The United States Geological Survey uses water-level (or stage) measurements to compute streamflow at over 8000 stream gaging stations located throughout the United States (waterwatch.usgs.gov, 2016). Streamflow (or discharge) is computed at five minute to hourly intervals from a relationship between water level and discharge that is uniquely determined for each station. The discharges are posted hourly to WaterWatch (waterwatch. usgs.gov) and are used by water managers to issue flood warnings and manage water supply and by other users of water information to make decisions. The accuracy of the water-level measurement is vital to the accuracy of the computed discharge. Because of the importance of water-level measurements, USGS has an accuracy policy of 0.02 ft or 0.2 percent of reading (whichever is larger) (Sauer and Turnipseed, 2010). Older technologies, such as float and shaft-encoder systems, bubbler systems and submersible pressure sensors, provide the needed accuracy but often require extensive construction to install and are prone to malfunctioning and damage from floating debris and sediment. No stilling wells or orifice lines need to be constructed for radar installations. During the last decade testing by the USGS Hydrologic Instrumentation Facility(HIF) found that radar water-level sensors can provide the needed accuracy for water-level measurements and because the sensor can be easily attached to bridges, reduce the construction required for installation. Additionally, the non-contact sensing of water level minimizes or eliminates damage and fouling from floating debris and sediment. This article is a brief summary of the testing efforts by the USGS HIF and field experiences with models of radar water-level sensors in streamflow measurement applications. Any use of trade names in this article is for descriptive purposes only and does not imply endorsement by the U.S. Government.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Manual on sea level: Measurement and interpretation Volume V: Radar gauges","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"United Nations Educational, Scientific and Cultural Organization","usgsCitation":"Fulford, J.M., 2016, Testing and use of radar water level sensors by the U.S. Geological Survey, 4 p.","productDescription":"4 p.","startPage":"121","endPage":"124","ipdsId":"IP-072695","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":352083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346989,"type":{"id":15,"text":"Index Page"},"url":"https://unesdoc.unesco.org/images/0024/002469/246981E.pdf"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afeea4ce4b0da30c1bfc5eb","contributors":{"authors":[{"text":"Fulford, Janice M. jfulford@usgs.gov","contributorId":991,"corporation":false,"usgs":true,"family":"Fulford","given":"Janice","email":"jfulford@usgs.gov","middleInitial":"M.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":714093,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70192004,"text":"70192004 - 2016 - Assessing the feasibility of using acoustic monitoring for Burbot conservation, management, and production","interactions":[],"lastModifiedDate":"2018-01-25T13:20:20","indexId":"70192004","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":" FWS/CSS-118-2016","title":"Assessing the feasibility of using acoustic monitoring for Burbot conservation, management, and production","docAbstract":"Burbot Lota lota is the sole freshwater representative of the cod-like fishes and supports subsistence, commercial, and recreational fisheries worldwide above approximately 40° N. It is a difficult species to manage effectively due to its preference for deep-water habitats and spawning activity under the ice in winter. Like other gadiform fishes, Burbot use acoustic signaling as part of their mating system, and while the acoustic repertoire of the species has been characterized under artificial conditions (i.e., net pen suspended under ice in a natural lake), there has been no work to determine whether the species is as vocal in natural spawning aggregations. Our objective was to assess the feasibility of collecting and using acoustic data to characterize the spawning activity and locations of Burbot under field conditions. We recorded audio and video of Burbot spawning aggregations through holes drilled into the ice at known spawning grounds at Moyie Lake in British Columbia, Canada. Acoustic recordings (call counts and audiograms) were analyzed using Raven Pro v 1. 4 software. Acoustic behavior was also related to video data to determine how acoustic activity correlated to any observed spawning behavior. In general, wild Burbot spawning in Moyie Lake did not vocalize as frequently as counterparts spawning under artificial conditions. Further, Burbot vocalizations were not recorded in conjunction with spawning activity. While it may be feasible to use passive acoustic monitoring to locate Burbot spawning grounds and identify periods of activity, it does not seem to hold much promise for locating and quantifying spawning activity in real time.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.13140/RG.2.1.4581.2881","usgsCitation":"Grabowski, T.B., 2016, Assessing the feasibility of using acoustic monitoring for Burbot conservation, management, and production: Cooperator Science Series FWS/CSS-118-2016, ii, 34 p., https://doi.org/10.13140/RG.2.1.4581.2881.","productDescription":"ii, 34 p.","numberOfPages":"36","ipdsId":"IP-072721","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":350614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350613,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/cdm/ref/collection/document/id/2126"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6afac6e4b06e28e9c9a901","contributors":{"authors":[{"text":"Grabowski, Timothy B. 0000-0001-9763-8948 tgrabowski@usgs.gov","orcid":"https://orcid.org/0000-0001-9763-8948","contributorId":4178,"corporation":false,"usgs":true,"family":"Grabowski","given":"Timothy","email":"tgrabowski@usgs.gov","middleInitial":"B.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":713831,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70191990,"text":"70191990 - 2016 - Evaluation and refinement of Guadalupe Bass conservation strategies to support adaptive management","interactions":[],"lastModifiedDate":"2018-01-25T13:23:19","indexId":"70191990","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-118-2016","title":"Evaluation and refinement of Guadalupe Bass conservation strategies to support adaptive management","docAbstract":"Burbot Lota lota is the sole freshwater representative of the cod-like fishes and supports subsistence, commercial, and recreational fisheries worldwide above approximately 40° N. It is a difficult species to manage effectively due to its preference for deep-water habitats and spawning activity under the ice in winter. Like other gadiform fishes, Burbot use acoustic signaling as part of their mating system, and while the acoustic repertoire of the species has been characterized under artificial conditions (i.e., net pen suspended under ice in a natural lake), there has been no work to determine whether the species is as vocal in natural spawning aggregations. Our objective was to assess the feasibility of collecting and using acoustic data to characterize the spawning activity and locations of Burbot under field conditions. We recorded audio and video of Burbot spawning aggregations through holes drilled into the ice at known spawning grounds at Moyie Lake in British Columbia, Canada. Acoustic recordings (call counts and audiograms) were analyzed using Raven Pro v 1. 4 software. Acoustic behavior was also related to video data to determine how acoustic activity correlated to any observed spawning behavior. In general, wild Burbot spawning in Moyie Lake did not vocalize as frequently as counterparts spawning under artificial conditions. Further, Burbot vocalizations were not recorded in conjunction with spawning activity. While it may be feasible to use passive acoustic monitoring to locate Burbot spawning grounds and identify periods of activity, it does not seem to hold much promise for locating and quantifying spawning activity in real time.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Grabowski, T.B., 2016, Evaluation and refinement of Guadalupe Bass conservation strategies to support adaptive management: Cooperator Science Series FWS/CSS-118-2016, ii, 34 p.","productDescription":"ii, 34 p.","numberOfPages":"36","ipdsId":"IP-061759","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":350616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350615,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/cdm/ref/collection/document/id/2126"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6afac7e4b06e28e9c9a90c","contributors":{"authors":[{"text":"Grabowski, Timothy B. 0000-0001-9763-8948 tgrabowski@usgs.gov","orcid":"https://orcid.org/0000-0001-9763-8948","contributorId":4178,"corporation":false,"usgs":true,"family":"Grabowski","given":"Timothy","email":"tgrabowski@usgs.gov","middleInitial":"B.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":713817,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70191935,"text":"70191935 - 2016 - San Pedro River Aquifer Binational Report","interactions":[],"lastModifiedDate":"2023-12-20T21:24:11.302348","indexId":"70191935","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"San Pedro River Aquifer Binational Report","docAbstract":"The United States and Mexico share waters in a number of hydrological basins and aquifers that cross the international boundary. Both countries recognize that, in a region of scarce water resources and expanding populations, a greater scientific understanding of these aquifer systems would be beneficial. In light of this, the Mexican and U.S. Principal Engineers of the International Boundary and Water Commission (IBWC) signed the “Joint Report of the Principal Engineers Regarding the Joint Cooperative Process United States-Mexico for the Transboundary Aquifer Assessment Program\" on August 19, 2009 (IBWC-CILA, 2009). This IBWC “Joint Report” serves as the framework for U.S.-Mexico coordination and dialogue to implement transboundary aquifer studies. The document clarifies several details about the program such as background, roles, responsibilities, funding, relevance of the international water treaties, and the use of information collected or compiled as part of the program. In the document, it was agreed by the parties involved, which included the IBWC, the Mexican National Water Commission (CONAGUA), the U.S. Geological Survey (USGS), and the Universities of Arizona and Sonora, to study two priority binational aquifers, one in the San Pedro River basin and the other in the Santa Cruz River basin.
This report focuses on the Binational San Pedro Basin (BSPB). Reasons for the focus on and interest in this aquifer include the fact that it is shared by the two countries, that the San Pedro River has an elevated ecological value because of the riparian ecosystem that it sustains, and that water resources are needed to sustain the river, existing communities, and continued development. This study describes the aquifer’s characteristics in its binational context; however, most of the scientific work has been undertaken for many years by each country without full knowledge of the conditions on the other side of the border. The general objective of this study is to use new and existing research to define the general hydrologic framework of the Binational San Pedro Aquifer (BSPA), to gather hydrogeological and other relevant data in preparation for future work such as an updated groundwater conceptual model and budget and to establish the basis for a binational numerical model.
The specific objectives are as follows:
The BSPB is one of the most studied basins in the region, and a database of publications has been compiled as part of this project. Previous studies include topics that range from geophysics and hydrogeology to biology and ecosystem services. The economic drivers on each side of the border are quite different. In the Arizona 4 portion of the basin military and tourism dominate while in the Sonoran portion, mining is the most important industry. Water management is also different in the two countries. In Mexico, primary authority for management of water resources devolves from the federal government. In the United States, primary authority rests with the states except in cases of interstate surface waters. Binational waters are not currently jointly managed by the two countries except in cases where treaties have been negotiated such as for the Rio Grande and Colorado Rivers. Thus, there is currently no binational coordination or treaty governing the management of groundwater.
Polyoxyethylene tallow amine (POEA) is an inert ingredient added to formulations of glyphosate, the most widely applied agricultural herbicide. POEA has been shown to have toxic effects to some aquatic organisms making the potential transport of POEA from the application site into the environment an important concern. This study characterized the adsorption of POEA to soils and assessed its occurrence and homologue distribution in agricultural soils from six states. Adsorption experiments of POEA to selected soils showed that POEA adsorbed much stronger than glyphosate; calcium chloride increased the binding of POEA; and the binding of POEA was stronger in low pH conditions. POEA was detected on a soil sample from an agricultural field near Lawrence, Kansas, but with a loss of homologues that contain alkenes. POEA was also detected on soil samples collected between February and early March from corn and soybean fields from ten different sites in five other states (Iowa, Illinois, Indiana, Missouri, Mississippi). This is the first study to characterize the adsorption of POEA to soil, the potential widespread occurrence of POEA on agricultural soils, and the persistence of the POEA homologues on agricultural soils into the following growing season.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.6b00965","usgsCitation":"Tush, D.L., and Meyer, M.T., 2016, Polyoxyethylene tallow amine, a glyphosate formulation adjuvant: Soil adsorption characteristics, degradation profile, and occurrence on selected soils from agricultural fields in Iowa, Illinois, Indiana, Kansas, Mississippi, and Missouri: Environmental Science & Technology, v. 50, no. 11, p. 5781-5789, https://doi.org/10.1021/acs.est.6b00965.","productDescription":"9 p.","startPage":"5781","endPage":"5789","ipdsId":"IP-065815","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":346722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Illinois, Indiana, Kansas, Mississippi, Missouri","volume":"50","issue":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-18","publicationStatus":"PW","scienceBaseUri":"59e71693e4b05fe04cd331c0","contributors":{"authors":[{"text":"Tush, Daniel L. 0000-0003-0031-3501 dtush@usgs.gov","orcid":"https://orcid.org/0000-0003-0031-3501","contributorId":4538,"corporation":false,"usgs":true,"family":"Tush","given":"Daniel","email":"dtush@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":712857,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyer, Michael T. 0000-0001-6006-7985 mmeyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":866,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael","email":"mmeyer@usgs.gov","middleInitial":"T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":712858,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191228,"text":"70191228 - 2016 - High performance computing to support multiscale representation of hydrography for the conterminous United States","interactions":[],"lastModifiedDate":"2017-10-04T08:41:29","indexId":"70191228","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"High performance computing to support multiscale representation of hydrography for the conterminous United States","docAbstract":"The National Hydrography Dataset (NHD) for the United States furnishes a comprehensive set of vector features representing the surface-waters in the country (U.S. Geological Survey 2000). The high-resolution (HR) layer of the NHD is largely comprised of hydrographic features originally derived from 1:24,000-scale (24K) U.S. Topographic maps. However, in recent years (2009 to present) densified hydrographic feature content, from sources as large as 1:2,400, have been incorporated into some watersheds of the HR NHD within the conterminous United States to better support the needs of various local and state organizations. As such, the HR NHD is a multiresolution dataset with obvious data density variations because of scale changes. In addition, data density variations exist within the HR NHD that are particularly evident in the surface-water flow network (NHD flowlines) because of natural variations of local geographic conditions; and also because of unintentional compilation inconsistencies due to variations in data collection standards and climate conditions over the many years of 24K hydrographic data collection (US Geological Survey 1955).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"19th ICA Workshop, Automated Generalisation for On-Demand Mapping","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"International Cartographic Association Commission on Generlisation and Multiple Representation","usgsCitation":"Stanislawski, L.V., Liu, Y., Buttenfield, B., Survila, K., Wendel, J., and Okok, A., 2016, High performance computing to support multiscale representation of hydrography for the conterminous United States, in 19th ICA Workshop, Automated Generalisation for On-Demand Mapping, 10 p.","productDescription":"10 p.","ipdsId":"IP-076465","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":346350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346295,"type":{"id":15,"text":"Index Page"},"url":"https://generalisation.icaci.org/prevevents/95-workshop2016program.html"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d4a1abe4b05fe04cc4e10a","contributors":{"authors":[{"text":"Stanislawski, Larry V. 0000-0002-9437-0576 lstan@usgs.gov","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":3386,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","email":"lstan@usgs.gov","middleInitial":"V.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":711622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Yan 0000-0003-2298-4728","orcid":"https://orcid.org/0000-0003-2298-4728","contributorId":196790,"corporation":false,"usgs":false,"family":"Liu","given":"Yan","email":"","affiliations":[],"preferred":false,"id":711623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buttenfield, Barbara P.","contributorId":145538,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":711624,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Survila, Kornelijus 0000-0003-4851-6084","orcid":"https://orcid.org/0000-0003-4851-6084","contributorId":196791,"corporation":false,"usgs":false,"family":"Survila","given":"Kornelijus","email":"","affiliations":[],"preferred":false,"id":711625,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wendel, Jeffrey 0000-0003-0294-0250 jwendel@usgs.gov","orcid":"https://orcid.org/0000-0003-0294-0250","contributorId":196792,"corporation":false,"usgs":true,"family":"Wendel","given":"Jeffrey","email":"jwendel@usgs.gov","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":711626,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Okok, Abdurraouf","contributorId":196793,"corporation":false,"usgs":false,"family":"Okok","given":"Abdurraouf","email":"","affiliations":[],"preferred":false,"id":711627,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198170,"text":"70198170 - 2016 - Nutrient dynamics of the Delta: Effects on primary producers","interactions":[],"lastModifiedDate":"2018-07-18T16:03:45","indexId":"70198170","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Nutrient dynamics of the Delta: Effects on primary producers","docAbstract":"Increasing clarity of Delta waters, the emergence of harmful algal blooms, the proliferation of aquatic water weeds, and the altered food web of the Delta have brought nutrient dynamics to the forefront. This paper focuses on the sources of nutrients, the transformation and uptake of nutrients, and the links of nutrients to primary producers. The largest loads of nutrients to the Delta come from the Sacramento River with the San Joaquin River seasonally important, especially in the summer. Nutrient concentrations reflect riverine inputs in winter and internal biological processes during periods of lower flow with internal nitrogen losses within the Delta estimated at approximately 30% annually. Light regime, grazing pressure, and nutrient availability influence rates of primary production at different times and locations within the Delta. The roles of the chemical form of dissolved inorganic nitrogen in growth rates of primary producers in the Delta and the structure of the open-water algal community are currently topics of much interest and considerable debate. Harmful algal blooms have been noted since the late 1990s, and the extent of invasive aquatic macrophytes (both submerged and free-floating forms) has increased especially during years of drought. Elevated nutrient loads must be considered in terms of their ability to support this excess biomass. Modern sensor technology and networks are now deployed that make high-frequency measurements of nitrate, ammonium, and phosphate. Data from such instruments allow a much more detailed assessment of the spatial and temporal dynamics of nutrients. Four fruitful directions for future research include utilizing continuous sensor data to estimate rates of primary production and ecosystem respiration, linking hydrodynamic models of the Delta with the transport and fate of dissolved nutrients, studying nutrient dynamics in various habitat types, and exploring the use of stable isotopes to trace the movement and fate of effluent-derived nutrients.
","language":"English","publisher":"University of California","doi":"10.15447/sfews.2016v14iss4art4","usgsCitation":"Dahm, C., Parker, A.E., Adelson, A.E., Christman, M.A., and Bergamaschi, B.A., 2016, Nutrient dynamics of the Delta: Effects on primary producers: San Francisco Estuary and Watershed Science, v. 14, no. 4, Article 4; 35 p., https://doi.org/10.15447/sfews.2016v14iss4art4.","productDescription":"Article 4; 35 p.","ipdsId":"IP-099451","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":471375,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2016v14iss4art4","text":"Publisher Index Page"},{"id":355816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.13775634765625,\n 37.73053874574077\n ],\n [\n -121.25610351562499,\n 37.73053874574077\n ],\n [\n -121.25610351562499,\n 38.25112269630296\n ],\n [\n -122.13775634765625,\n 38.25112269630296\n ],\n [\n -122.13775634765625,\n 37.73053874574077\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-28","publicationStatus":"PW","scienceBaseUri":"5b6fca10e4b0f5d57878ec8c","contributors":{"authors":[{"text":"Dahm, Clifford N.","contributorId":22730,"corporation":false,"usgs":false,"family":"Dahm","given":"Clifford N.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":740403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parker, Alexander E.","contributorId":206434,"corporation":false,"usgs":false,"family":"Parker","given":"Alexander","email":"","middleInitial":"E.","affiliations":[{"id":37328,"text":"California State University Maritime Academy Vallejo, CA","active":true,"usgs":false}],"preferred":false,"id":740404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adelson, Anne E.","contributorId":206435,"corporation":false,"usgs":false,"family":"Adelson","given":"Anne","email":"","middleInitial":"E.","affiliations":[{"id":37329,"text":"Delta Stewardship Council Sacramento, CA","active":true,"usgs":false}],"preferred":false,"id":740405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christman, Mairgareth A.","contributorId":206436,"corporation":false,"usgs":false,"family":"Christman","given":"Mairgareth","email":"","middleInitial":"A.","affiliations":[{"id":37330,"text":"Delta Stewardship Council, Sacramento, CA","active":true,"usgs":false}],"preferred":false,"id":740406,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":740402,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190606,"text":"70190606 - 2016 - Acoustic doppler velocimeter backscatter for quantification of suspended sediment concentration in South San Francisco Bay","interactions":[],"lastModifiedDate":"2017-09-11T10:17:43","indexId":"70190606","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Acoustic doppler velocimeter backscatter for quantification of suspended sediment concentration in South San Francisco Bay","docAbstract":"A data set was acquired on a shallow mudflat in south San Francisco Bay that featured simultaneous, co-located optical and acoustic sensors for subsequent estimation of suspended sediment concentrations (SSC). The optical turbidity sensor output was converted to SSC via an empirical relation derived at a nearby site using bottle sample estimates of SSC. The acoustic data was obtained using an acoustic Doppler velocimeter. Backscatter and noise were combined to develop another empirical relation between the optical estimates of SSC and the relative backscatter from the acoustic velocimeter. The optical and acoustic approaches both reproduced similar general trends in the data and have merit. Some seasonal variation in the dataset was evident, with the two methods differing by greater or lesser amounts depending on which portion of the record was examined. It is hypothesized that this is the result of flocculation, affecting the two signals by different degrees, and that the significance or mechanism of the flocculation has some seasonal variability. In the earlier portion of the record (March), there is a clear difference that appears in the acoustic approach between ebb and flood periods, and this is not evident later in the record (May). The acoustic method has promise but it appears that characteristics of flocs that form and break apart may need to be accounted for to improve the power of the method. This may also be true of the optical method: both methods involve assuming that the sediment characteristics (size, size distribution, and shape) are constant
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","language":"English","publisher":"Taylor & Francis","doi":"10.1080/IW-6.4.883","usgsCitation":"Winslow, L., Zwart, J., Batt, R., Dugan, H., Woolway, R., Corman, J., Hanson, P.C., and Read, J.S., 2016, LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models: Inland Waters, v. 6, no. 4, p. 622-636, https://doi.org/10.1080/IW-6.4.883.","productDescription":"15 p.","startPage":"622","endPage":"636","ipdsId":"IP-065534","costCenters":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"links":[{"id":349534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-02","publicationStatus":"PW","scienceBaseUri":"5a60fd87e4b06e28e9c24fa5","contributors":{"authors":[{"text":"Winslow, Luke 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":168947,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":723877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zwart, Jacob A.","contributorId":173345,"corporation":false,"usgs":false,"family":"Zwart","given":"Jacob A.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":723878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Batt, Ryan D.","contributorId":168948,"corporation":false,"usgs":false,"family":"Batt","given":"Ryan D.","affiliations":[{"id":25393,"text":"Department of Ecology, Evolution, and Natural Resources, Rutgers University, New Brunswick, New Jersey, USA 08901","active":true,"usgs":false}],"preferred":false,"id":723879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dugan, Hilary A.","contributorId":150191,"corporation":false,"usgs":false,"family":"Dugan","given":"Hilary","middleInitial":"A.","affiliations":[{"id":17938,"text":"Center for Limnology University of Wisconsin, Madison, WI 53706, US","active":true,"usgs":false}],"preferred":false,"id":723880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woolway, R. 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Historically, polar bears (Ursus maritimus) of the SB have mostly remained on the sea ice year-round (except for those that came ashore to den), but recent changes in the extent and phenology of sea ice habitat have coincided with evidence that use of terrestrial habitat is increasing. We characterized the spatial behavior of polar bears spending summer and fall on land along Alaska’s north coast to better understand the nexus between rapid environmental change and increased use of terrestrial habitat. We found that the percentage of radiocollared adult females from the SB subpopulation coming ashore has tripled over 15 years. Moreover, we detected trends of earlier arrival on shore, increased length of stay, and later departure back to sea ice, all of which were related to declines in the availability of sea ice habitat over the continental shelf and changes to sea ice phenology. Since the late 1990s, the mean duration of the open-water season in the SB increased by 36 days, and the mean length of stay on shore increased by 31 days. While on shore, the distribution of polar bears was influenced by the availability of scavenge subsidies in the form of subsistence-harvested bowhead whale (Balaena mysticetus) remains aggregated at sites along the coast. The declining spatio-temporal availability of sea ice habitat and increased availability of human-provisioned resources are likely to result in increased use of land. Increased residency on land is cause for concern given that, while there, bears may be exposed to a greater array of risk factors including those associated with increased human activities.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0155932","usgsCitation":"Atwood, T.C., Peacock, E.L., McKinney, M.A., Lillie, K., Wilson, R.H., Douglas, D.C., Miller, S., and Terletzky, P., 2016, Rapid environmental change drives increased land use by an Arctic marine predator: PLoS ONE, v. 6, no. 11, Article e0155932; 18 p., https://doi.org/10.1371/journal.pone.0155932.","productDescription":"Article e0155932; 18 p.","ipdsId":"IP-072257","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":471388,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0155932","text":"Publisher Index Page"},{"id":341326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, Yukon","otherGeospatial":"Southern Beaufort Sea","volume":"6","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-01","publicationStatus":"PW","scienceBaseUri":"591abe37e4b0a7fdb43c8bf7","contributors":{"authors":[{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":695266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peacock, Elizabeth L. 0000-0001-7279-0329 lpeacock@usgs.gov","orcid":"https://orcid.org/0000-0001-7279-0329","contributorId":3361,"corporation":false,"usgs":true,"family":"Peacock","given":"Elizabeth","email":"lpeacock@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":false,"id":695552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKinney, Melissa A.","contributorId":11496,"corporation":false,"usgs":false,"family":"McKinney","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":6619,"text":"University of Connecticutt","active":true,"usgs":false}],"preferred":false,"id":695267,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lillie, Kate","contributorId":148213,"corporation":false,"usgs":false,"family":"Lillie","given":"Kate","affiliations":[{"id":17117,"text":"Department of Wildland Resources, Utah State University, Logan","active":true,"usgs":false}],"preferred":false,"id":695268,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":695269,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":695270,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Terletzky, Pat","contributorId":192063,"corporation":false,"usgs":false,"family":"Terletzky","given":"Pat","affiliations":[{"id":12682,"text":"Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":695272,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Miller, Susanne","contributorId":50955,"corporation":false,"usgs":false,"family":"Miller","given":"Susanne","email":"","affiliations":[{"id":13235,"text":"U.S. Fish and Wildlife Service, Marine Mammals Management","active":true,"usgs":false}],"preferred":false,"id":695271,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70169002,"text":"70169002 - 2016 - Rating curve uncertainty: A comparison of estimation methods","interactions":[],"lastModifiedDate":"2017-04-25T10:35:59","indexId":"70169002","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Rating curve uncertainty: A comparison of estimation methods","docAbstract":"The USGS is engaged in both internal development and collaborative efforts to evaluate existing methods for characterizing the uncertainty of streamflow measurements (gaugings), stage-discharge relations (ratings), and, ultimately, the streamflow records derived from them. This paper provides a brief overview of two candidate methods that may be used to characterize the uncertainty of ratings, and illustrates the results of their application to the ratings of the two USGS streamgages.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the international conference on fluvial hydraulics (river flow 2016)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"International Conference on Fluvial Hydraulics (River Flow 2016)","conferenceDate":"July 11-14, 2016","conferenceLocation":"St. Louis, MO","language":"English","publisher":"CRC Press","doi":"10.1201/9781315644479-115","isbn":"978-1-138-02913-2","usgsCitation":"Mason, Kiang, J.E., and Cohn, T., 2016, Rating curve uncertainty: A comparison of estimation methods, in Proceedings of the international conference on fluvial hydraulics (river flow 2016), St. Louis, MO, July 11-14, 2016, p. 729-734, https://doi.org/10.1201/9781315644479-115.","productDescription":"6 p.","startPage":"729","endPage":"734","ipdsId":"IP-073963","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":340158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-06","publicationStatus":"PW","scienceBaseUri":"58ff0e9ee4b006455f2d61c4","contributors":{"editors":[{"text":"Constantinescu, George","contributorId":174167,"corporation":false,"usgs":false,"family":"Constantinescu","given":"George","email":"","affiliations":[{"id":7241,"text":"IIHR-Hydroscience and Engineering, Department of Civil and Environmental Engineering, The University of Iowa","active":true,"usgs":false}],"preferred":false,"id":692521,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Garcia, Marcelo H.","contributorId":74236,"corporation":false,"usgs":false,"family":"Garcia","given":"Marcelo H.","affiliations":[{"id":33106,"text":"University of Illinois at Urbana Champaign","active":true,"usgs":false}],"preferred":false,"id":692522,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Hanes, Dan","contributorId":174168,"corporation":false,"usgs":false,"family":"Hanes","given":"Dan","email":"","affiliations":[{"id":12995,"text":"Department of Earth and Atmospheric Sciences, Saint Louis University","active":true,"usgs":false}],"preferred":false,"id":692523,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Mason, Jr. 0000-0002-3998-3468 rrmason@usgs.gov","orcid":"https://orcid.org/0000-0002-3998-3468","contributorId":2090,"corporation":false,"usgs":true,"family":"Mason","suffix":"Jr.","email":"rrmason@usgs.gov","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":622465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":622466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cohn, Timothy A. tacohn@usgs.gov","contributorId":2927,"corporation":false,"usgs":true,"family":"Cohn","given":"Timothy A.","email":"tacohn@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":622467,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173765,"text":"70173765 - 2016 - Consequences of seasonal variation in reservoir water level for predatory fishes: linking visual foraging and prey densities","interactions":[],"lastModifiedDate":"2016-06-21T15:53:42","indexId":"70173765","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Consequences of seasonal variation in reservoir water level for predatory fishes: linking visual foraging and prey densities","docAbstract":"In reservoirs, seasonal drawdown can alter the physical environment and may influence predatory fish performance. We investigated the performance of lake trout (Salvelinus namaycush) in a western reservoir by coupling field measurements with visual foraging and bioenergetic models at four distinct states (early summer, mid-summer, late summer, and fall). The models suggested that lake trout prey, juvenile kokanee (Oncorhynchus nerka), are limited seasonally by suitable temperature and dissolved oxygen. Accordingly, prey densities were greatest in late summer when reservoir volume was lowest and fish were concentrated by stratification. Prey encounter rates (up to 68 fish·day−1) and predator consumption are also predicted to be greatest during late summer. However, our models suggested that turbidity negatively correlates with prey detection and consumption across reservoir states. Under the most turbid conditions, lake trout did not meet physiological demands; however, during less turbid periods, predator consumption reached maximum bioenergetic efficiency. Overall, our findings demonstrate that rapid reservoir fluctuations and associated abiotic conditions can influence predator–prey interactions, and our models describe the potential impacts of water level fluctuation on valuable sport fishes.
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","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the SPE/IAEE hydrocarbon economics and evaluation symposium 2016","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SPE/IAEE Hydrocarbon Economics and Evaluation Symposium 2016","conferenceDate":"May 17-18, 2016","conferenceLocation":"Houston, TX","language":"English","publisher":"Society of Petroleum Engineers","publisherLocation":"Richardson, TX","doi":"10.2118/179997-MS","isbn":"9781510831292","usgsCitation":"Attanasi, E., 2016, A strategy for low cost development of incremental oil in legacy reservoirs, in Proceedings of the SPE/IAEE hydrocarbon economics and evaluation symposium 2016, Houston, TX, May 17-18, 2016, p. 636-652, https://doi.org/10.2118/179997-MS.","productDescription":"17 p.","startPage":"636","endPage":"652","ipdsId":"IP-073305","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":340145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-10","publicationStatus":"PW","scienceBaseUri":"58ff0e9ee4b006455f2d61c6","contributors":{"authors":[{"text":"Attanasi, Emil 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":1809,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":620942,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70169860,"text":"70169860 - 2016 - Status and trends in the Lake Superior fish community, 2015","interactions":[],"lastModifiedDate":"2018-03-28T13:37:53","indexId":"70169860","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Status and trends in the Lake Superior fish community, 2015","docAbstract":"In 2015, the Lake Superior fish community was sampled with daytime bottom trawls at 76 nearshore and 33 offshore stations. Spring and summer water temperatures in 2015 were colder than average, but warmer than that observed in 2014. In the nearshore zone, a total of 11,882 individuals from 22 species or morphotypes were collected. Nearshore lakewide mean biomass was 1.8 kg/ha, which was near the lowest biomass on record for this survey since it began in 1978. In the offshore zone, a total 12,433 individuals from 8 species or morphotypes were collected lakewide. Offshore lakewide mean biomass was 5.9 kg/ha. The mean of the four previous years was 7.1 kg/ha. The abundance of age-1 Cisco was 14.3 fish/ha which was similar to that measured in 2009. We collected larval Coregonus in surface trawls at 94 locations and estimated a nearshore lakewide average density of 1,459 fish/ha which was nearly twice that measured in 2014.
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chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Succession in wetlands","docAbstract":"Succession refers to the change in vegetation over time driven by disturbances and the maturation of plant species. In wetlands, these disturbances include water and salinity level changes along other factors that can alter vegetation. The historical view of succession (Clementsian) was that vegetation change represented the linear progression of through stages of vegetation toward a climax state. These stages were thought to be comprised of species that were interlocked with each other. These days the idea that succession is represented by the successive replacement of highly related sets of communities over time has been deemphasized, in favor of the idea that species in the community act more independently of one another (Gleasonian). An important example of this Gleasonian perspective model has been developed for prairie wetlands of North America by van der Valk. In this view, succession proceeds in a cyclic fashion, with flooding and drought driving changes in specific species, so that the individualistic species responses to water regime and other disturbances drive changes in the system (environmental sieve model). The succession of many other world wetlands types is thought to occur in a similar way. These recent ideas of succession emphasize that species that are able to regenerate after disturbance via seed banks and propagules, and that the nature of post-disturbance regeneration is the most important determinant of later succession (initial floristics). Notably, the idea that lakes and bogs represent an early state of succession, and that depressions fill in to become dry land (terrestrialization) has little evidence. With climate change, wetlands are likely to have altered successional trajectories, particularly as these ecosystems become exposed to different climatic temperatures, flooding/drought cycles, salinity intrusion and increased CO2.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The Wetland Book","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-94-007-6172-8_1-2","isbn":"978-94-007-6172-8","usgsCitation":"Middleton, B.A., 2016, Succession in wetlands, chap. of The Wetland Book, 18 p., https://doi.org/10.1007/978-94-007-6172-8_1-2.","productDescription":"18 p.","ipdsId":"IP-026617","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":357150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2016-12-12","publicationStatus":"PW","scienceBaseUri":"5b98a6cfe4b0702d0e8430d7","contributors":{"editors":[{"text":"Finlayson, C. Max","contributorId":96573,"corporation":false,"usgs":true,"family":"Finlayson","given":"C. 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The U.S.\r\nGeological Survey (USGS) conducted a study from\r\nJune through August 2015 to investigate the effects of\r\nwater quality on phytoplankton species and density and\r\ntrophic state in Big Base and Little Base Lakes, with\r\nparticular regard to nutrient concentrations. Nutrient\r\nconcentrations, trophic-state indices, and the large part\r\nof the phytoplankton biovolume composed of\r\ncyanobacteria, indicate eutrophic conditions were\r\nprevalent for Big Base and Little Base Lakes,\r\nparticularly in August 2015. Cyanobacteria densities\r\nand biovolumes measured in this study likely pose a\r\nlow to moderate risk of adverse algal toxicity, and the\r\nhigh proportion of filamentous cyanobacteria in the\r\nlakes, in relation to other algal groups, is important\r\nfrom a fisheries standpoint because these algae are a\r\npoor food source for many aquatic taxa. In both lakes,\r\ntotal nitrogen to total phosphorus (N:P) ratios declined\r\nover the sampling period as total phosphorus\r\nconcentrations increased relative to nitrogen\r\nconcentrations. The N:P ratios in the August samples\r\n(20:1 and 15:1 in Big Base and Little Base Lakes,\r\nrespectively) and other indications of eutrophic\r\nconditions are of concern and suggest that exposure of\r\nthe two lakes to additional nutrients could cause\r\nunfavorable dissolved-oxygen conditions and increase\r\nthe risk of cyanobacteria blooms and associated\r\ncyanotoxin issues.","language":"English","publisher":"Arkansas Academy of Science","usgsCitation":"Driver, L., and Justus, B., 2016, Water-quality effects on phytoplankton species and density and trophic state indices at Big Base and Little Base Lakes, Little Rock Air Force Base, Arkansas, June through August, 2015: Journal of the Arkansas Academy of Science, v. 70, no. 1, p. 88-95.","productDescription":"8 p.","startPage":"88","endPage":"95","ipdsId":"IP-074006","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":347379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346820,"type":{"id":15,"text":"Index Page"},"url":"https://scholarworks.uark.edu/jaas/vol70/iss1/16"}],"country":"United States","state":"Arkansas","otherGeospatial":"Big Base Lake, Little Base Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.17520713806152,\n 34.888395122782164\n ],\n [\n -92.1556806564331,\n 34.888395122782164\n ],\n [\n -92.1556806564331,\n 34.904375309375645\n ],\n [\n -92.17520713806152,\n 34.904375309375645\n ],\n [\n -92.17520713806152,\n 34.888395122782164\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"70","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2a8e4b0220bbd9d9f8d","contributors":{"authors":[{"text":"Driver, Lucas ldriver@usgs.gov","contributorId":197344,"corporation":false,"usgs":true,"family":"Driver","given":"Lucas","email":"ldriver@usgs.gov","affiliations":[],"preferred":true,"id":713230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Justus, Billy bjustus@usgs.gov","contributorId":152446,"corporation":false,"usgs":true,"family":"Justus","given":"Billy","email":"bjustus@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713229,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168829,"text":"70168829 - 2016 - Water-quality response to a high-elevation wildfire in the Colorado Front Range","interactions":[],"lastModifiedDate":"2021-04-20T13:20:37.020538","indexId":"70168829","displayToPublicDate":"2015-12-29T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Water-quality response to a high-elevation wildfire in the Colorado Front Range","docAbstract":"Water quality of the Big Thompson River in the Front Range of Colorado was studied for 2 years following a high‐elevation wildfire that started in October 2012 and burned 15% of the watershed. A combination of fixed‐interval sampling and continuous water‐quality monitors was used to examine the timing and magnitude of water‐quality changes caused by the wildfire. Prefire water quality was well characterized because the site has been monitored at least monthly since the early 2000s. Major ions and nitrate showed the largest changes in concentrations; major ion increases were greatest in the first postfire snowmelt period, but nitrate increases were greatest in the second snowmelt period. The delay in nitrate release until the second snowmelt season likely reflected a combination of factors including fire timing, hydrologic regime, and rates of nitrogen transformations. Despite the small size of the fire, annual yields of dissolved constituents from the watershed increased 20–52% in the first 2 years following the fire. Turbidity data from the continuous sensor indicated high‐intensity summer rain storms had a much greater effect on sediment transport compared to snowmelt. High‐frequency sensor data also revealed that weekly sampling missed the concentration peak during snowmelt and short‐duration spikes during rain events, underscoring the challenge of characterizing postfire water‐quality response with fixed‐interval sampling.
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Hurricane Sandy made landfall during an investigation in Barnegat Bay-Little Egg Harbor estuary that included water quality monitoring, geomorphologic characterization, and numerical modeling; this provided an opportunity to characterize the storm response of the barrier island-estuary system. Barrier island morphologic response was characterized by significant changes in shoreline position, dune elevation, and beach volume; morphologic changes within the estuary were less dramatic with a net gain of only 200,000 m3 of sediment. When observed, estuarine deposition was adjacent to the back-barrier shoreline or collocated with maximum estuary depths. Estuarine sedimentologic changes correlated well with bed shear stresses derived from numerically simulated storm conditions, suggesting that change is linked to winnowing from elevated storm-related wave-current interactions rather than deposition. Rapid storm-related changes in estuarine water level, turbidity, and salinity were coincident with minima in island and estuarine widths, which may have influenced the location of two barrier island breaches. Barrier-estuary connectivity, or the transport of sediment from barrier island to estuary, was influenced by barrier island land use and width. Coupled assessments like this one provide critical information about storm-related coastal and estuarine sediment transport that may not be evident from investigations that consider only one component of the coastal system.
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hydrologic evidence","docAbstract":"Explosives used in construction have been implicated as sources of NO3– contamination in groundwater, but direct forensic evidence is limited. Identification of blasting-related NO3– can be complicated by other NO3– sources, including agriculture and wastewater disposal, and by hydrogeologic factors affecting NO3– transport and stability. Here we describe a study that used hydrogeology, chemistry, stable isotopes, and mass balance calculations to evaluate groundwater NO3– sources and transport in areas surrounding a highway construction site with documented blasting in New Hampshire. Results indicate various groundwater responses to contamination: (1) rapid breakthrough and flushing of synthetic NO3– (low δ15N, high δ18O) from dissolution of unexploded NH4NO3 blasting agents in oxic groundwater; (2) delayed and reduced breakthrough of synthetic NO3– subjected to partial denitrification (high δ15N, high δ18O); (3) relatively persistent concentrations of blasting-related biogenic NO3– derived from nitrification of NH4+ (low δ15N, low δ18O); and (4) stable but spatially variable biogenic NO3– concentrations, consistent with recharge from septic systems (high δ15N, low δ18O), variably affected by denitrification. Source characteristics of denitrified samples were reconstructed from dissolved-gas data (Ar, N2) and isotopic fractionation trends associated with denitrification (Δδ15N/Δδ18O ≈ 1.31). Methods and data from this study are expected to be applicable in studies of other aquifers affected by explosives used in construction.
","language":"English","publisher":"American Chemical Society","publisherLocation":"Easton, PA","doi":"10.1021/acs.est.5b03671","usgsCitation":"Degnan, J.R., Bohlke, J.K., Pelham, K., Langlais, D.M., and Walsh, G.J., 2016, Identification of groundwater nitrate contamination from explosives used in road construction: Isotopic, chemical, and hydrologic evidence: Environmental Science & Technology, v. 50, no. 2, p. 593-603, https://doi.org/10.1021/acs.est.5b03671.","productDescription":"11 p.","startPage":"593","endPage":"603","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067263","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":313910,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-28","publicationStatus":"PW","scienceBaseUri":"568e4912e4b0e7a44bc419dd","chorus":{"doi":"10.1021/acs.est.5b03671","url":"http://dx.doi.org/10.1021/acs.est.5b03671","publisher":"American Chemical Society (ACS)","authors":"Degnan James R., Böhlke J. 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The approach was applied at three sites spanning gradients in watershed size and land use in the Chesapeake Bay watershed. Results indicate that 58-73% of the annual nitrate load to the streams was groundwater-discharged nitrate. Average annual first order nitrate loss rate constants (k) were similar to those reported in both modelling and in-stream process-based studies, and were greater at the small streams (0.06 and 0.22 d-1) than at the large river (0.05 d-1), but 11% of the annual loads were retained/lost in the small streams, compared with 23% in the large river. Larger streambed area to water volume ratios in small streams result in greater loss rates, but shorter residence times in small streams result in a smaller fraction of nitrate loads being removed than in larger streams. A seasonal evaluation of k values suggests that nitrate was retained/lost at varying rates during the growing season. Consistent with previous studies, streamflow and nitrate concentration were inversely related to k. This new approach for interpreting high-frequency nitrate data and the associated findings furthers our ability to understand, predict, and mitigate nitrate impacts on streams and receiving waters by providing insights into temporal nitrate dynamics that would be difficult to obtain using traditional field-based studies.
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Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":588270,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pellerin, Brian A. bpeller@usgs.gov","contributorId":1451,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian","email":"bpeller@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":588271,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hyer, Kenneth E. kenhyer@usgs.gov","contributorId":152108,"corporation":false,"usgs":true,"family":"Hyer","given":"Kenneth E.","email":"kenhyer@usgs.gov","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":588272,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":588273,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70155254,"text":"70155254 - 2016 - The East African monsoon system: Seasonal climatologies and recent variations: Chapter 10","interactions":[],"lastModifiedDate":"2017-04-17T15:14:20","indexId":"70155254","displayToPublicDate":"2015-12-26T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"The East African monsoon system: Seasonal climatologies and recent variations: Chapter 10","docAbstract":"This chapter briefly reviews the complex climatological cycle of the East African monsoon system, paying special attention to its connection to the larger Indo-Pacific-Asian monsoon cycle. We examine the seasonal monsoon cycle, and briefly explore recent circulation changes. The spatial footprint of our analysis corresponds with the “Greater Horn of Africa” (GHA) region, extending from Tanzania in the south to Yemen and Sudan in the north. During boreal winter, when northeast trade winds flow across the northwest Indian Ocean and the equatorial moisture transports over the Indian Ocean exhibit strong westerly mean flows over the equatorial Indian Ocean, East African precipitation is limited to a few highland areas. As the Indian monsoon circulation transitions during boreal spring, the trade winds over the northwest Indian Ocean reverse, and East African moisture convergence supports the “long” rains. In boreal summer, the southwesterly Somali Jet intensifies over eastern Africa. Subsidence forms along the westward flank of this jet, shutting down precipitation over eastern portions of East Africa. In boreal fall, the Jet subsides, but easterly moisture transports support rainfall in limited regions of the eastern Horn of Africa. We use regressions with the trend mode of global sea surface temperatures to explore potential changes in the seasonal monsoon circulations. Significant reductions in total precipitable water are indicated in Kenya, Tanzania, Rwanda, Burundi, Uganda, Ethiopia, South Sudan, Sudan, and Yemen, with moisture transports broadly responding in ways that reinforce the climatological moisture transports over the Indian Ocean. Over Kenya, southern Ethiopia and Somalia, regressions with velocity potential indicate increased convergence aloft. Near the surface, this convergence appears to manifest as a surface high pressure system that modifies moisture transports in these countries as well as Uganda, Tanzania, Rwanda, and Burundi. An analysis of rainfall changes indicates significant declines in parts of Tanzania, Rwanda, Burundi, Uganda, Kenya, Somalia, Ethiopia, and Yemen.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The Monsoons and Climate Change","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"Cham","doi":"10.1007/978-3-319-21650-8_8","usgsCitation":"Funk, C.C., Hoell, A., Shukla, S., Husak, G.J., and Michaelsen, J., 2016, The East African monsoon system: Seasonal climatologies and recent variations: Chapter 10, chap. of The Monsoons and Climate Change, p. 163-185, https://doi.org/10.1007/978-3-319-21650-8_8.","productDescription":"13 p.","startPage":"163","endPage":"185","ipdsId":"IP-062072","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":339820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-21","publicationStatus":"PW","scienceBaseUri":"58f5d440e4b0f2e20545e415","contributors":{"authors":[{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565381,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoell, Andrew","contributorId":145803,"corporation":false,"usgs":false,"family":"Hoell","given":"Andrew","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shukla, Shraddhanand","contributorId":145802,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565383,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Husak, Gregory J.","contributorId":34435,"corporation":false,"usgs":true,"family":"Husak","given":"Gregory","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":565384,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Michaelsen, J.","contributorId":12288,"corporation":false,"usgs":true,"family":"Michaelsen","given":"J.","affiliations":[],"preferred":false,"id":565385,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70156787,"text":"70156787 - 2016 - Multi-scale predictions of massive conifer mortality due to chronic temperature rise","interactions":[],"lastModifiedDate":"2018-01-12T15:44:21","indexId":"70156787","displayToPublicDate":"2015-12-21T16:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale predictions of massive conifer mortality due to chronic temperature rise","docAbstract":"Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April–August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted ≥50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.
","language":"English","publisher":"Nature Publishing Group","publisherLocation":"London, UK","doi":"10.1038/nclimate2873","usgsCitation":"McDowell, N., Williams, A., Xu, C., Pockman, W., Dickman, L., Sevanto, S., Pangle, R., Limousin, J., Plaut, J., Mackay, D., Ogee, J., Domec, J., Allen, C.D., Fisher, R.A., Jiang, X., Muss, J., Breshears, D., Rauscher, S.A., and Koven, C., 2016, Multi-scale predictions of massive conifer mortality due to chronic temperature rise: Nature Climate Change, v. 6, p. 295-300, https://doi.org/10.1038/nclimate2873.","productDescription":"6 p.","startPage":"295","endPage":"300","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058464","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471401,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1492529","text":"External Repository"},{"id":312936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-21","publicationStatus":"PW","scienceBaseUri":"56826b46e4b0a04ef4925b86","contributors":{"authors":[{"text":"McDowell, Nathan G.","contributorId":9176,"corporation":false,"usgs":true,"family":"McDowell","given":"Nathan G.","affiliations":[],"preferred":false,"id":583294,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, A.P.","contributorId":70226,"corporation":false,"usgs":true,"family":"Williams","given":"A.P.","email":"","affiliations":[],"preferred":false,"id":583295,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xu, C.","contributorId":9781,"corporation":false,"usgs":true,"family":"Xu","given":"C.","email":"","affiliations":[],"preferred":false,"id":583296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pockman, W. T.","contributorId":57260,"corporation":false,"usgs":false,"family":"Pockman","given":"W. T.","affiliations":[{"id":7164,"text":"Department of Biology, University of New Mexico, Albuquerque, NM 87131 USA","active":true,"usgs":false}],"preferred":false,"id":583297,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dickman, L. T.","contributorId":150844,"corporation":false,"usgs":false,"family":"Dickman","given":"L. T.","affiliations":[],"preferred":false,"id":583298,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sevanto, Sanna","contributorId":150845,"corporation":false,"usgs":false,"family":"Sevanto","given":"Sanna","email":"","affiliations":[],"preferred":false,"id":583299,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pangle, R.","contributorId":150846,"corporation":false,"usgs":false,"family":"Pangle","given":"R.","email":"","affiliations":[],"preferred":false,"id":583300,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Limousin, J.","contributorId":150892,"corporation":false,"usgs":false,"family":"Limousin","given":"J.","affiliations":[],"preferred":false,"id":583491,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Plaut, J.J.","contributorId":6982,"corporation":false,"usgs":true,"family":"Plaut","given":"J.J.","email":"","affiliations":[],"preferred":false,"id":583302,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mackay, D.S.","contributorId":150893,"corporation":false,"usgs":false,"family":"Mackay","given":"D.S.","email":"","affiliations":[],"preferred":false,"id":583492,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ogee, J.","contributorId":150847,"corporation":false,"usgs":false,"family":"Ogee","given":"J.","affiliations":[],"preferred":false,"id":583301,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Domec, Jean-Christophe","contributorId":146460,"corporation":false,"usgs":false,"family":"Domec","given":"Jean-Christophe","email":"","affiliations":[],"preferred":false,"id":583305,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":570546,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Fisher, Rosie A.","contributorId":147090,"corporation":false,"usgs":false,"family":"Fisher","given":"Rosie","email":"","middleInitial":"A.","affiliations":[{"id":16785,"text":"National Center for Atmospheric Research, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":583306,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Jiang, X.","contributorId":150848,"corporation":false,"usgs":false,"family":"Jiang","given":"X.","email":"","affiliations":[],"preferred":false,"id":583307,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Muss, J.D.","contributorId":31954,"corporation":false,"usgs":true,"family":"Muss","given":"J.D.","affiliations":[],"preferred":false,"id":583308,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Breshears, D.D.","contributorId":17952,"corporation":false,"usgs":false,"family":"Breshears","given":"D.D.","email":"","affiliations":[{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false}],"preferred":false,"id":583309,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Rauscher, Sara A.","contributorId":47653,"corporation":false,"usgs":true,"family":"Rauscher","given":"Sara","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":583310,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Koven, C.","contributorId":39655,"corporation":false,"usgs":true,"family":"Koven","given":"C.","email":"","affiliations":[],"preferred":false,"id":583311,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70160330,"text":"70160330 - 2016 - Structure and spatial patterns of macrobenthic community in Tai Lake, a large shallow lake, China","interactions":[],"lastModifiedDate":"2015-12-17T14:23:38","indexId":"70160330","displayToPublicDate":"2015-12-17T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Structure and spatial patterns of macrobenthic community in Tai Lake, a large shallow lake, China","docAbstract":"Tai Lake (Chinese: Taihu), the third-largest freshwater lake in China, suffers from harmful cyanobacteria blooms that are caused by economic development and population growth near the lake. Several studies have focused on phytoplankton in Tai Lake after a drinking water crisis in 2007; however, these studies primarily focused on microcystin bioaccumulation and toxicity to individual species without examining the effects of microcystin on macrobenthic community diversity. In this study, we conducted a survey of the lake to examine the effects of microcystine and other pollutants on marcobenthic community diversity. A totally of forty-nine species of macroinvertebrates were found in Tai Lake. Limnodrilus hoffmeisteri and Corbicula fluminea were the most abundant species. Cluster-analysis and one-way analysis of similarity (ANOSIM) identified three significantly different macrobenthic communities among the sample sites. More specifically, sites in the eastern bays, where aquatic macrophytes were abundant, had the highest diversity of macrobenthic communities, which were dominated by Bellamya aeruginosa, Bellamya purificata, L. hoffmeisteri, and Alocinma longicornis. Sites in Zhushan Bay contained relatively diverse communities, mainly composed of L. hoffmeisteri, C. fluminea, L. claparederanus, R. sinicus, and Cythura sp. Sites in the western region, Meiliang Bay and Wuli Bay had the lowest diversity, mainly composed ofL. hoffmeisteri, C. fluminea, Branchiura sowerbyi, and Rhyacodrilus sinicus. In addition, the relationships between macrobenthic metrics (Shannon–Wiener, Margalef, and Pielou) and environmental variables showed that community structure and spatial patterns of macrobenthos in Tai Lake were significantly influenced by chemical oxygen demand (CODCr), biochemical oxygen demand (BOD5), lead (Pb), and microcystin-LR (L for leucine and R for arginine). Our findings provide critical information that could help managers and policymakers assess and modify ecological restoration practices.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2015.08.043","usgsCitation":"Li, D., Erickson, R.A., Song Tang, Li, X., Niu, Z., Wang, X., Liu, H., and Yu, H., 2016, Structure and spatial patterns of macrobenthic community in Tai Lake, a large shallow lake, China: Ecological Indicators, v. 61, no. 2, p. 170-187, https://doi.org/10.1016/j.ecolind.2015.08.043.","productDescription":"18 p.","startPage":"170","endPage":"187","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062777","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":312468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Tai Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 119.89105224609375,\n 30.935212690426727\n ],\n [\n 119.89105224609375,\n 31.54460103811182\n ],\n [\n 120.59280395507812,\n 31.54460103811182\n ],\n [\n 120.59280395507812,\n 30.935212690426727\n ],\n [\n 119.89105224609375,\n 30.935212690426727\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"61","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5673dcb4e4b0da412f4f8201","contributors":{"authors":[{"text":"Li, Di","contributorId":150650,"corporation":false,"usgs":false,"family":"Li","given":"Di","email":"","affiliations":[{"id":18059,"text":"State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":582573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":582572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Song Tang","contributorId":150651,"corporation":false,"usgs":false,"family":"Song Tang","affiliations":[{"id":18060,"text":"School of Environment and Sustainability, University of Saskatchewan, Canada","active":true,"usgs":false}],"preferred":false,"id":582574,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, Xuwen","contributorId":150652,"corporation":false,"usgs":false,"family":"Li","given":"Xuwen","email":"","affiliations":[{"id":18061,"text":"Jiangsu Environmental Monitoring Center, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":582575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Niu, Zhichun","contributorId":150653,"corporation":false,"usgs":false,"family":"Niu","given":"Zhichun","email":"","affiliations":[{"id":18061,"text":"Jiangsu Environmental Monitoring Center, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":582576,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Xia","contributorId":150654,"corporation":false,"usgs":false,"family":"Wang","given":"Xia","email":"","affiliations":[{"id":18061,"text":"Jiangsu Environmental Monitoring Center, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":582577,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liu, Hongling","contributorId":150655,"corporation":false,"usgs":false,"family":"Liu","given":"Hongling","email":"","affiliations":[{"id":18059,"text":"State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":582578,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yu, Hongxia","contributorId":150656,"corporation":false,"usgs":false,"family":"Yu","given":"Hongxia","email":"","affiliations":[{"id":18059,"text":"State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":582579,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70159869,"text":"ofr20151230 - 2016 - Water use in Georgia by county for 2010 and water-use trends, 1985–2010","interactions":[],"lastModifiedDate":"2016-12-08T17:04:41","indexId":"ofr20151230","displayToPublicDate":"2015-12-16T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1230","title":"Water use in Georgia by county for 2010 and water-use trends, 1985–2010","docAbstract":"Water use and water withdrawals and returns in 2010 are estimated for each major river basin, principal aquifer, water-planning region, and county in Georgia using data obtained from various Federal and State agencies and local sources. Offstream water use in 2010 is estimated for the categories of public supply, domestic, commercial, industrial, mining, irrigation, livestock, aquaculture, and thermoelectric power. Water-use trends for 1985 to 2010 are also shown.
\nThe period between 2007 and 2010 was a challenging time economically and climatologically in Georgia. During that period, the United States was in the midst of a major recession, resulting in decreases in the manufacturing and construction industries and large increases in unemployment. During 2007, 2008, and the latter half of 2010, precipitation in Georgia was substantially below the 30-year norm.
\nAccording to the 2010 Census of Population and Housing, nearly 9.7 million people lived in Georgia. The water for about 85 percent of that population was provided by public water suppliers. Estimated total water withdrawals from ground-water and surface-water sources were about 4,670 million gallons per day (Mgal/d) in 2010, about a 15-percent reduction from 2005 (5,471 Mgal/d). In 2010, thermoelectric-power facilities (2,046 Mgal/d) and public-supply uses (1,121 Mgal/d) accounted for 68 percent of all water withdrawn in Georgia. Surface-water withdrawals were greatest for thermoelectric-power generation (2,043 Mgal/d), whereas irrigation used the largest amount of groundwater (599 Mgal/d). Surface water provided 78 percent of the 1,121 Mgal/day withdrawn for public supply in 2010. Typically, counties in northern Georgia withdraw a larger percentage of water from surface water than groundwater sources; whereas, counties in the southern part of the State withdraw more water from groundwater sources.
\nHistorically, water withdrawals in Georgia were highest in 1980 (6,725 Mgal/d). By 1990, water use had decreased by 20 percent to 5,353 Mgal/d, but increased to 6,487 Mgal/d in 2000. By 2005, water use had decreased to an estimated 5,471 Mgal/d, and declined further to 4,670 Mgal/d in 2010—a 30-percent decrease since 1980. This decline was evident across all water-use categories, but was greatest for surface-water withdrawals by thermoelectric-power facilities. The estimated total water use per capita in 1985 (total withdrawals for all categories divided by total population) was about 850 gallons per day (gal/d), steadily decreasing to about 798 gal/d in 2000, and decreasing further to 460 gal/d in 2010. Although water use declined among all use categories during that 10-year period, most of the decline in per capita water use was caused by the large decrease in water used for thermoelectric-power generation.
\nThroughout 1985–2010 water withdrawn for thermoelectric-power generation has constituted the largest volume of offstream water use in Georgia. Total withdrawals for thermoelectric-power generation declined about 37 percent between 2000 and 2010, mostly due to the decommissioning of power plants in the State. Also during this period, several power plants were shut down and re-tooled to use natural gas-powered generators; thus, water withdrawals for cooling were substantially reduced.
\nThe decline in water withdrawals and use between 2005 and 2010 can probably be attributed to several factors working together during this period: (1) water conservation laws and policies along with advances in water-conservation technology; (2) the onset of a major recession in 2007; and (3) below average rainfall in 2007, 2008, and the latter half of 2010. Because of these factors, water withdrawn by public suppliers decreased by 4.8 percent (despite a nearly 11-percent increase in population served) and per capita use decreased by 19 percent between 2005 and 2010.
\nAbout 2,225 Mgal/d of water was returned to Georgia streams and lakes in 2010 under the National Pollutant Discharge Elimination System program administered by the Georgia Environmental Protection Division. This amount is about 48 percent of the total water withdrawn from all sources in 2010. Water returns declined 39 percent between 1995 and 2010, mirroring the decline in water withdrawals during that period. In addition, land applications of treated wastewater increased steadily between 1995 and 2010.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151230","collaboration":"Prepared in cooperation with the Georgia Department of Natural Resources, Environmental Protection Division","usgsCitation":"Lawrence, S.J., 2016, Water use in Georgia by county for 2010 and water-use trends, 1985–2010 (ver. 1.1, January 2016): U.S. Geological Survey Open-File Report 2015–1230, 206 p., https://dx.doi.org/10.3133/ofr20151230.","productDescription":"viii, 206 p.","numberOfPages":"218","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2010-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-037442","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":312330,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1230/ofr20151230.pdf","text":"Report","size":"19.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1230"},{"id":312329,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1230/coverthbn.jpg"},{"id":314402,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2015/1230/verHist.txt","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2015-1230"}],"country":"United States","state":"Georgia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.594482421875,\n 34.994003757575776\n ],\n [\n -84.990234375,\n 32.222095840502334\n ],\n [\n -85.166015625,\n 31.83089906339438\n ],\n [\n -85.05615234375,\n 31.541089879585808\n ],\n [\n -85.1220703125,\n 31.21280145833882\n ],\n [\n -84.91333007812499,\n 30.72294882477251\n ],\n [\n -82.24365234375,\n 30.5717205651999\n ],\n [\n -82.188720703125,\n 30.363396239603716\n ],\n [\n -82.0458984375,\n 30.334953881988564\n ],\n [\n -82.034912109375,\n 30.732392734006083\n ],\n [\n -81.89208984375,\n 30.86451022625836\n ],\n [\n -81.45263671875,\n 30.62845887475364\n ],\n [\n -81.10107421874999,\n 31.690781806136822\n ],\n [\n -80.9033203125,\n 31.942839972853083\n ],\n [\n -81.27685546875,\n 32.55607364492029\n ],\n [\n -81.5625,\n 33.08233672856376\n ],\n [\n -81.9580078125,\n 33.46810795527896\n ],\n [\n -82.518310546875,\n 33.93424531117312\n ],\n [\n -82.880859375,\n 34.4793919710481\n ],\n [\n -83.045654296875,\n 34.470335121217495\n ],\n [\n -83.375244140625,\n 34.732584206123626\n ],\n [\n -83.08959960937499,\n 35.0120020431607\n ],\n [\n -85.594482421875,\n 34.994003757575776\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted December 16, 2015; Version 1.1: January 15, 2016","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/