. Users should consult the RZWQM2 user manual distributed along with the model and a more detailed protocol on how to calibrate RZWQM2 provided in a book chapter. Two case studies (or examples) are included in this article. One is from an irrigated maize study in Colorado to illustrate the use of field and laboratory measured soil hydraulic properties on simulated soil water and crop production. It also demonstrates the interaction between soil and plant parameters in simulated plant responses to water stresses. The other is from a maize-soybean rotation study in Iowa to show a manual calibration of the model for crop yield, soil water, and N leaching in tile-drained soils. Although the commonly used trial-and-error calibration method works well for experienced users, as shown in the second example, an automated calibration procedure is more objective, as shown in the first example. Furthermore, the incorporation of the Parameter Estimation Software (PEST) into RZWQM2 made the calibration of the model more efficient than a grid (ordered) search of model parameters. In addition, PEST provides sensitivity and uncertainty analyses that should help users in selecting the right parameters to calibrate.","language":"English","publisher":"American Society of Agricultural and Biological Engineers","doi":"10.13031/2013.42252","usgsCitation":"Ma, L., Ahuja, L., Nolan, B.T., Malone, R., Trout, T., and Qi, Z., 2012, Root zone water quality model (RZWQM2): Model use, calibration and validation: Transactions of the ASABE, v. 55, no. 4, p. 1425-1446, https://doi.org/10.13031/2013.42252.","productDescription":"22 p.","startPage":"1425","endPage":"1446","ipdsId":"IP-037029","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":381890,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5200c969e4b009d47a4c23de","contributors":{"authors":[{"text":"Ma, Liwang","contributorId":6751,"corporation":false,"usgs":false,"family":"Ma","given":"Liwang","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":463644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ahuja, Lajpat","contributorId":100275,"corporation":false,"usgs":true,"family":"Ahuja","given":"Lajpat","email":"","affiliations":[],"preferred":false,"id":463649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nolan, B. T.","contributorId":21565,"corporation":false,"usgs":true,"family":"Nolan","given":"B.","email":"","middleInitial":"T.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":463645,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Malone, Robert","contributorId":28888,"corporation":false,"usgs":true,"family":"Malone","given":"Robert","affiliations":[],"preferred":false,"id":463646,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trout, Thomas","contributorId":95785,"corporation":false,"usgs":true,"family":"Trout","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":463647,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Qi, Z.","contributorId":99870,"corporation":false,"usgs":true,"family":"Qi","given":"Z.","email":"","affiliations":[],"preferred":false,"id":463648,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70046096,"text":"70046096 - 2012 - The science, information, and engineering needed to manage water availability and quality in 2050","interactions":[],"lastModifiedDate":"2022-12-27T17:14:35.840593","indexId":"70046096","displayToPublicDate":"2012-01-01T09:54:29","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"23","title":"The science, information, and engineering needed to manage water availability and quality in 2050","docAbstract":"This chapter explores four water resources issues: 1) hydrologic variability, hazards, water supply and ecosystem preservation; 2) urban landscape design; 3) non-point source water quality, and 4) climate change, resiliency, and nonstationarity.  It also considers what science, technology, and engineering practice may be needed in the coming decades to sustain water supplies and ecosystems in the face of increasing stresses from a growing demand for water.  Dealing with these four water resource issues in the highly uncertain future would will demand predictive models that are rooted in real-world data.  In a non-stationary world, continuity of observations is crucial.  All watersheds are influenced by human actions through changes in land use, water use, and climate.  The focus of water planning and management between today and 2050 will depend more than ever on collection and analysis of long-term data to learn about the evolving state of the system, understanding ecosystem processes in the water and on the landscape, and finding innovative ways to manage water as a shared resource.  This includes sharing water with our neighbors on the landscape, sharing with the other species that depend on water, and sharing with future generations.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Toward a sustainable water future: Visions for 2050","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/9780784412077.ch23","usgsCitation":"Hirsch, R.M., 2012, The science, information, and engineering needed to manage water availability and quality in 2050, chap. 23 <i>of</i> Toward a sustainable water future: Visions for 2050, p. 215-225, https://doi.org/10.1061/9780784412077.ch23.","productDescription":"11 p.","startPage":"215","endPage":"225","ipdsId":"IP-017761","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":276736,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2013-05-10","publicationStatus":"PW","scienceBaseUri":"52136e3ae4b0b08f4461993d","contributors":{"authors":[{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":478895,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70037991,"text":"70037991 - 2012 - Near-surface, marine seismic-reflection data defines potential hydrogeologic confinement bypass in a tertiary carbonate aquifer, southeastern Florida","interactions":[],"lastModifiedDate":"2013-07-30T09:51:23","indexId":"70037991","displayToPublicDate":"2012-01-01T09:34:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3317,"text":"SEG Technical Program Expanded Abstracts","active":true,"publicationSubtype":{"id":10}},"title":"Near-surface, marine seismic-reflection data defines potential hydrogeologic confinement bypass in a tertiary carbonate aquifer, southeastern Florida","docAbstract":"Approximately 210 km of near-surface, high-frequency, marine seismic-reflection data were acquired on the southeastern part of the Florida Platform between 2007 and 2011. Many high-resolution, seismic-reflection profiles, interpretable to a depth of about 730 m, were collected on the shallow-marine shelf of southeastern Florida in water as shallow as 1 m. Landward of the present-day shelf-margin slope, these data image middle Eocene to Pleistocene strata and Paleocene to Pleistocene strata on the Miami Terrace. This high-resolution data set provides an opportunity to evaluate geologic structures that cut across confining units of the Paleocene to Oligocene-age carbonate rocks that form the Floridan aquifer system.Seismic profiles image two structural systems, tectonic faults and karst collapse structures, which breach confining beds in the Floridan aquifer system. Both structural systems may serve as pathways for vertical groundwater flow across relatively low-permeability carbonate strata that separate zones of regionally extensive high-permeability rocks in the Floridan aquifer system. The tectonic faults occur as normal and reverse faults, and collapse-related faults have normal throw. The most common fault occurrence delineated on the reflection profiles is associated with karst collapse structures. These high-frequency seismic data are providing high quality structural analogs to unprecedented depths on the southeastern Florida Platform. The analogs can be used for assessment of confinement of other carbonate aquifers and the sealing potential of deeper carbonate rocks associated with reservoirs around the world.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"SEG Technical Program Expanded Abstracts","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/segam2012-0638.1","usgsCitation":"Cunningham, K.J., Walker, C., and Westcott, R., 2012, Near-surface, marine seismic-reflection data defines potential hydrogeologic confinement bypass in a tertiary carbonate aquifer, southeastern Florida: SEG Technical Program Expanded Abstracts, v. 2012, p. 1-6, https://doi.org/10.1190/segam2012-0638.1.","productDescription":"6 p.","startPage":"1","endPage":"6","ipdsId":"IP-037097","costCenters":[{"id":286,"text":"Florida Water Science Center-Ft. Lauderdale","active":false,"usgs":true}],"links":[{"id":275557,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275556,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1190/segam2012-0638.1"}],"country":"United States","state":"Florida","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.2109,25.1254 ], [ -81.2109,28.5942 ], [ -79.9365,28.5942 ], [ -79.9365,25.1254 ], [ -81.2109,25.1254 ] ] ] } } ] }","volume":"2012","noUsgsAuthors":false,"publicationDate":"2012-10-25","publicationStatus":"PW","scienceBaseUri":"51f8e063e4b0cecbe8fa9885","contributors":{"authors":[{"text":"Cunningham, Kevin J. 0000-0002-2179-8686 kcunning@usgs.gov","orcid":"https://orcid.org/0000-0002-2179-8686","contributorId":1689,"corporation":false,"usgs":true,"family":"Cunningham","given":"Kevin","email":"kcunning@usgs.gov","middleInitial":"J.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":463222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Cameron","contributorId":81777,"corporation":false,"usgs":true,"family":"Walker","given":"Cameron","affiliations":[],"preferred":false,"id":463224,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westcott, Richard L.","contributorId":71465,"corporation":false,"usgs":true,"family":"Westcott","given":"Richard L.","affiliations":[],"preferred":false,"id":463223,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048460,"text":"sir20125107 - 2012 - Sources and sinks of nitrogen and phosphorus to a deep, oligotrophic lake, Lake Crescent, Olympic National Park, Washington","interactions":[],"lastModifiedDate":"2025-02-10T14:45:57.485874","indexId":"sir20125107","displayToPublicDate":"2012-01-01T08:09:00","publicationYear":"2012","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":"2012-5107","displayTitle":"Sources and Sinks of Nitrogen and Phosphorus in a Deep,  Oligotrophic Lake, Lake Crescent, Olympic National Park,  Washington","title":"Sources and sinks of nitrogen and phosphorus to a deep, oligotrophic lake, Lake Crescent, Olympic National Park, Washington","docAbstract":"Lake Crescent, in Olympic National Park in the northwest corner of Washington State is a deep-water lake renowned for its pristine water quality and oligotrophic nature. To examine the major sources and sinks of nutrients (as total nitrogen, total phosphorus, and dissolved nitrate), a study was conducted in the Lake Crescent watershed. The study involved measuring five major inflow streams, the Lyre River as the major outflow, recording weather and climatic data, coring lake bed sediment, and analyzing nutrient chemistry in several relevant media over 14 months. Water samples for total nitrogen, total phosphorous, and dissolved nitrate from the five inflow streams, the outlet Lyre River, and two stations in the lake were collected monthly from May 2006 through May 2007. Periodic samples of shallow water from temporary sampling wells were collected at numerous locations around the lake. Concentrations of nutrients detected in Lake Crescent and tributaries were then applied to the water budget estimates to arrive at monthly and annual loads from various environmental components within the watershed. Other sources, such as leaf litter, pollen, or automobile exhaust were estimated from annual values obtained from various literature sources. This information then was used to construct a nutrient budget for total nitrogen and total phosphorus. The nitrogen budget generally highlights vehicle traffic-diesel trucks in particular-along U.S. Highway 101 as a potential major anthropogenic source of nitrogen compounds in the lake. In contrast, contribution of nitrogen compounds from onsite septic systems appears to be relatively minor related to the other sources identified.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125107","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Moran, P., Cox, S., Embrey, S., Huffman, R., Olsen, T.D., and Fradkin, S., 2012, Sources and sinks of nitrogen and phosphorus to a deep, oligotrophic lake, Lake Crescent, Olympic National Park, Washington: U.S. Geological Survey Scientific Investigations Report 2012-5107, Report: viii, 56 p.; 6 Appendices, https://doi.org/10.3133/sir20125107.","productDescription":"Report: viii, 56 p.; 6 Appendices","numberOfPages":"64","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":278167,"rank":9,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5107/","text":"USGS Index Page","linkFileType":{"id":5,"text":"html"},"description":"SIR 2012-5107"},{"id":278176,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5107/pdf/sir2012-5107_appendixF.pdf","text":"Appendix F","size":"443 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2012-5107 Appendix F"},{"id":278175,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5107/pdf/sir2012-5107_appendixE.pdf","text":"Appendix E","size":"123 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2012-5107 Appendix E"},{"id":278173,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5107/pdf/sir2012-5107_appendixD.pdf","text":"Appendix D","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2012-5107 Appendix D"},{"id":278177,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125107.jpg"},{"id":278171,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5107/pdf/sir2012-5107_appendixC.pdf","text":"Appendix C","size":"294 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2012-5107 Appendix C"},{"id":278170,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5107/pdf/sir2012-5107_appendixB.pdf","text":"Appendix B","size":"64 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2012-5107 Appendix B"},{"id":278169,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5107/pdf/sir2012-5107_appendixA.pdf","text":"Appendix A","size":"75 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2012-5107 Appendix A"},{"id":278168,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5107/pdf/sir2012-5107.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2012-5107"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Crescent, Olympic National Park, Olympic Peninsula","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.7348,47.4695 ], [ -124.7348,48.2747 ], [ -123.1217,48.2747 ], [ -123.1217,47.4695 ], [ -124.7348,47.4695 ] ] ] } } ] }","contact":"<p><a href=\"mailto:dc_wa@usgs.gov\" data-mce-href=\"mailto:dc_wa@usgs.gov\">Director</a>, <a href=\"http://wa.water.usgs.gov\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"http://wa.water.usgs.gov\">Washington Water Science Center</a><br>U.S. Geological Survey<br>934 Broadway, Suite 300<br>Tacoma, WA 98402</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Description of Lake Crescent and the Watershed</li><li>Methods of Investigation</li><li>Sources and Sinks of Nitrogen And Phosphorous</li><li>Summary</li><li>Recommendations</li><li>Acknowledgments</li><li>References Cited</li><li>Appendix A. Results of Chemical Analyses on Field Blank-Water, Field-Replicate, and Aqueous Standard-Reference Quality-Control Samples</li><li>Appendix B. Daily Mean Streamflows for Fairholm Creek, Lapoel Creek, Smith Creek, Barnes Creek, Piedmont Creek, and Lyre River, Washington, Water Years 2006–07</li><li>Appendix C. Results of Chemical Analyses on Water Samples from Lake Crescent and Streams</li><li>Appendix D. Results of Chemical Analyses on Bottom-Sediment Core Samples Collected from Lake Crescent, Washington, September 2008</li><li>Appendix E. Results of Chemical Analyses and Field Measurements on Water Samples from Piezometers, October 2007</li><li>Appendix F. Estimated and Observed Daily Total Nitrogen and Total Phosphorus Loads and Loadest Model Parameters</li></ul>","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5246e91ce4b035b7f35addeb","contributors":{"authors":[{"text":"Moran, P.W.","contributorId":9401,"corporation":false,"usgs":true,"family":"Moran","given":"P.W.","email":"","affiliations":[],"preferred":false,"id":484707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cox, S.E.","contributorId":66663,"corporation":false,"usgs":true,"family":"Cox","given":"S.E.","email":"","affiliations":[],"preferred":false,"id":484710,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Embrey, S.S.","contributorId":8448,"corporation":false,"usgs":true,"family":"Embrey","given":"S.S.","affiliations":[],"preferred":false,"id":484706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huffman, R.L.","contributorId":44956,"corporation":false,"usgs":true,"family":"Huffman","given":"R.L.","email":"","affiliations":[],"preferred":false,"id":484709,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olsen, T. D.","contributorId":41463,"corporation":false,"usgs":true,"family":"Olsen","given":"T.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":484708,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fradkin, S.C.","contributorId":69880,"corporation":false,"usgs":true,"family":"Fradkin","given":"S.C.","email":"","affiliations":[],"preferred":false,"id":484711,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70032649,"text":"70032649 - 2012 - Updated determination of stress parameters for nine well-recorded earthquakes in eastern North America","interactions":[],"lastModifiedDate":"2017-10-17T16:51:03","indexId":"70032649","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Updated determination of stress parameters for nine well-recorded earthquakes in eastern North America","docAbstract":"<p><span>Stress parameters (Δ</span><i>σ</i><span>) are determined for nine relatively well-recorded earthquakes in eastern North America for ten attenuation models. This is an update of a previous study by Boore<span>&nbsp;</span></span><i>et al.</i><span><span>&nbsp;</span>(2010). New to this paper are observations from the 2010 Val des Bois earthquake, additional observations for the 1988 Saguenay and 2005 Riviere du Loup earthquakes, and consideration of six attenuation models in addition to the four used in the previous study. As in that study, it is clear that Δ</span><i>σ</i><span><span>&nbsp;</span>depends strongly on the rate of geometrical spreading (as well as other model parameters). The observations necessary to determine conclusively which attenuation model best fits the data are still lacking. At this time, a simple 1/</span><i>R</i><span><span>&nbsp;</span>model seems to give as good an overall fit to the data as more complex models.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/gssrl.83.1.190","issn":"08950695","usgsCitation":"Boore, D.M., 2012, Updated determination of stress parameters for nine well-recorded earthquakes in eastern North America: Seismological Research Letters, v. 83, no. 1, p. 190-199, https://doi.org/10.1785/gssrl.83.1.190.","productDescription":"10 p.","startPage":"190","endPage":"199","numberOfPages":"10","ipdsId":"IP-034108","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":241355,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213701,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/gssrl.83.1.190"}],"volume":"83","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-09","publicationStatus":"PW","scienceBaseUri":"505bbd16e4b08c986b328ebe","contributors":{"authors":[{"text":"Boore, David M. boore@usgs.gov","contributorId":2509,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":437265,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70192533,"text":"70192533 - 2012 - Use of occupancy models to evaluate expert knowledge-based species-habitat relationships","interactions":[],"lastModifiedDate":"2018-12-21T13:06:14","indexId":"70192533","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Use of occupancy models to evaluate expert knowledge-based species-habitat relationships","docAbstract":"<p><span>Expert knowledge-based species-habitat relationships are used extensively to guide conservation planning, particularly when data are scarce. Purported relationships describe the initial state of knowledge, but are rarely tested. We assessed support in the data for suitability rankings of vegetation types based on expert knowledge for three terrestrial avian species in the South Atlantic Coastal Plain of the United States. Experts used published studies, natural history, survey data, and field experience to rank vegetation types as optimal, suitable, and marginal. We used single-season occupancy models, coupled with land cover and Breeding Bird Survey data, to examine the hypothesis that patterns of occupancy conformed to species-habitat suitability rankings purported by experts. Purported habitat suitability was validated for two of three species. As predicted for the Eastern Wood-Pewee (</span><i>Contopus virens</i><span>) and Brown-headed Nuthatch (</span><i>Sitta pusilla</i><span>), occupancy was strongly influenced by vegetation types classified as “optimal habitat” by the species suitability rankings for nuthatches and wood-pewees. Contrary to predictions, Red-headed Woodpecker (</span><i>Melanerpes erythrocephalus</i><span>) models that included vegetation types as covariates received similar support by the data as models without vegetation types. For all three species, occupancy was also related to sampling latitude. Our results suggest that covariates representing other habitat requirements might be necessary to model occurrence of generalist species like the woodpecker. The modeling approach described herein provides a means to test expert knowledge-based species-habitat relationships, and hence, help guide conservation planning.</span></p>","language":"English","publisher":"Avian Conservation and Ecology","doi":"10.5751/ACE-00551-070205","usgsCitation":"Iglecia, M.N., Collazo, J., and McKerrow, A., 2012, Use of occupancy models to evaluate expert knowledge-based species-habitat relationships: Avian Conservation and Ecology, v. 7, no. 2, p. 1-13, https://doi.org/10.5751/ACE-00551-070205.","productDescription":"Article 5; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-029469","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":38315,"text":"GAP Analysis Project","active":true,"usgs":true}],"links":[{"id":474667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-00551-070205","text":"Publisher Index Page"},{"id":349461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6105a0e4b06e28e9c25585","contributors":{"authors":[{"text":"Iglecia, Monica N.","contributorId":200933,"corporation":false,"usgs":false,"family":"Iglecia","given":"Monica","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":723848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":716133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":127753,"corporation":false,"usgs":true,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":723849,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193286,"text":"70193286 - 2012 - Displacement fields from point cloud data: Application of particle imaging velocimetry to landslide geodesy","interactions":[],"lastModifiedDate":"2019-05-30T10:00:16","indexId":"70193286","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Displacement fields from point cloud data: Application of particle imaging velocimetry to landslide geodesy","docAbstract":"<p><span>Acquiring spatially continuous ground-surface displacement fields from Terrestrial Laser Scanners (TLS) will allow better understanding of the physical processes governing landslide motion at detailed spatial and temporal scales. Problems arise, however, when estimating continuous displacement fields from TLS point-clouds because reflecting points from sequential scans of moving ground are not defined uniquely, thus repeat TLS surveys typically do not track individual reflectors. Here, we implemented the cross-correlation-based Particle Image Velocimetry (PIV) method to derive a surface deformation field using TLS point-cloud data. We estimated associated errors using the shape of the cross-correlation function and tested the method's performance with synthetic displacements applied to a TLS point cloud. We applied the method to the toe of the episodically active Cleveland Corral Landslide in northern California using TLS data acquired in June 2005–January 2007 and January–May 2010. Estimated displacements ranged from decimeters to several meters and they agreed well with independent measurements at better than 9% root mean squared (RMS) error. For each of the time periods, the method provided a smooth, nearly continuous displacement field that coincides with independently mapped boundaries of the slide and permits further kinematic and mechanical inference. For the 2010 data set, for instance, the PIV-derived displacement field identified a diffuse zone of displacement that preceded by over a month the development of a new lateral shear zone. Additionally, the upslope and downslope displacement gradients delineated by the dense PIV field elucidated the non-rigid behavior of the slide.</span></p>","language":"English","publisher":"AGU","doi":"10.1029/2011JF002161","usgsCitation":"Aryal, A., Brooks, B.A., Reid, M.E., Bawden, G.W., and Pawlak, G., 2012, Displacement fields from point cloud data: Application of particle imaging velocimetry to landslide geodesy: Journal of Geophysical Research F: Earth Surface, v. 117, no. F1, p. 1-15, https://doi.org/10.1029/2011JF002161.","productDescription":"F01029; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-034573","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":474690,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011jf002161","text":"Publisher Index Page"},{"id":347929,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sierra Nevada Mountains","volume":"117","issue":"F1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2012-03-21","publicationStatus":"PW","scienceBaseUri":"59f98bc1e4b0531197afa068","contributors":{"authors":[{"text":"Aryal, Arjun","contributorId":199281,"corporation":false,"usgs":false,"family":"Aryal","given":"Arjun","affiliations":[],"preferred":false,"id":718548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, Benjamin A. 0000-0001-7954-6281 bbrooks@usgs.gov","orcid":"https://orcid.org/0000-0001-7954-6281","contributorId":5237,"corporation":false,"usgs":true,"family":"Brooks","given":"Benjamin","email":"bbrooks@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":718549,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reid, Mark E. 0000-0002-5595-1503 mreid@usgs.gov","orcid":"https://orcid.org/0000-0002-5595-1503","contributorId":1167,"corporation":false,"usgs":true,"family":"Reid","given":"Mark","email":"mreid@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":718547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bawden, Gerald W. gbawden@usgs.gov","contributorId":1071,"corporation":false,"usgs":true,"family":"Bawden","given":"Gerald","email":"gbawden@usgs.gov","middleInitial":"W.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":718546,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pawlak, Geno","contributorId":66178,"corporation":false,"usgs":true,"family":"Pawlak","given":"Geno","email":"","affiliations":[],"preferred":false,"id":718550,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70032665,"text":"70032665 - 2012 - Occurrence and geochemistry of radium in water from principal drinking-water aquifer systems of the United States","interactions":[],"lastModifiedDate":"2019-09-25T10:51:13","indexId":"70032665","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence and geochemistry of radium in water from principal drinking-water aquifer systems of the United States","docAbstract":"A total of 1270 raw-water samples (before treatment) were collected from 15 principal and other major aquifer systems (PAs) used for drinking water in 45 states in all major physiographic provinces of the USA and analyzed for concentrations of the Ra isotopes  224Ra,  226Ra and  228Ra establishing the framework for evaluating Ra occurrence. The US Environmental Protection Agency Maximum Contaminant Level (MCL) of 0.185Bq/L (5pCi/L) for combined Ra (  226Ra plus  228Ra) for drinking water was exceeded in 4.02% (39 of 971) of samples for which both  226Ra and  228Ra were determined, or in 3.15% (40 of 1266) of the samples in which at least one isotope concentration (  226Ra or  228Ra) was determined. The maximum concentration of combined Ra was 0.755Bq/L (20.4pCi/L) in water from the North Atlantic Coastal Plain quartzose sand aquifer system. All the exceedences of the MCL for combined Ra occurred in water samples from the following 7PAs (in order of decreasing relative frequency of occurrence): the Midcontinent and Ozark Plateau Cambro-Ordovician dolomites and sandstones, the North Atlantic Coastal Plain, the Floridan, the crystalline rocks (granitic, metamorphic) of New England, the Mesozoic basins of the Appalachian Piedmont, the Gulf Coastal Plain, and the glacial sands and gravels (highest concentrations in New England).The concentration of Ra was consistently controlled by geochemical properties of the aquifer systems, with the highest concentrations most likely to be present where, as a consequence of the geochemical environment, adsorption of the Ra was slightly decreased. The result is a slight relative increase in Ra mobility, especially notable in aquifers with poor sorptive capacity (Fe-oxide-poor quartzose sands and carbonates), even if Ra is not abundant in the aquifer solids. The most common occurrence of elevated Ra throughout the USA occurred in anoxic water (low dissolved-O  2) with high concentrations of Fe or Mn, and in places, high concentrations of the competing ions Ca, Mg, Ba and Sr, and occasionally of dissolved solids, K, SO  4 and HCO  3. The other water type to frequently contain elevated concentrations of the Ra radioisotopes was acidic (low pH), and had in places, high concentrations of NO  3 and other acid anions, and on occasion, of the competing divalent cations, Mn and Al. One or the other of these broad water types was commonly present in each of the PAs in which elevated concentrations of combined Ra occurred. Concentrations of  226Ra or  228Ra or combined Ra correlated significantly with those of the above listed water-quality constituents (on the basis of the non-parametric Spearman correlation technique) and loaded on principal components describing the above water types from the entire data set and for samples from the PAs with the highest combined Ra concentrations.Concentrations of  224Ra and  226Ra were significantly correlated to those of  228Ra (Spearman's rank correlation coefficient, +0.236 and +0.326, respectively). Activity ratios of  224Ra/  228Ra in the water samples were mostly near 1 when concentrations of both isotopes were greater than or equal to 0.037Bq/L (1pCi/L), the level above which analytical results were most reliable. Co-occurrence among these highest concentrations of the Ra radionuclides was most likely in those PAs where chemical conditions are most conducive to Ra mobility (e.g. acidic North Atlantic Coastal Plain). The concentrations of  224Ra were occasionally greater than 0.037Bq/L and the ratios of  224Ra/  228Ra were generally highest in the PAs composed of alluvial sands and Cretaceous/Tertiary sandstones from the western USA, likely because concentrations of  224Ra are enhanced in solution relative to those of  228Ra by alpha recoil from the aquifer matrix. Rapid adsorption of the two Ra isotopes (controlled by the alkaline and oxic aquifer geochemistry) combined with preferential faster recoil of  224Ra generates a  224Ra/  228Ra ratio much greater than ","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Geochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.apgeochem.2011.11.002","issn":"08832927","usgsCitation":"Szabo, Z., DePaul, V.T., Fischer, J., Kraemer, T.F., and Jacobsen, E., 2012, Occurrence and geochemistry of radium in water from principal drinking-water aquifer systems of the United States: Applied Geochemistry, v. 27, no. 3, p. 729-752, https://doi.org/10.1016/j.apgeochem.2011.11.002.","startPage":"729","endPage":"752","numberOfPages":"24","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":474677,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2011.11.002","text":"Publisher Index Page"},{"id":241597,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213923,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeochem.2011.11.002"}],"volume":"27","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a6b6ce4b0c8380cd746a9","contributors":{"authors":[{"text":"Szabo, Z. 0000-0002-0760-9607","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":44302,"corporation":false,"usgs":true,"family":"Szabo","given":"Z.","affiliations":[],"preferred":false,"id":437349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DePaul, Vincent T. 0000-0002-7977-5217 vdepaul@usgs.gov","orcid":"https://orcid.org/0000-0002-7977-5217","contributorId":2778,"corporation":false,"usgs":true,"family":"DePaul","given":"Vincent","email":"vdepaul@usgs.gov","middleInitial":"T.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":437351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischer, J.M. 0000-0003-2996-9272","orcid":"https://orcid.org/0000-0003-2996-9272","contributorId":74419,"corporation":false,"usgs":true,"family":"Fischer","given":"J.M.","affiliations":[],"preferred":false,"id":437352,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kraemer, T. F.","contributorId":63400,"corporation":false,"usgs":true,"family":"Kraemer","given":"T.","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":437350,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jacobsen, E.","contributorId":101462,"corporation":false,"usgs":true,"family":"Jacobsen","given":"E.","email":"","affiliations":[],"preferred":false,"id":437353,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70035654,"text":"70035654 - 2012 - Recent paleorecords document rising mercury contamination in Lake Tanganyika","interactions":[],"lastModifiedDate":"2020-11-16T21:20:59.329352","indexId":"70035654","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Recent paleorecords document rising mercury contamination in Lake Tanganyika","docAbstract":"<p><span>Recent Lake Tanganyika Hg deposition records were derived using&nbsp;</span><sup>14</sup><span>C and excess&nbsp;</span><sup>210</sup><span>Pb geochronometers in sediment cores collected from two contrasting depositional environments: the Kalya Platform, located mid-lake and more removed from watershed impacts, and the Nyasanga/Kahama River delta region, located close to the lake’s shoreline north of Kigoma. At the Kalya Platform area, pre-industrial Hg concentrations are 23</span><span>&nbsp;</span><span>±</span><span>&nbsp;</span><span>0.2</span><span>&nbsp;</span><span>ng/g, increasing to 74</span><span>&nbsp;</span><span>ng/g in modern surface sediment, and the Hg accumulation rate has increased from 1.0 to 7.2</span><span>&nbsp;</span><span>μg/m</span><sup>2</sup><span>/a from pre-industrial to present, which overall represents a 6-fold increase in Hg concentration and accumulation. At the Nyasanga/Kahama delta region, pre-industrial Hg concentrations are 20</span><span>&nbsp;</span><span>±</span><span>&nbsp;</span><span>3</span><span>&nbsp;</span><span>ng/g, increasing to 46</span><span>&nbsp;</span><span>ng/g in surface sediment. Mercury accumulation rate has increased from 30 to 70</span><span>&nbsp;</span><span>μg/m</span><sup>2</sup><span>/a at this site, representing a 2–3-fold increase in Hg concentration and accumulation. There is a lack of correlation between charcoal abundance and Hg accumulation rate in the sediment cores, demonstrating that local biomass burning has little relationship with the observed Hg concentration or Hg accumulation rates. Examined using a sediment focusing-corrected mass accumulation rate approach, the cores have similar anthropogenic atmospheric Hg deposition profiles, suggesting that after accounting for background sediment concentrations the source of accumulating Hg is predominantly atmospheric in origin. In summary, the data document an increase of Hg flux to the Lake Tanganyika ecosystem that is consistent with increasing watershed sediment delivery with background-level Hg contamination, and regional as well as global increases in atmospheric Hg deposition.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2011.11.005","issn":"08832927","usgsCitation":"Conaway, C.H., Swarzenski, P.W., and Cohen, A., 2012, Recent paleorecords document rising mercury contamination in Lake Tanganyika: Applied Geochemistry, v. 27, no. 1, p. 352-359, https://doi.org/10.1016/j.apgeochem.2011.11.005.","productDescription":"8 p.","startPage":"352","endPage":"359","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":244359,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":216486,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeochem.2011.11.005"}],"country":"United States","county":"Tanzania, the Democratic Republic of the Congo , Burundi, and Zambia","otherGeospatial":"Lake Tanganyika","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              28.872070312500004,\n              -3.2063329870791315\n            ],\n            [\n              28.872070312500004,\n              -5.98760689165826\n            ],\n            [\n              30.344238281249996,\n              -8.646195681181904\n            ],\n            [\n              31.09130859375,\n              -9.123792057073972\n            ],\n            [\n              31.61865234375,\n              -8.885071663468981\n            ],\n            [\n              29.487304687499996,\n              -3.118576216781991\n            ],\n            [\n              28.872070312500004,\n              -3.2063329870791315\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"27","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a9630e4b0c8380cd81e5b","contributors":{"authors":[{"text":"Conaway, Christopher H. 0000-0002-0991-033X cconaway@usgs.gov","orcid":"https://orcid.org/0000-0002-0991-033X","contributorId":5074,"corporation":false,"usgs":true,"family":"Conaway","given":"Christopher","email":"cconaway@usgs.gov","middleInitial":"H.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":451690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":451689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cohen, A.S.","contributorId":19313,"corporation":false,"usgs":true,"family":"Cohen","given":"A.S.","email":"","affiliations":[],"preferred":false,"id":451688,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70032430,"text":"70032430 - 2012 - Slab1.0: A three-dimensional model of global subduction zone geometries","interactions":[],"lastModifiedDate":"2018-03-08T12:20:03","indexId":"70032430","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Slab1.0: A three-dimensional model of global subduction zone geometries","docAbstract":"<p><span>We describe and present a new model of global subduction zone geometries, called Slab1.0. An extension of previous efforts to constrain the two-dimensional non-planar geometry of subduction zones around the focus of large earthquakes, Slab1.0 describes the detailed, non-planar, three-dimensional geometry of approximately 85% of subduction zones worldwide. While the model focuses on the detailed form of each slab from their trenches through the seismogenic zone, where it combines data sets from active source and passive seismology, it also continues to the limits of their seismic extent in the upper-mid mantle, providing a uniform approach to the definition of the entire seismically active slab geometry. Examples are shown for two well-constrained global locations; models for many other regions are available and can be freely downloaded in several formats from our new Slab1.0 website,&nbsp;</span>http://on.doi.gov/d9ARbS<span>. We describe improvements in our two-dimensional geometry constraint inversion, including the use of ‘average’ active source seismic data profiles in the shallow trench regions where data are otherwise lacking, derived from the interpolation between other active source seismic data along-strike in the same subduction zone. We include several analyses of the uncertainty and robustness of our three-dimensional interpolation methods. In addition, we use the filtered, subduction-related earthquake data sets compiled to build Slab1.0 in a reassessment of previous analyses of the deep limit of the thrust interface seismogenic zone for all subduction zones included in our global model thus far, concluding that the width of these seismogenic zones is on average 30% larger than previous studies have suggested.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2011JB008524","usgsCitation":"Hayes, G.P., Wald, D.J., and Johnson, R.L., 2012, Slab1.0: A three-dimensional model of global subduction zone geometries: Journal of Geophysical Research B: Solid Earth, v. 117, no. B1, Article B01302; 15 p., https://doi.org/10.1029/2011JB008524.","productDescription":"Article B01302; 15 p.","costCenters":[],"links":[{"id":241645,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","issue":"B1","noUsgsAuthors":false,"publicationDate":"2012-01-04","publicationStatus":"PW","scienceBaseUri":"505b912ee4b08c986b3197a2","contributors":{"authors":[{"text":"Hayes, Gavin P. 0000-0003-3323-0112 ghayes@usgs.gov","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":842,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin","email":"ghayes@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":436147,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":436146,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Rebecca L. 0000-0002-8771-6161 rljohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-8771-6161","contributorId":178874,"corporation":false,"usgs":true,"family":"Johnson","given":"Rebecca","email":"rljohnson@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":436145,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70032584,"text":"70032584 - 2012 - Foraging segregation and genetic divergence between geographically proximate colonies of a highly mobile seabird","interactions":[],"lastModifiedDate":"2020-11-30T20:05:34.775007","indexId":"70032584","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Foraging segregation and genetic divergence between geographically proximate colonies of a highly mobile seabird","docAbstract":"<p><span>Foraging segregation may play an important role in the maintenance of animal diversity, and is a proposed mechanism for promoting genetic divergence within seabird species. However, little information exists regarding its presence among seabird populations. We investigated genetic and foraging divergence between two colonies of endangered Hawaiian petrels (</span><i>Pterodroma sandwichensis</i><span>) nesting on the islands of Hawaii and Kauai using the mitochondrial&nbsp;</span><i>Cytochrome b</i><span>&nbsp;gene and carbon, nitrogen and hydrogen isotope values (δ</span><sup>13</sup><span>C, δ</span><sup>15</sup><span>N and δD, respectively) of feathers. Genetic analyses revealed strong differentiation between colonies on Hawaii and Kauai, with Φ</span><sub>ST</sub><span>&nbsp;=&nbsp;0.50 (</span><i>p</i><span>&nbsp;&lt;&nbsp;0.0001). Coalescent-based analyses gave estimates of &lt;1 migration event per 1,000 generations. Hatch-year birds from Kauai had significantly lower δ</span><sup>13</sup><span>C and δ</span><sup>15</sup><span>N values than those from Hawaii. This is consistent with Kauai birds provisioning chicks with prey derived from near or north of the Hawaiian Islands, and Hawaii birds provisioning young with prey from regions of the equatorial Pacific characterized by elevated δ</span><sup>15</sup><span>N values at the food web base. δ</span><sup>15</sup><span>N values of Kauai and Hawaii adults differed significantly, indicating additional foraging segregation during molt. Feather δD varied from −69 to 53‰. This variation cannot be related solely to an isotopically homogeneous ocean water source or evaporative water loss. Instead, we propose the involvement of salt gland excretion. Our data demonstrate the presence of foraging segregation between proximately nesting seabird populations, despite high species mobility. This ecological diversity may facilitate population coexistence, and its preservation should be a focus of conservation strategies.</span></p>","language":"English","publisher":"Springer- Verlag","doi":"10.1007/s00442-011-2085-y","issn":"00298549","usgsCitation":"Wiley, A.E., Welch, A., Ostrom, P., James, H.F., Stricker, C.A., Fleischer, R., Gandhi, H., Adams, J., Ainley, D., Duvall, F., Holmes, N., Hu, D., Judge, S., Penniman, J., and Swindle, K., 2012, Foraging segregation and genetic divergence between geographically proximate colonies of a highly mobile seabird: Oecologia, v. 168, no. 1, p. 119-130, https://doi.org/10.1007/s00442-011-2085-y.","productDescription":"12 p.","startPage":"119","endPage":"130","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research 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G.","affiliations":[],"preferred":false,"id":436929,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Duvall, F.","contributorId":89250,"corporation":false,"usgs":true,"family":"Duvall","given":"F.","email":"","affiliations":[],"preferred":false,"id":436933,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Holmes, N.","contributorId":105131,"corporation":false,"usgs":true,"family":"Holmes","given":"N.","email":"","affiliations":[],"preferred":false,"id":436935,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hu, D.","contributorId":11420,"corporation":false,"usgs":true,"family":"Hu","given":"D.","email":"","affiliations":[],"preferred":false,"id":436921,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Judge, S.","contributorId":99785,"corporation":false,"usgs":true,"family":"Judge","given":"S.","affiliations":[],"preferred":false,"id":436934,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Penniman, J.","contributorId":16661,"corporation":false,"usgs":true,"family":"Penniman","given":"J.","email":"","affiliations":[],"preferred":false,"id":436922,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Swindle, K.A.","contributorId":56414,"corporation":false,"usgs":true,"family":"Swindle","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":436927,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70032606,"text":"70032606 - 2012 - Reducing uncertainty about objective functions in adaptive management","interactions":[],"lastModifiedDate":"2020-11-30T17:51:50.10832","indexId":"70032606","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Reducing uncertainty about objective functions in adaptive management","docAbstract":"<p><span>This paper extends the uncertainty framework of adaptive management to include uncertainty about the objectives to be used in guiding decisions. Adaptive decision making typically assumes explicit and agreed-upon objectives for management, but allows for uncertainty as to the structure of the decision process that generates change through time. Yet it is not unusual for there to be uncertainty (or disagreement) about objectives, with different stakeholders expressing different views not only about resource responses to management but also about the appropriate management objectives. In this paper I extend the treatment of uncertainty in adaptive management, and describe a stochastic structure for the joint occurrence of uncertainty about objectives as well as models, and show how adaptive decision making and the assessment of post-decision monitoring data can be used to reduce uncertainties of both kinds. Different degrees of association between model and objective uncertainty lead to different patterns of learning about objectives.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2011.11.009","issn":"03043800","usgsCitation":"Williams, B.K., 2012, Reducing uncertainty about objective functions in adaptive management: Ecological Modelling, v. 225, p. 61-65, https://doi.org/10.1016/j.ecolmodel.2011.11.009.","productDescription":"5 p.","startPage":"61","endPage":"65","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":241728,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214041,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolmodel.2011.11.009"}],"volume":"225","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4a3d2e4b0e8fec6cdb9b8","contributors":{"authors":[{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":207067,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":437032,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70032617,"text":"70032617 - 2012 - Histologic, immunologic and endocrine biomarkers indicate contaminant effects in fishes of the Ashtabula River","interactions":[],"lastModifiedDate":"2013-03-25T15:07:01","indexId":"70032617","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Histologic, immunologic and endocrine biomarkers indicate contaminant effects in fishes of the Ashtabula River","docAbstract":"The use of fish as sentinels of aquatic ecosystem health is a biologically relevant approach to environmental monitoring and assessment. We examined the health of the Ashtabula River using histologic, immunologic, and endocrine biomarkers in brown bullhead (BB; Ameiurus nebulosus) and largemouth bass (Micropterus salmoides) and compared fish collected from a reference site (Conneaut Creek). Seasonal analysis was necessary to distinguish differences in fish between the two rivers. Overall BB from the Ashtabula River had a lower condition factor and significantly more macrophage aggregates than those from the reference site. Reduced bactericidal and cytotoxic-cell activity was observed in anterior kidney leukocytes from both BB and largemouth bass from the Ashtabula River. Lower plasma thyroxine and triiodo-L-thyronine in both species in the Ashtabula River indicated disruption of the thyroid axis. Differences in physiological biomarker responses were supported by body burden chemical concentrations when data were analyzed on a seasonal basis. The use of two fish species added a level of rigor that demonstrated biological effects were not exclusive to a single species. The results provide strong evidence that contaminants have affected fish in the Ashtabula River, a Great Lakes Area of Concern, and provide a baseline by which to evaluate remediation activities.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecotoxicology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10646-011-0776-0","issn":"09639292","usgsCitation":"Iwanowicz, L., Blazer, V., Hitt, N., McCormick, S., Devault, D., and Ottinger, C., 2012, Histologic, immunologic and endocrine biomarkers indicate contaminant effects in fishes of the Ashtabula River: Ecotoxicology, v. 21, no. 1, p. 165-182, https://doi.org/10.1007/s10646-011-0776-0.","productDescription":"18 p.","startPage":"165","endPage":"182","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":213697,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10646-011-0776-0"},{"id":241351,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Ashtabula River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.8203,38.4034 ], [ -84.8203,41.9773 ], [ -80.5182,41.9773 ], [ -80.5182,38.4034 ], [ -84.8203,38.4034 ] ] ] } } ] }","volume":"21","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-09-01","publicationStatus":"PW","scienceBaseUri":"505a3153e4b0c8380cd5de21","contributors":{"authors":[{"text":"Iwanowicz, L. R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":43864,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"L. R.","affiliations":[],"preferred":false,"id":437067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, V. S. 0000-0001-6647-9614","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":56991,"corporation":false,"usgs":true,"family":"Blazer","given":"V. S.","affiliations":[],"preferred":false,"id":437068,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hitt, N.P. 0000-0002-1046-4568","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":101466,"corporation":false,"usgs":true,"family":"Hitt","given":"N.P.","affiliations":[],"preferred":false,"id":437070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCormick, S. D. 0000-0003-0621-6200","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":20278,"corporation":false,"usgs":true,"family":"McCormick","given":"S. D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":437066,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Devault, D.S.","contributorId":87764,"corporation":false,"usgs":true,"family":"Devault","given":"D.S.","affiliations":[],"preferred":false,"id":437069,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ottinger, C. A. 0000-0003-2551-1985","orcid":"https://orcid.org/0000-0003-2551-1985","contributorId":8796,"corporation":false,"usgs":true,"family":"Ottinger","given":"C. A.","affiliations":[],"preferred":false,"id":437065,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70035463,"text":"70035463 - 2012 - GONe: Software for estimating effective population size in species with generational overlap","interactions":[],"lastModifiedDate":"2020-11-23T17:10:47.117736","indexId":"70035463","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2776,"text":"Molecular Ecology Resources","active":true,"publicationSubtype":{"id":10}},"title":"GONe: Software for estimating effective population size in species with generational overlap","docAbstract":"<p>GONe is a user‐friendly, Windows‐based program for estimating effective size (N<span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><i></i></span><sub>e</sub>) in populations with overlapping generations. It uses the Jorde–Ryman modification to the temporal method to account for age structure in populations. This method requires estimates of age‐specific survival and birth rate and allele frequencies measured in two or more consecutive cohorts. Allele frequencies are acquired by reading in genotypic data from files formatted for either GENEPOP or TEMPOFS. For each interval between consecutive cohorts, Ne is estimated at each locus and over all loci. Furthermore, Ne estimates are output for three different genetic drift estimators (<i>F</i><sub><i>s</i></sub><span>,&nbsp;</span><i>F</i><sub><i>c</i></sub><span>&nbsp;and&nbsp;</span><i>F</i><sub><i>k</i></sub>). Confidence intervals are derived from a chi‐square distribution with degrees of freedom equal to the number of independent alleles. GONe has been validated over a wide range of Ne values, and for scenarios where survival and birth rates differ between sexes, sex ratios are unequal and reproductive variances differ.</p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1755-0998.2011.03057.x","issn":"1755098X","usgsCitation":"Coombs, J., Letcher, B., and Nislow, K., 2012, GONe: Software for estimating effective population size in species with generational overlap: Molecular Ecology Resources, v. 12, no. 1, p. 160-163, https://doi.org/10.1111/j.1755-0998.2011.03057.x.","productDescription":"4 p.","startPage":"160","endPage":"163","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":242880,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215106,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1755-0998.2011.03057.x"}],"volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-08-09","publicationStatus":"PW","scienceBaseUri":"505a1478e4b0c8380cd54a4d","contributors":{"authors":[{"text":"Coombs, J.A.","contributorId":91295,"corporation":false,"usgs":true,"family":"Coombs","given":"J.A.","affiliations":[],"preferred":false,"id":450790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Letcher, B. H. 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":48132,"corporation":false,"usgs":true,"family":"Letcher","given":"B.","middleInitial":"H.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":450788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nislow, K.H.","contributorId":66477,"corporation":false,"usgs":true,"family":"Nislow","given":"K.H.","affiliations":[],"preferred":false,"id":450789,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70035364,"text":"70035364 - 2012 - Regulation leads to increases in riparian vegetation, but not direct allochthonous inputs, along the Colorado River in Grand Canyon, Arizona","interactions":[],"lastModifiedDate":"2012-03-12T17:21:56","indexId":"70035364","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Regulation leads to increases in riparian vegetation, but not direct allochthonous inputs, along the Colorado River in Grand Canyon, Arizona","docAbstract":"Dams and associated river regulation have led to the expansion of riparian vegetation, especially nonnative species, along downstream ecosystems. Nonnative saltcedar is one of the dominant riparian plants along virtually every major river system in the arid western United States, but allochthonous inputs have never been quantified along a segment of a large river that is dominated by saltcedar. We developed a novel method for estimating direct allochthonous inputs along the 387km-long reach of the Colorado River downstream of Glen Canyon Dam that utilized a GIS vegetation map developed from aerial photographs, empirical and literature-derived litter production data for the dominant vegetation types, and virtual shorelines of annual peak discharge (566m  3s  -1 stage elevation). Using this method, we estimate that direct allochthonous inputs from riparian vegetation for the entire reach studied total 186metric tonsyear  -1, which represents mean inputs of 470gAFDMm  -1year  -1 of shoreline or 5.17gAFDMm  -2year  -1 of river surface. These values are comparable to allochthonous inputs for other large rivers and systems that also have sparse riparian vegetation. Nonnative saltcedar represents a significant component of annual allochthonous inputs (36% of total direct inputs) in the Colorado River. We also estimated direct allochthonous inputs for 46.8km of the Colorado River prior to closure of Glen Canyon Dam using a vegetation map that was developed from historical photographs. Regulation has led to significant increases in riparian vegetation (270-319% increase in cover, depending on stage elevation), but annual allochthonous inputs appear unaffected by regulation because of the lower flood peaks on the post-dam river. Published in 2010 by John Wiley &amp; Sons, Ltd.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"River Research and Applications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1002/rra.1431","issn":"15351459","usgsCitation":"Kennedy, T., and Ralston, B., 2012, Regulation leads to increases in riparian vegetation, but not direct allochthonous inputs, along the Colorado River in Grand Canyon, Arizona: River Research and Applications, v. 28, no. 1, p. 2-12, https://doi.org/10.1002/rra.1431.","startPage":"2","endPage":"12","numberOfPages":"11","costCenters":[],"links":[{"id":242977,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215194,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/rra.1431"}],"volume":"28","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-04","publicationStatus":"PW","scienceBaseUri":"50e4a5f2e4b0e8fec6cdc02e","contributors":{"authors":[{"text":"Kennedy, T.A.","contributorId":86155,"corporation":false,"usgs":true,"family":"Kennedy","given":"T.A.","email":"","affiliations":[],"preferred":false,"id":450341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ralston, B.E.","contributorId":61662,"corporation":false,"usgs":true,"family":"Ralston","given":"B.E.","email":"","affiliations":[],"preferred":false,"id":450340,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
]}