{"pageNumber":"1151","pageRowStart":"28750","pageSize":"25","recordCount":184935,"records":[{"id":70168924,"text":"70168924 - 2016 - Evaluation of downscaled, gridded climate data for the conterminous United States","interactions":[],"lastModifiedDate":"2017-08-29T09:40:39","indexId":"70168924","displayToPublicDate":"2016-02-24T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of downscaled, gridded climate data for the conterminous United States","docAbstract":"

Weather and climate affect many ecological processes, making spatially continuous yet fine-resolution weather data desirable for ecological research and predictions. Numerous downscaled weather data sets exist, but little attempt has been made to evaluate them systematically. Here we address this shortcoming by focusing on four major questions: (1) How accurate are downscaled, gridded climate data sets in terms of temperature and precipitation estimates?, (2) Are there significant regional differences in accuracy among data sets?, (3) How accurate are their mean values compared with extremes?, and (4) Does their accuracy depend on spatial resolution? We compared eight widely used downscaled data sets that provide gridded daily weather data for recent decades across the United States. We found considerable differences among data sets and between downscaled and weather station data. Temperature is represented more accurately than precipitation, and climate averages are more accurate than weather extremes. The data set exhibiting the best agreement with station data varies among ecoregions. Surprisingly, the accuracy of the data sets does not depend on spatial resolution. Although some inherent differences among data sets and weather station data are to be expected, our findings highlight how much different interpolation methods affect downscaled weather data, even for local comparisons with nearby weather stations located inside a grid cell. More broadly, our results highlight the need for careful consideration among different available data sets in terms of which variables they describe best, where they perform best, and their resolution, when selecting a downscaled weather data set for a given ecological application.

","language":"English","publisher":"Ecological Society of America","publisherLocation":"Tempe, AZ","doi":"10.1002/15-1061","usgsCitation":"Behnke, R.J., Stephen J. Vavrus, Allstadt, A., Albright, T.P., Thogmartin, W.E., and Radeloff, V.C., 2016, Evaluation of downscaled, gridded climate data for the conterminous United States: Ecological Applications, v. 26, no. 5, p. 1338-1351, https://doi.org/10.1002/15-1061.","productDescription":"14 p.","startPage":"1338","endPage":"1351","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066648","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":471211,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/15-1061","text":"Publisher Index Page"},{"id":318680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Vavrus","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":622127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allstadt, Andrew","contributorId":167392,"corporation":false,"usgs":false,"family":"Allstadt","given":"Andrew","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":622128,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Albright, Thomas P.","contributorId":167393,"corporation":false,"usgs":false,"family":"Albright","given":"Thomas","email":"","middleInitial":"P.","affiliations":[{"id":24706,"text":"University of Nevada-Reno","active":true,"usgs":false}],"preferred":false,"id":622129,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":622125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Radeloff, Volker C.","contributorId":149494,"corporation":false,"usgs":false,"family":"Radeloff","given":"Volker","email":"","middleInitial":"C.","affiliations":[{"id":13679,"text":"SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":622130,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70168825,"text":"70168825 - 2016 - Reconnecting fragmented sturgeon populations in North American rivers","interactions":[],"lastModifiedDate":"2018-02-28T14:35:05","indexId":"70168825","displayToPublicDate":"2016-02-24T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Reconnecting fragmented sturgeon populations in North American rivers","docAbstract":"

The majority of large North American rivers are fragmented by dams that interrupt migrations of wide-ranging fishes like sturgeons. Reconnecting habitat is viewed as an important means of protecting sturgeon species in U.S. rivers because these species have lost between 5% and 60% of their historical ranges. Unfortunately, facilities designed to pass other fishes have rarely worked well for sturgeons. The most successful passage facilities were sized appropriately for sturgeons and accommodated bottom-oriented species. For upstream passage, facilities with large entrances, full-depth guidance systems, large lifts, or wide fishways without obstructions or tight turns worked well. However, facilitating upstream migration is only half the battle. Broader recovery for linked sturgeon populations requires safe “round-trip” passage involving multiple dams. The most successful downstream passage facilities included nature-like fishways, large canal bypasses, and bottom-draw sluice gates. We outline an adaptive approach to implementing passage that begins with temporary programs and structures and monitors success both at the scale of individual fish at individual dams and the scale of metapopulations in a river basin. The challenge will be to learn from past efforts and reconnect North American sturgeon populations in a way that promotes range expansion and facilitates population recovery.

","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/03632415.2015.1132705","usgsCitation":"Jager, H., Parsley, M.J., Cech, J.J., McLaughlin, R.L., Forsythe, P.S., and Elliott, R.S., 2016, Reconnecting fragmented sturgeon populations in North American rivers: Fisheries, v. 41, no. 3, p. 140-148, https://doi.org/10.1080/03632415.2015.1132705.","productDescription":"9 p.","startPage":"140","endPage":"148","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056808","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":490009,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1240513","text":"External Repository"},{"id":318553,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United 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L.","contributorId":75736,"corporation":false,"usgs":false,"family":"McLaughlin","given":"R.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":621859,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Forsythe, Patrick S.","contributorId":167341,"corporation":false,"usgs":false,"family":"Forsythe","given":"Patrick","email":"","middleInitial":"S.","affiliations":[{"id":24696,"text":"Green Bay Fish and Wildlife Conservation Office, USGS, New Franken, Wisconsin","active":true,"usgs":false}],"preferred":false,"id":621860,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elliott, Robert S.","contributorId":167342,"corporation":false,"usgs":false,"family":"Elliott","given":"Robert","email":"","middleInitial":"S.","affiliations":[{"id":24697,"text":"Department of Natural and Applied Sciences, University of Wisconsin - Green Bay, Green Bay, WI","active":true,"usgs":false}],"preferred":false,"id":621861,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70171334,"text":"70171334 - 2016 - Genetic diversity of Wolbachia endosymbionts in Culex quinquefasciatus from Hawai`i, Midway Atoll, and Samoa","interactions":[],"lastModifiedDate":"2018-01-04T12:43:21","indexId":"70171334","displayToPublicDate":"2016-02-24T07:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":414,"text":"Technical Report","active":false,"publicationSubtype":{"id":9}},"seriesNumber":"HCSU-074","title":"Genetic diversity of Wolbachia endosymbionts in Culex quinquefasciatus from Hawai`i, Midway Atoll, and Samoa","docAbstract":"

Incompatible insect techniques are potential methods for controlling Culex quinquefasciatus and avian disease transmission in Hawai‘i without the use of pesticides or genetically modified organisms. The approach is based on naturally occurring sperm-egg incompatibilities within the Culex pipiens complex that are controlled by different strains of the bacterial endosymbiont Wolbachia pipientis (wPip). Incompatibilities can be unidirectional (crosses between males infected with strain A and females infected with strain B are fertile, while reciprocal crosses are not) or bidirectional (reciprocal crosses between sexes with different wPip strains are infertile). The technique depends on release of sufficient numbers of male mosquitoes infected with an incompatible wPip strain to suppress mosquito populations and reduce transmission of introduced avian malaria (Plasmodium relictum) and Avipoxvirus in native forest bird habitats. Both diseases are difficult to manage using more traditional methods based on removal and treatment of larval habitats and coordination of multiple approaches may be needed to control this vector. We characterized the diversity of Wolbachia strains in C. quinquefasciatus from Hawai‘i, Kaua‘i, Midway Atoll, and American Samoa with a variety of genetic markers to identify compatibility groups and their distribution within and between islands. We confirmed the presence of wPip with multilocus sequence typing, tested for local genetic variability using 16 WO prophage genes, and identified similarities to strains from other parts of the world with a transposable element (tr1). We also tested for genetic differences in ankyrin motifs (ank2 and pk1) which have been used to classify wPip strains into five worldwide groups (wPip1–wPip5) that vary in compatibility with each other based on experimental crosses. We found a mixture of both widely distributed and site specific genotypes based on presence or absence of WO prophage and transposable element markers on Hawai‘i Island (Volcano, Pu‘u Wa‘awa‘a, Laupāhoehoe, Kaumana, Kahuku, Nīnole, and Maulua Gulch), Kaua‘i Island (Kawaikōī, Mōhihi, Kalāheo, Lāwa‘i and Hanapepe) and Midway Atoll. Genotypes from American Samoa were unique and formed their own clade. Based on analysis of ankyrin motifs, wPip strains from Hawai‘i, Kaua‘i, and Midway Atoll were most similar to wPip5 strains of Australasian origin. By contrast, Wolbachia strains from Culex quinquefasciatus collected in American Samoa were most similar to wPip3 strains of American origin. We detected a single Culex mosquito from Pu‘u Wa‘awa‘a on Hawai‘i Island that was infected with a unique wPip3 genotype. This discovery, plus a rarefaction analysis of genotypes from Kaua‘i and Hawai‘i Islands suggests that limited sampling may have underestimated diversity of wPip in our study. Mosquitoes infected with wPip5 and wPip3 are bidirectionally compatible with each other based on prior studies, which would support their ability to coexist within the same population on Hawai‘i Island. Available evidence from prior studies suggests that genotype wPip4 from Africa, the Middle East, Europe, and Asia is bidirectionally incompatible with genotype wPip5 and varies in compatibility with genotype wPip3 depending on geographic origin. Since wPip5 appears to be the most common compatibility group in Hawai‘i based on limited sampling, logical next steps are to 1) expand the current survey to include additional islands and localities, 2) infect a laboratory colony of Hawaiian Culex with wPip4 through tetracycline treatment of Hawaiian mosquitoes and backcross with Culex from Europe, North Africa, and the Middle East that are naturally infected with wPip4, 3) conduct cage trials to confirm bidirectional incompatibilities between Hawaiian Culex infected with wPip4 and wPip5, and 4) conduct field trials to evaluate whether release of incompatible males can be applied at small scales to suppress local populations.

","language":"English","publisher":"University of Hawaii at Hilo","publisherLocation":"Hilo, Hi","collaboration":"This product was prepared under Cooperative Agreement G15AC00191 for the Pacific Island Ecosystems Research Center of the U.S. Geological Survey.","usgsCitation":"Atkinson, C.T., Watcher-Weatherwax, W., and Lapointe, D., 2016, Genetic diversity of Wolbachia endosymbionts in Culex quinquefasciatus from Hawai`i, Midway Atoll, and Samoa: Technical Report HCSU-074, Report: iv, 33 p.","productDescription":"Report: iv, 33 p.","startPage":"1","endPage":"33","numberOfPages":"37","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073512","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328011,"type":{"id":15,"text":"Index 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Unit","active":true,"usgs":false}],"preferred":false,"id":630610,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaPointe, Dennis A. 0000-0002-6323-263X dlapointe@usgs.gov","orcid":"https://orcid.org/0000-0002-6323-263X","contributorId":150365,"corporation":false,"usgs":true,"family":"LaPointe","given":"Dennis","email":"dlapointe@usgs.gov","middleInitial":"A.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":630611,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175344,"text":"70175344 - 2016 - Are brown trout replacing or displacing bull trout populations in a changing climate?","interactions":[],"lastModifiedDate":"2016-09-06T13:36:12","indexId":"70175344","displayToPublicDate":"2016-02-23T17:15:00","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":"Are brown trout replacing or displacing bull trout populations in a changing climate?","docAbstract":"

Understanding how climate change may facilitate species turnover is an important step in identifying potential conservation strategies. We used data from 33 sites in western Montana to quantify climate associations with native bull trout (Salvelinus confluentus) and non-native brown trout (Salmo trutta) abundance and population growth rates (λ). We estimated λ using exponential growth state space models and delineated study sites based on bull trout use for either Spawning and Rearing (SR) or Foraging, Migrating, and Overwintering (FMO) habitat. Bull trout abundance was negatively associated with mean August stream temperatures within SR habitat (r = -0.75). Brown trout abundance was generally highest at temperatures between 12 and 14°C. We found bull trout λ were generally stable at sites with mean August temperature below 10°C but significantly decreasing, rare, or extirpated at 58% of the sites with temperatures exceeding 10°C. Brown trout λ were highest in SR and sites with temperatures exceeding 12°C. Declining bull trout λs at sites where brown trout were absent suggests brown trout are likely replacing bull trout in a warming climate.

","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2015-0293","usgsCitation":"Al-Chokhachy, R.K., Schmetterling, D.A., Clancy, C., Saffel, P., Kovach, R., Nyce, L., Liermann, B., Fredenberg, W.A., and Pierce, R., 2016, Are brown trout replacing or displacing bull trout populations in a changing climate?: Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 9, p. 1395-1404, https://doi.org/10.1139/cjfas-2015-0293.","productDescription":"10 p.","startPage":"1395","endPage":"1404","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070449","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":326148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.1474609375,\n 47.60616304386874\n ],\n [\n -109.2919921875,\n 47.45780853075031\n ],\n [\n -109.599609375,\n 45.521743896993634\n ],\n [\n -116.19140625,\n 45.30580259943578\n ],\n [\n -116.23535156249999,\n 47.30903424774781\n ],\n [\n -116.1474609375,\n 47.60616304386874\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"73","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a5b8b4e4b0ebae89b7884e","contributors":{"authors":[{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmetterling, David A.","contributorId":20223,"corporation":false,"usgs":true,"family":"Schmetterling","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":644796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clancy, Chris","contributorId":173465,"corporation":false,"usgs":false,"family":"Clancy","given":"Chris","email":"","affiliations":[{"id":6581,"text":"Montana Fish, Wildlife and Parks, Kalispell, Montana 59901, USA","active":true,"usgs":false}],"preferred":false,"id":644797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saffel, Pat","contributorId":173466,"corporation":false,"usgs":false,"family":"Saffel","given":"Pat","email":"","affiliations":[{"id":6581,"text":"Montana Fish, Wildlife and Parks, Kalispell, Montana 59901, USA","active":true,"usgs":false}],"preferred":false,"id":644798,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kovach, Ryan 0000-0001-5402-2123 rkovach@usgs.gov","orcid":"https://orcid.org/0000-0001-5402-2123","contributorId":145914,"corporation":false,"usgs":true,"family":"Kovach","given":"Ryan","email":"rkovach@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644799,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nyce, Leslie","contributorId":173467,"corporation":false,"usgs":false,"family":"Nyce","given":"Leslie","email":"","affiliations":[{"id":6581,"text":"Montana Fish, Wildlife and Parks, Kalispell, Montana 59901, USA","active":true,"usgs":false}],"preferred":false,"id":644800,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liermann, Brad","contributorId":173468,"corporation":false,"usgs":false,"family":"Liermann","given":"Brad","email":"","affiliations":[{"id":6581,"text":"Montana Fish, Wildlife and Parks, Kalispell, Montana 59901, USA","active":true,"usgs":false}],"preferred":false,"id":644801,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fredenberg, Wade A.","contributorId":78860,"corporation":false,"usgs":true,"family":"Fredenberg","given":"Wade","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":644802,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pierce, Ron","contributorId":171578,"corporation":false,"usgs":false,"family":"Pierce","given":"Ron","email":"","affiliations":[{"id":6581,"text":"Montana Fish, Wildlife and Parks, Kalispell, Montana 59901, USA","active":true,"usgs":false}],"preferred":false,"id":644803,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70168543,"text":"ofr20161021 - 2016 - Ecoregions of California","interactions":[],"lastModifiedDate":"2025-05-14T18:41:14.173917","indexId":"ofr20161021","displayToPublicDate":"2016-02-23T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1021","title":"Ecoregions of California","docAbstract":"

Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. By recognizing the spatial differences in the capacities and potentials of ecosystems, ecoregions stratify the environment by its probable response to disturbance (Bryce and others, 1999). These general purpose regions are critical for structuring and implementing ecosystem management strategies across Federal agencies, State agencies, and nongovernment organizations that are responsible for different types of resources in the same geographical areas (Omernik and others, 2000).

The approach used to compile this map is based on the premise that ecological regions are hierarchical and can be identified through the analysis of the spatial patterns and the composition of biotic and abiotic phenomena that affect or reflect differences in ecosystem quality and integrity (Wiken, 1986; Omernik, 1987, 1995). These phenomena include geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another regardless of the hierarchical level. A Roman numeral hierarchical scheme has been adopted for different levels of ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997, map revised 2006). At level III, the continental United States contains 105 ecoregions and the conterminous United States has 85 ecoregions (U.S. Environmental Protection Agency, 2013). Level IV, depicted here for California, is a further refinement of level III ecoregions. Explanations of the methods used to define these ecoregions are given in Omernik (1995), Omernik and others (2000), and Omernik and Griffith (2014).

California has great ecological and biological diversity. The State contains offshore islands and coastal lowlands, large alluvial valleys, forested mountain ranges, deserts, and various aquatic habitats. There are 13 level III ecoregions and 177 level IV ecoregions in California and most continue into ecologically similar parts of adjacent States of the United States or Mexico (Bryce and others, 2003; Thorson and others, 2003; Griffith and others, 2014).

The California ecoregion map was compiled at a scale of 1:250,000. It revises and subdivides an earlier national ecoregion map that was originally compiled at a smaller scale (Omernik, 1987; U.S. Environmental Protection Agency, 2013). This poster is the result of a collaborative project primarily between U.S. Environmental Protection Agency (USEPA) Region IX, USEPA National Health and Environmental Effects Research Laboratory (Corvallis, Oregon), California Department of Fish and Wildlife (DFW), U.S. Department of Agriculture (USDA)–Natural Resources Conservation Service (NRCS), U.S. Department of the Interior–Geological Survey (USGS), and other State of California agencies and universities.

The project is associated with interagency efforts to develop a common framework of ecological regions (McMahon and others, 2001). Reaching that objective requires recognition of the differences in the conceptual approaches and mapping methodologies applied to develop the most common ecoregion-type frameworks, including those developed by the USDA–Forest Service (Bailey and others, 1994; Miles and Goudy, 1997; Cleland and others, 2007), the USEPA (Omernik 1987, 1995), and the NRCS (U.S. Department of Agriculture–Soil Conservation Service, 1981; U.S. Department of Agriculture–Natural Resources Conservation Service, 2006). As each of these frameworks is further refined, their differences are becoming less discernible. Regional collaborative projects such as this one in California, where some agreement has been reached among multiple resource-management agencies, are a step toward attaining consensus and consistency in ecoregion frameworks for the entire nation.

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\"}}]}","contact":"

Western Geographic Science Center
U.S. Geological Survey
345 Middlefield Road, MS 531
Menlo Park, CA 94025
http://geography.wr.usgs.gov/

","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2016-02-23","noUsgsAuthors":false,"publicationDate":"2016-02-23","publicationStatus":"PW","scienceBaseUri":"56cd82afe4b0b1892d9e4e8c","contributors":{"authors":[{"text":"Griffith, Glenn E. 0000-0001-7966-4720 ggriffith@usgs.gov","orcid":"https://orcid.org/0000-0001-7966-4720","contributorId":4053,"corporation":false,"usgs":true,"family":"Griffith","given":"Glenn","email":"ggriffith@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":620826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Omernik, James M.","contributorId":50081,"corporation":false,"usgs":true,"family":"Omernik","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":620827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, David W. 0000-0002-9543-800X dwsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-9543-800X","contributorId":1681,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"dwsmith@usgs.gov","middleInitial":"W.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Terry D.","contributorId":167040,"corporation":false,"usgs":false,"family":"Cook","given":"Terry D.","affiliations":[{"id":24598,"text":"USDA-NRCS retired","active":true,"usgs":false}],"preferred":false,"id":620829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tallyn, Ed","contributorId":167041,"corporation":false,"usgs":false,"family":"Tallyn","given":"Ed","email":"","affiliations":[{"id":24598,"text":"USDA-NRCS retired","active":true,"usgs":false}],"preferred":false,"id":620830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moseley, Kendra","contributorId":167042,"corporation":false,"usgs":false,"family":"Moseley","given":"Kendra","email":"","affiliations":[{"id":24598,"text":"USDA-NRCS retired","active":true,"usgs":false}],"preferred":false,"id":620831,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Colleen B.","contributorId":167043,"corporation":false,"usgs":false,"family":"Johnson","given":"Colleen B.","affiliations":[{"id":24599,"text":"Raytheon/SRA","active":true,"usgs":false}],"preferred":false,"id":620832,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70170007,"text":"70170007 - 2016 - Reproductive allochrony in seasonally sympatric populations maintained by differential response to photoperiod: Implications for population divergence and response to climate change","interactions":[],"lastModifiedDate":"2016-04-01T12:48:30","indexId":"70170007","displayToPublicDate":"2016-02-23T13:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":740,"text":"American Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Reproductive allochrony in seasonally sympatric populations maintained by differential response to photoperiod: Implications for population divergence and response to climate change","docAbstract":"

Reproductive allochrony presents a potential barrier to gene flow and is common in seasonally sympatric migratory and sedentary birds. Mechanisms mediating reproductive allochrony can influence population divergence and the capacity of populations to respond to environmental change. We asked whether reproductive allochrony in seasonally sympatric birds results from a difference in response to supplementary or photoperiodic cues and whether the response varies in relation to the distance separating breeding and wintering locations as measured by stable isotopes. We held seasonally sympatric migratory and sedentary male dark-eyed juncos (Junco hyemalis) in a common garden in early spring under simulated natural changes in photoperiod and made measurements of reproductive and migratory physiology. On the same dates and photoperiods, sedentary juncos had higher testosterone (initial and gonadotropin-releasing hormone induced), more developed cloacal protuberances, and larger testes than migrants. In contrast, migratory juncos had larger fat reserves (fuel for migration). We found a negative relationship between testis mass and feather hydrogen isotope ratios, indicating that testis growth was more delayed in migrants making longer migrations. We conclude that reproductive allochrony in seasonally sympatric migratory and sedentary birds can result from a differential response to photoperiodic cues in a common garden, and as a result, gene flow between migrants and residents may be reduced by photoperiodic control of reproductive development. Further, earlier breeding in response to future climate change may currently be constrained by differential response to photoperiodic cues.

","language":"English","publisher":"American Society of Naturalists","publisherLocation":"Salem, MS","doi":"10.1086/685296","collaboration":"Indiana University; North Dakota State University","usgsCitation":"Fudickar, A., Grieves, T., Atwell, J.W., Stricker, C.A., and Ketterson, E.D., 2016, Reproductive allochrony in seasonally sympatric populations maintained by differential response to photoperiod: Implications for population divergence and response to climate change: American Naturalist, v. 187, no. 4, p. 436-446, https://doi.org/10.1086/685296.","productDescription":"11 p.","startPage":"436","endPage":"446","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066641","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":319730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"187","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56ff9c20e4b0328dcb7eab29","contributors":{"authors":[{"text":"Fudickar, A.M.","contributorId":168419,"corporation":false,"usgs":false,"family":"Fudickar","given":"A.M.","affiliations":[{"id":12645,"text":"Indiana University - Northwest","active":true,"usgs":false}],"preferred":false,"id":625863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grieves, T.J.","contributorId":168420,"corporation":false,"usgs":false,"family":"Grieves","given":"T.J.","email":"","affiliations":[{"id":12471,"text":"North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":625864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atwell, Jonathan W.","contributorId":168421,"corporation":false,"usgs":false,"family":"Atwell","given":"Jonathan","email":"","middleInitial":"W.","affiliations":[{"id":12645,"text":"Indiana University - Northwest","active":true,"usgs":false}],"preferred":false,"id":625865,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":625862,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ketterson, Ellen D.","contributorId":168422,"corporation":false,"usgs":false,"family":"Ketterson","given":"Ellen","email":"","middleInitial":"D.","affiliations":[{"id":12645,"text":"Indiana University - Northwest","active":true,"usgs":false}],"preferred":false,"id":625866,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70161955,"text":"sir20155163 - 2016 - Groundwater ages from the freshwater zone of the Edwards aquifer, Uvalde County, Texas—Insights into groundwater flow and recharge","interactions":[],"lastModifiedDate":"2016-02-24T09:17:23","indexId":"sir20155163","displayToPublicDate":"2016-02-23T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5163","title":"Groundwater ages from the freshwater zone of the Edwards aquifer, Uvalde County, Texas—Insights into groundwater flow and recharge","docAbstract":"

Tritium–helium-3 groundwater ages of the Edwards aquifer in south-central Texas were determined as part of a long-term study of groundwater flow and recharge in the Edwards and Trinity aquifers. These ages help to define groundwater residence times and to provide constraints for calibration of groundwater flow models. A suite of 17 samples from public and private supply wells within Uvalde County were collected for active and noble gases, and for tritium–helium-3 analyses from the confined and unconfined parts of the Edwards aquifer. Samples were collected from monitoring wells at discrete depths in open boreholes as well as from integrated pumped well-head samples. The data indicate a fairly uniform groundwater flow system within an otherwise structurally complex geologic environment comprised of regionally and locally faulted rock units, igneous intrusions, and karst features within carbonate rocks. Apparent ages show moderate, downward average, linear velocities in the Uvalde area with increasing age to the east along a regional groundwater flow path. Though the apparent age data show a fairly consistent distribution across the study area, many apparent ages indicate mixing of both modern (less than 60 years) and premodern (greater than 60 years) waters. This mixing is most evident along the “bad water” line, an arbitrary delineation of 1,000 milligrams per liter dissolved solids that separates the freshwater zone of the Edwards aquifer from the downdip saline water zone. Mixing of modern and premodern waters also is indicated within the unconfined zone of the aquifer by high excess helium concentrations in young waters. Excess helium anomalies in the unconfined aquifer are consistent with possible subsurface discharge of premodern groundwater from the underlying Trinity aquifer into the younger groundwater of the Edwards aquifer.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155163","usgsCitation":"Hunt, A.G., Landis, G.P., and Faith, J.R., 2016, Groundwater ages from the freshwater zone of the Edwards Aquifer, Uvalde County, Texas—Insights into groundwater flow and recharge: U.S. Geological Survey Scientific Investigations Report 2015–5163, 28 p., https://dx.doi.org/10.3133/sir20155163.","productDescription":"viii, 28 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065915","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":318180,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5163/coverthb.jpg"},{"id":318181,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5163/sir20155163.pdf","text":"Report","size":"3.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5163"}],"country":"United States","state":"Texas","county":"Uvalde County","otherGeospatial":"Edwards Aquifer","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-99.4132,29.6253],[-99.4107,29.087],[-99.6813,29.0872],[-100.1119,29.0844],[-100.1112,29.3486],[-100.111,29.6236],[-100.0145,29.6237],[-99.6173,29.6257],[-99.6033,29.6257],[-99.4132,29.6253]]]},\"properties\":{\"name\":\"Uvalde\",\"state\":\"TX\"}}]}","contact":"

Center Director, USGS Crustal Geophysics and Geochemistry Science Center
Box 25046, Mail Stop 964
Denver, CO 80225

http://crustal.usgs.gov/

","tableOfContents":"","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2016-02-23","noUsgsAuthors":false,"publicationDate":"2016-02-23","publicationStatus":"PW","scienceBaseUri":"56cd82b1e4b0b1892d9e4e9a","contributors":{"authors":[{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":588188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landis, Gary P.","contributorId":72405,"corporation":false,"usgs":true,"family":"Landis","given":"Gary","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":588189,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faith, Jason R.","contributorId":92758,"corporation":false,"usgs":true,"family":"Faith","given":"Jason","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":588190,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159430,"text":"sir20155148 - 2016 - Arsenic in groundwater of Licking County, Ohio, 2012—Occurrence and relation to hydrogeology","interactions":[],"lastModifiedDate":"2016-02-23T12:36:36","indexId":"sir20155148","displayToPublicDate":"2016-02-23T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5148","title":"Arsenic in groundwater of Licking County, Ohio, 2012—Occurrence and relation to hydrogeology","docAbstract":"

Arsenic concentrations were measured in samples from 168 domestic wells in Licking County, Ohio, to document arsenic concentrations in a wide variety of wells and to identify hydrogeologic factors associated with arsenic concentrations in groundwater. Elevated concentrations of arsenic (greater than 10.0 micrograms per liter [µg/L]) were detected in 12 percent of the wells (about 1 in 8). The maximum arsenic concentration of about 44 µg/L was detected in two wells in the same township.

A subset of 102 wells was also sampled for iron, sulfate, manganese, and nitrate, which were used to estimate redox conditions of the groundwater. Elevated arsenic concentrations were detected only in strongly reducing groundwater. Almost 20 percent of the samples with iron concentrations high enough to produce iron staining (greater than 300 µg/L) also had elevated concentrations of arsenic.

In groundwater, arsenic primarily occurs as two inorganic species—arsenite and arsenate. Arsenic speciation was determined for a subset of nine samples, and arsenite was the predominant species. Of the two species, arsenite is more difficult to remove from water, and is generally considered to be more toxic to humans.

Aquifer and well-construction characteristics were compiled from 99 well logs. Elevated concentrations of arsenic (and iron) were detected in glacial and bedrock aquifers but were more prevalent in glacial aquifers. The reason may be that the glacial deposits typically contain more organic carbon than the Paleozoic bedrock. Organic carbon plays a role in the redox reactions that cause arsenic (and iron) to be released from the aquifer matrix. Arsenic concentrations were not significantly different for different types of bedrock (sandstone, shale, sandstone/shale, or other). However, arsenic concentrations in bedrock wells were correlated with two well-construction characteristics; higher arsenic concentrations in bedrock wells were associated with (1) shorter open intervals and (2) deeper open intervals, relative to the water level.

The spatial distribution of arsenic concentrations was compared to hydrogeologic characteristics of Licking County. Elevated concentrations of arsenic (and iron) were associated with areas of flat topography and thick (greater than 100 feet),clay-rich glacial deposits. These characteristics are conducive to development of strongly reducing redox conditions, which can cause arsenic associated with iron oxyhydroxides in the aquifer matrix to be released to the groundwater.

Hydrogeologic characteristics conducive to the development of strongly reducing groundwater are relatively wide-spread in the western part of Licking County, which is part of the Central Lowland physiographic province. In this area, a thick layer of clay-rich glacial deposits obscures the bedrock surface and creates flat to gently rolling landscape with poorly developed drainage networks. In the eastern part of the county, which is part of the Appalachian Plateaus physiographic province, the landscape includes steep-sided valleys and bedrock uplands. In this area, elevated arsenic concentrations were detected in buried valleys but not in the bedrock uplands, where glacial deposits are thin or absent. The observation that elevated concentrations of arsenic (and iron) were more prevalent in the western part of Licking County is true for both glacial and bedrock aquifers.

In Licking County, thick, clay-rich glacial deposits (and elevated concentrations of arsenic) are associated with two hydrogeologic settings—buried valley and complex thick drift. Most wells in the buried-valley setting had low arsenic concentrations, but a few samples had very high concentrations (30–44 µg/L) and very reducing redox conditions (methanogenic and near-methanogenic). For wells in the complex-thick-drift setting, elevated arsenic concentrations are more prevalent, but the maximum concentration was lower (about 21 µg/L). Similar observations were made about arsenic concentrations in parts of southwestern Ohio.

The hydrogeologic settings and characteristics associated with arsenic in Licking County also exist in other parts of Ohio. The statewide extent of these characteristics roughly corresponds to areas where elevated concentrations of arsenic are known to exist. This preliminary conceptual model can be tested and revised as additional wells are sampled for arsenic.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155148","isbn":"978-1-4113-4008-4","collaboration":"Prepared in cooperation with the Ohio Water Development Authority","usgsCitation":"Thomas, M.A., 2016, Arsenic in groundwater of Licking County, Ohio, 2012—Occurrence and relation to hydrogeology:\nU.S. Geological Survey Scientific Investigations Report 2015–5148, 38 p., https://dx.doi.org/10.3133/sir20155148.","productDescription":"Report: vii, 38 p.; Table","numberOfPages":"50","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-065867","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":318250,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5148/sir20155148_table2.xlsx","text":"Table 2. Water-quality and hydrogeologic data for 168 domestic wells in Licking County, Ohio, 2012.","size":"108 kb","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5148 Table 2."},{"id":318247,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5148/coverthb.jpg"},{"id":318248,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5148/sir20155148.pdf","text":"Report","size":"9.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5148"}],"country":"United States","state":"Ohio","county":"Licking County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.96875,\n 39.95185892663003\n ],\n [\n -82.96875,\n 40.50544628405211\n ],\n [\n -81.89208984375,\n 40.50544628405211\n ],\n [\n -81.89208984375,\n 39.95185892663003\n ],\n [\n -82.96875,\n 39.95185892663003\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, USGS Ohio Water Science Center
6480 Doubletree Ave
Columbus, OH 43229-1111

http://oh.water.usgs.gov/

 

","tableOfContents":"","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-02-23","noUsgsAuthors":false,"publicationDate":"2016-02-23","publicationStatus":"PW","scienceBaseUri":"56cd82ace4b0b1892d9e4e80","contributors":{"authors":[{"text":"Thomas, Mary Ann mathomas@usgs.gov","contributorId":2536,"corporation":false,"usgs":true,"family":"Thomas","given":"Mary","email":"mathomas@usgs.gov","middleInitial":"Ann","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":578588,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70162007,"text":"ds69PP - 2016 - Geology and assessment of the undiscovered, technically recoverable petroleum resources of Armenia, 2013","interactions":[],"lastModifiedDate":"2016-02-24T09:12:55","indexId":"ds69PP","displayToPublicDate":"2016-02-23T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"69","chapter":"PP","title":"Geology and assessment of the undiscovered, technically recoverable petroleum resources of Armenia, 2013","docAbstract":"

The U.S. Geological Survey (USGS) assessed the undiscovered, technically recoverable oil and gas resources of Armenia in 2013. A Paleozoic and a Cenozoic total petroleum system (TPS) were identified within the country of Armenia. The postulated petroleum system elements are uncertain, resulting in low geologic probabilities for significant oil an gas resources. Two assessment units (AU) were delineated in each TPS—a Paleozoic-Sourced Conventional Reservoirs AU and a Permian Shale Gas AU in the Paleozoic Composite TPS and a Paleogene-Sourced Conventional Reservoirs AU and a Cenozoic Coalbed Gas AU in the Cenozoic Composite TPS. The TPS elements are largely uncertain and risked, and so only the Paleogene-Sourced Conventional Reservoirs AU was quantitatively assessed because the geologic probability is more than the threshold of 10 percent (that is, the probability of at least one conventional oil or gas accumulation of 5 million barrels of oil equivalent or greater based on postulated petroleum-system elements). The USGS estimated fully risked mean volumes of about 1 million barrels of oil (MMBO), about 6 billion cubic feet of natural gas (BCFG), and less than 1 million barrels of natural gas liquids (MMBNGL).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds69PP","usgsCitation":"Klett, T.R., 2016, Geology and assessment of undiscovered, technically recoverable petroleum resources of Armenia, 2013: U.S. Geological Survey Digital Data Series 69–PP, 21 p., https://dx.doi.org/10.3133/ds69PP.","productDescription":"Report: vi, 21 p.; Figure","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063804","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":318114,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-pp/dds69pp.pdf","text":"Report","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DDS-69-PP Report"},{"id":318113,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-pp/coverthb.jpg"},{"id":318154,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-pp/figure09.pdf","text":"Figure 9, lithostratigraphic column","size":"424 kb","linkFileType":{"id":1,"text":"pdf"},"description":"DDS-69-PP Figure 9"}],"country":"Armenia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[43.58275,41.09214],[44.97248,41.24813],[45.1795,40.98535],[45.56035,40.81229],[45.35917,40.5615],[45.89191,40.21848],[45.61001,39.89999],[46.03453,39.62802],[46.4835,39.46415],[46.50572,38.77061],[46.14362,38.7412],[45.73538,39.31972],[45.73998,39.474],[45.29814,39.47175],[45.00199,39.74],[44.79399,39.713],[44.40001,40.005],[43.65644,40.25356],[43.75266,40.7402],[43.58275,41.09214]]]},\"properties\":{\"name\":\"Armenia\"}}]}","contact":"

Center Director, USGS Central Energy Resources Science Center
Box 25046, Mail Stop 939
Denver, CO 80225

\n

http://energy.usgs.gov/

","tableOfContents":"","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2016-02-23","noUsgsAuthors":false,"publicationDate":"2016-02-23","publicationStatus":"PW","scienceBaseUri":"56cd82b0e4b0b1892d9e4e93","contributors":{"authors":[{"text":"Klett, T. R. 0000-0001-9779-1168","orcid":"https://orcid.org/0000-0001-9779-1168","contributorId":83067,"corporation":false,"usgs":true,"family":"Klett","given":"T. R.","affiliations":[],"preferred":false,"id":588321,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70159429,"text":"sir20155156 - 2016 - The effectiveness of water-treatment systems for arsenic used in 11 homes in Southwestern and Central Ohio, 2013","interactions":[],"lastModifiedDate":"2016-02-23T12:37:41","indexId":"sir20155156","displayToPublicDate":"2016-02-23T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5156","title":"The effectiveness of water-treatment systems for arsenic used in 11 homes in Southwestern and Central Ohio, 2013","docAbstract":"

In 2013, the U.S. Geological Survey and the Miami Conservancy District investigated the effectiveness of methods used to remove arsenic from drinking water at 11 homes in southwestern and central Ohio. The untreated (raw) ground-water had arsenic concentrations of 7.7–382 micrograms per liter (µg/L), and the median concentration was 30 µg/L. The pH was neutral to slightly alkaline, and redox conditions were strongly reducing, as indicated by high concentrations of iron. The predominant arsenic species was arsenite (As3+), which is difficult to treat because it exists in water as an uncharged compound (H3AsO3).

The water-treatment systems included (1) seven single-tap reverse-osmosis systems, (2) two whole-house oxidation/filtration systems, and (3) two systems that included wholehouse anion exchange and single-tap reverse osmosis. All but one system included pretreatment by a water softener, and two systems included preoxidation to convert arsenite (As3+) to arsenate (As5+) before treatment by anion exchange.

None of the treatment systems removed all of the arsenic from the drinking water. About one-half of the systems decreased the arsenic concentration to less than the maximum contamination level of 10 µg/L. The effectiveness of the systems varied widely; the percentage of arsenic removed ranged from 2 to 90 percent, and the median was 65 percent.

At some sites, the low effectiveness of arsenic removal may have been related to system maintenance and(or) operation issues. At two sites, homeowners acknowledged that the treatment systems had not been maintained for several years. At two other sites, the treatment systems were being maintained, but the water-quality data indicated that one of the components was not working, unbeknownst to the homeowner. EPA research at a small number of sites in Ohio indicated that operation and maintenance of some arsenic-treatment systems was not always simple.

Another factor that affected system effectiveness was the quality of the raw water. In general, the treatment systems were less effective at treating higher concentrations of arsenic. For five sites with raw-water arsenic concentrations of 10–30 µg/L, the systems removed 65–81 percent of the arsenic, and the final concentrations were less than the maximum contamination level. For three sites with higher raw-water arsenic concentrations (50–75 µg/L), the systems removed 22–34 percent of the arsenic; and the final concentrations were 4–5 times more than the maximum contamination level. Other characteristics of the raw water may have affected the performance of treatment systems; in general, raw water with the higher arsenic concentrations also had higher pH, higher concentrations of organic carbon and ammonia, and more reducing (methanogenic) redox conditions.

For sites with raw-water arsenic concentrations of 10–30 µg/L, two types of systems (reverse osmosis and oxidation/filtration) removed similar amounts of arsenic, but the quality of the treated water differed in other respects. Reverse osmosis caused substantial decreases in pH, alkalinity, and concentrations of most ions. On the other hand, oxidation/filtration using manganese-based media caused a large increase of manganese concentrations, from less than 50 µg/L in raw water to more than 700 µg/L in outflow from the oxidation filtration units.

It is not known if the results of this study are widely applicable; the number of systems sampled was relatively small, and each system was sampled only once. Further study may be warranted to investigate whether available methods of arsenic removal are effective/practical for residential use in areas like Ohio, were groundwater with elevated arsenic concentrations is strongly reducing, and the predominant arsenic species is arsenite (As3+).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155156","isbn":"978-1-4113-4006-0","collaboration":"Prepared in cooperation with Miami Conservancy District","usgsCitation":"Thomas, M.A., and Ekberg, Mike, 2016, The effectiveness of water-treatment systems for arsenic used in 11 homes in Southwestern and Central Ohio, 2013: U.S. Geological Survey Scientific Investigations Report 2015–5156, 26 p., https://dx.doi.org/10.3133/sir20155156.","productDescription":"Report: vi, 26 p.; Table","numberOfPages":"37","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-065490","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":318264,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5156/sir20155156_table2.xlsx","text":"Table 2. Water-quality results from 11 domestic wells in southwestern and central Ohio, 2013","size":"36.0 kb","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5156 Table 2"},{"id":318263,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5156/sir20155156.pdf","text":"Report","size":"1.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5156"},{"id":318262,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5156/coverthb.jpg"}],"country":"United States","state":"Ohio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.825439453125,\n 39.24927084622338\n ],\n [\n -84.825439453125,\n 40.43858586704328\n ],\n [\n -81.815185546875,\n 40.43858586704328\n ],\n [\n -81.815185546875,\n 39.24927084622338\n ],\n [\n -84.825439453125,\n 39.24927084622338\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, USGS Ohio Water Science Center
6480 Doubletree Ave
Columbus, OH 43229-1111

http://oh.water.usgs.gov/

 

","tableOfContents":"","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-02-23","noUsgsAuthors":false,"publicationDate":"2016-02-23","publicationStatus":"PW","scienceBaseUri":"56cd82b4e4b0b1892d9e4ea5","contributors":{"authors":[{"text":"Thomas, Mary Ann mathomas@usgs.gov","contributorId":2536,"corporation":false,"usgs":true,"family":"Thomas","given":"Mary","email":"mathomas@usgs.gov","middleInitial":"Ann","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":578586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ekberg, Mike","contributorId":149482,"corporation":false,"usgs":false,"family":"Ekberg","given":"Mike","affiliations":[{"id":17747,"text":"Miami Conservancy District","active":true,"usgs":false}],"preferred":false,"id":578587,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168722,"text":"70168722 - 2016 - Active tectonics within the NW and SE extensions of the Pambak-Sevan-Syunik fault: Implications for the present geodynamics of Armenia","interactions":[],"lastModifiedDate":"2016-02-26T14:08:51","indexId":"70168722","displayToPublicDate":"2016-02-22T15:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3217,"text":"Quaternary International","active":true,"publicationSubtype":{"id":10}},"title":"Active tectonics within the NW and SE extensions of the Pambak-Sevan-Syunik fault: Implications for the present geodynamics of Armenia","docAbstract":"

This study analyzes the active tectonics within the northwestern and southeastern extensions of the Pambak-Sevan-Syunik fault (PSSF), a major right-lateral strike-slip fault cutting through Armenia. Quantifying the deformations in terms of geometry, kinematics, slip rates and earthquake activity, using cosmogenic 3He, OSL/IRSL and radiocarbon dating techniques, reveal different behaviors between the two regions. Within the northwestern extension, in the region of Amasia, the PSSF bends to the west and splits into two main WNW–ESE trending reverse faults defining a compressional pop-up structure. We estimate an uplift rate and a shortening rate of 0.5 ± 0.1 mm/y and 1.4 ± 0.6 mm/y, respectively. This suggests that most of the ∼2 mm/y right lateral movement of the PSSF seems to be absorbed within the Amasia pop-structure. Within the southeastern extension, the PSSF shows signs of dying out within the Tsghuk Volcano region at the southernmost tip of the Syunik graben. There, the tectonic activity is characterized by a very slow NS trending normal faulting associated with a slight right-lateral movement. Slip rates analyses (i.e. vertical slip rate, EW stretching rate at 90° to the fault, and right-lateral slip rate of ∼0.2 mm/y, ∼0.1 mm/y and ∼0.05 mm/y, respectively) lead to the conclusion that the right lateral movement observed further north along the PSSF is mainly transferred within other active faults further west within the Karabagh (Hagari fault or other structures further northwestwards). Comparing our slip rates with those estimated from GPS data suggests that most of the deformation is localized and seismic, at least within the Tsghuk region. The geometrical and kinematic pattern observed within the two terminations of the PSSF suggests that the fault and its surrounding crustal blocks are presently rotating anticlockwise, as also observed within the GPS velocity field. This is consistent with the recent kinematic models proposed for the Caucasus-Kura-South Caspian region and brings a new insight into the present geodynamics of Armenia.

\n

 

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Sediment accumulation threatens the viability and hydrologic functioning of many naturally formed depressional wetlands across the interior regions of North America. These wetlands provide many ecosystem services and vital habitats for diverse plant and animal communities. Climate change may further impact sediment accumulation rates in the context of current land use patterns. We estimated sediment accretion in wetlands within a region renowned for its large populations of breeding waterfowl and migrant shorebirds and examined the relative roles of precipitation and land use context in the sedimentation process. We modeled rates of sediment accumulation from 1971 through 2100 using the Revised Universal Soil Loss Equation (RUSLE) with a sediment delivery ratio and the Unit Stream Power Erosion Deposition model (USPED). These models predicted that by 2100, 21–33 % of wetlands filled completely with sediment and 27–46 % filled by half with sediments; estimates are consistent with measured sediment accumulation rates in the region reported by empirical studies. Sediment accumulation rates were strongly influenced by size of the catchment, greater coverage of tilled landscape within the catchment, and steeper slopes. Conservation efforts that incorporate the relative risk of infilling of wetlands with sediments, thus emphasizing areas of high topographic relief and large watersheds, may benefit wetland-dependent biota.

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Heavy rainfall occurred across South Carolina during October 1–5, 2015, as a result of an upper atmospheric low-pressure system that funneled tropical moisture from Hurricane Joaquin into the State. The storm caused major flooding in the central and coastal parts of South Carolina. Almost 27 inches of rain fell near Mount Pleasant in Charleston County during this period. U.S. Geological Survey (USGS) streamgages recorded peaks of record at 17 locations, and 15 other locations had peaks that ranked in the top 5 for the period of record. During the October 2015 flood event, USGS personnel made about 140 streamflow measurements at 86 locations to verify, update, or extend existing rating curves (which are used to compute streamflow from monitored river stage). Immediately after the storm event, USGS personnel documented 602 high-water marks, noting the location and height of the water above land surface. Later in October, 50 additional high-water marks were documented near bridges for South Carolina Department of Transportation. Using a subset of these high-water marks, 20 flood-inundation maps of 12 communities were created. Digital datasets of the inundation area, modeling boundary, and water depth rasters are all available for download.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161019","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Musser, J.W., Watson, K.M., Painter, J.A., and Gotvald, A.J., 2016, Flood-inundation maps of selected areas affected by the flood of October 2015 in central and coastal South Carolina: U.S. Geological Survey Open-File Report 2016–1019, 81 p., https://dx.doi.org/10.3133/ofr20161019.","productDescription":"Report: v, 81 p.; Raw Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072657","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":318176,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1019/ofr20161019.pdf","text":"Report","size":"47.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1019"},{"id":318175,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1019/coverthb.jpg"},{"id":318184,"rank":3,"type":{"id":19,"text":"Raw Data"},"url":"https://water.usgs.gov/floods/events/2015/Joaquin/data_ofr20161019","text":"USGS Flood Information (Data Download)"}],"country":"United States","state":"South Carolina","otherGeospatial":"Salkehatchie River Basin, Savannah River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.541259765625,\n 33.86129311351553\n ],\n [\n -78.64013671875,\n 33.76088200086917\n ],\n [\n -78.94775390625,\n 33.61461929233378\n ],\n [\n -79.1015625,\n 33.348884792201694\n ],\n [\n -79.1455078125,\n 33.22030778968541\n ],\n [\n -79.34326171875,\n 32.99945000822837\n ],\n [\n -79.530029296875,\n 32.96258644191747\n ],\n [\n -79.60693359375,\n 32.85190345738802\n ],\n [\n -79.815673828125,\n 32.74108223150125\n ],\n [\n -80.057373046875,\n 32.55607364492029\n ],\n [\n -80.2880859375,\n 32.491230287947594\n ],\n [\n -80.386962890625,\n 32.41706632846282\n ],\n [\n -80.474853515625,\n 32.287132632616384\n ],\n [\n -80.628662109375,\n 32.175612478499346\n ],\n [\n -80.7275390625,\n 32.06395559466043\n ],\n [\n -80.85937499999999,\n 31.942839972853083\n ],\n [\n -80.936279296875,\n 31.99875937194732\n ],\n [\n -81.123046875,\n 32.12910537866886\n ],\n [\n -81.14501953125,\n 32.25926542645936\n ],\n [\n -81.14501953125,\n 32.36140331527543\n ],\n [\n -81.2548828125,\n 32.44488496716713\n ],\n [\n -81.298828125,\n 32.537551746769\n ],\n [\n -81.375732421875,\n 32.58384932565662\n ],\n [\n -81.4306640625,\n 32.685619853722\n ],\n [\n -81.474609375,\n 32.879587173066305\n ],\n [\n -81.507568359375,\n 33.00866349457558\n ],\n [\n -81.58447265624999,\n 33.073130945006625\n ],\n [\n -81.71630859375,\n 33.146750228776455\n ],\n [\n -81.815185546875,\n 33.23868752757414\n ],\n [\n -81.88110351562499,\n 33.32134852669881\n ],\n [\n -81.990966796875,\n 33.37641235124676\n ],\n [\n -81.947021484375,\n 33.458942753687644\n ],\n [\n -82.078857421875,\n 33.568861182555544\n ],\n [\n -82.166748046875,\n 33.642062504753675\n ],\n [\n -82.19970703125,\n 33.715201644740844\n ],\n [\n -82.28759765625,\n 33.80653802509606\n ],\n [\n -82.430419921875,\n 33.897777013859475\n ],\n [\n -82.55126953124999,\n 34.00713506435885\n ],\n [\n -82.496337890625,\n 34.17999758688084\n ],\n [\n -82.254638671875,\n 34.75966612466248\n ],\n [\n -81.947021484375,\n 35.11990857099681\n ],\n [\n -81.837158203125,\n 35.191766965947394\n ],\n [\n -81.39770507812499,\n 35.16482750605027\n ],\n [\n -81.046142578125,\n 35.146862906756304\n ],\n [\n -81.024169921875,\n 35.074964853989556\n ],\n [\n -80.91430664062499,\n 35.110921809704756\n ],\n [\n -80.771484375,\n 34.95799531086792\n ],\n [\n -80.782470703125,\n 34.84987503195418\n ],\n [\n -80.5517578125,\n 34.831841149828676\n ],\n [\n -80.255126953125,\n 34.804782919572425\n ],\n [\n -79.716796875,\n 34.82282272723702\n ],\n [\n -78.541259765625,\n 33.86129311351553\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-02-22","noUsgsAuthors":false,"publicationDate":"2016-02-22","publicationStatus":"PW","scienceBaseUri":"56cc3129e4b059daa47df815","contributors":{"authors":[{"text":"Musser, Jonathan W. 0000-0002-3543-0807 jwmusser@usgs.gov","orcid":"https://orcid.org/0000-0002-3543-0807","contributorId":2266,"corporation":false,"usgs":true,"family":"Musser","given":"Jonathan","email":"jwmusser@usgs.gov","middleInitial":"W.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620148,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watson, Kara M. 0000-0002-2685-0260 kmwatson@usgs.gov","orcid":"https://orcid.org/0000-0002-2685-0260","contributorId":2134,"corporation":false,"usgs":true,"family":"Watson","given":"Kara","email":"kmwatson@usgs.gov","middleInitial":"M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620149,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Painter, Jaime A. 0000-0001-8883-9158 jpainter@usgs.gov","orcid":"https://orcid.org/0000-0001-8883-9158","contributorId":1466,"corporation":false,"usgs":true,"family":"Painter","given":"Jaime","email":"jpainter@usgs.gov","middleInitial":"A.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620150,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gotvald, Anthony J. 0000-0002-9019-750X agotvald@usgs.gov","orcid":"https://orcid.org/0000-0002-9019-750X","contributorId":1970,"corporation":false,"usgs":true,"family":"Gotvald","given":"Anthony","email":"agotvald@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620151,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174205,"text":"70174205 - 2016 - Hydraulic and biochemical gradients limit wetland mercury supply to an Adirondack stream","interactions":[],"lastModifiedDate":"2020-12-21T16:03:58.442011","indexId":"70174205","displayToPublicDate":"2016-02-22T06:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5121,"text":"SOJ Aquatic Research","active":true,"publicationSubtype":{"id":10}},"title":"Hydraulic and biochemical gradients limit wetland mercury supply to an Adirondack stream","docAbstract":"

Net fluxes (change between upstream and downstream margins) for water, methylmercury (MeHg), total mercury (THg), dissolved organic carbon (DOC), and chloride (Cl) were assessed twice in an Adirondack stream reach (Sixmile Brook, USA), to test the hypothesized importance of wetland-stream hydraulic and chemical gradients as fundamental controls on fluvial mercury (Hg) supply. The 500 m study reach represented less than 4% of total upstream basin area. During a snowmelt high-flow event in May 2009 surface water, DOC, and chloride fluxes increased by 7.1±1.3%, 8.0±1.3%, and 9.0±1.3%, respectively, within the reach, demonstrating that the adjacent wetlands are important sources of water and solutes to the stream. However, shallow groundwater Hg concentrations lower than in the surface water limited groundwater-surface water Hg exchange and no significant changes in Hg (filtered MeHg and THg) fluxes were observed within the reach despite the favorable hydraulic gradient. In August 2009, the lack of significant wetland-stream hydraulic gradient resulted in no net flux of water or solutes (MeHg, THg, DOC, or Cl) within the reach. The results are consistent with the wetland-Hg-source hypothesis and indicate that hydraulic and chemical gradient (direction and magnitude) interactions are fundamental controls on the supply of wetland Hg to the stream.

","language":"English","publisher":"Symbiosis Group","doi":"10.15226/24754706/1/1/00102","usgsCitation":"Bradley, P.M., Burns, D.A., Harvey, J., Journey, C.A., Brigham, M.E., and Riva-Murray, K., 2016, Hydraulic and biochemical gradients limit wetland mercury supply to an Adirondack stream: SOJ Aquatic Research, v. 1, no. 17, p. 1-9, https://doi.org/10.15226/24754706/1/1/00102.","productDescription":"9 p.","startPage":"1","endPage":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054962","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":471213,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15226/24754706/1/1/00102","text":"Publisher Index Page"},{"id":324656,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York, South Carolina","otherGeospatial":"Fishing Brook, McTier Creek basin, Sixmile Brook","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.990966796875,\n 33.442901319379345\n ],\n [\n -81.990966796875,\n 34.01396527491264\n ],\n [\n -81.09283447265625,\n 34.01396527491264\n ],\n [\n -81.09283447265625,\n 33.442901319379345\n ],\n [\n -81.990966796875,\n 33.442901319379345\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.7125244140625,\n 43.69965122967144\n ],\n [\n -74.7125244140625,\n 44.3670601700202\n ],\n [\n -73.6578369140625,\n 44.3670601700202\n ],\n [\n -73.6578369140625,\n 43.69965122967144\n ],\n [\n -74.7125244140625,\n 43.69965122967144\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"1","issue":"17","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-22","publicationStatus":"PW","scienceBaseUri":"5774f25ae4b07dd077c6a300","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":641286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harvey, Judson 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":140228,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":641287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":641288,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brigham, Mark E. 0000-0001-7412-6800 mbrigham@usgs.gov","orcid":"https://orcid.org/0000-0001-7412-6800","contributorId":1840,"corporation":false,"usgs":true,"family":"Brigham","given":"Mark","email":"mbrigham@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641289,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":168876,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641290,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70169298,"text":"70169298 - 2016 - Are the Columbia River Basalts, Columbia Plateau, Idaho, Oregon, and Washington, USA, a viable geothermal target? A preliminary analysis","interactions":[],"lastModifiedDate":"2017-04-21T16:05:35","indexId":"70169298","displayToPublicDate":"2016-02-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Are the Columbia River Basalts, Columbia Plateau, Idaho, Oregon, and Washington, USA, a viable geothermal target? A preliminary analysis","docAbstract":"

The successful development of a geothermal electric power generation facility relies on (1) the identification of sufficiently high temperatures at an economically viable depth and (2) the existence of or potential to create and maintain a permeable zone (permeability >10-14 m2) of sufficient size to allow efficient long-term extraction of heat from the reservoir host rock. If both occur at depth under the Columbia Plateau, development of geothermal resources there has the potential to expand both the magnitude and spatial extent of geothermal energy production. However, a number of scientific and technical issues must be resolved in order to evaluate the likelihood that the Columbia River Basalts, or deeper geologic units under the Columbia Plateau, are viable geothermal targets.

Recent research has demonstrated that heat flow beneath the Columbia Plateau Regional Aquifer System may be higher than previously measured in relatively shallow (<600 m depth) wells, indicating that sufficient temperatures for electricity generation occur at depths 5 km. The remaining consideration is evaluating the likelihood that naturally high permeability exists, or that it is possible to replicate the high average permeability (approximately 10-14 to 10-12 m2) characteristic of natural hydrothermal reservoirs. From a hydraulic perspective, Columbia River Basalts are typically divided into dense, impermeable flow interiors and interflow zones comprising the top of one flow, the bottom of the overlying flow, and any sedimentary interbed. Interflow zones are highly variable in texture but, at depths <600 m, some of them form highly permeable regional aquifers with connectivity over many tens of kilometers. Below depths of ~600 m, permeability reduction occurs in many interflow zones, caused by the formation of low-temperature hydrothermal alteration minerals (corresponding to temperatures above ~35 °C). However, some high permeability (>10-14 m2) interflows are documented at depths up to ~1,400 m. If the elevated permeability in these zones persists to greater depths, they may provide natural permeability of sufficient magnitude to allow their exploitation as conventional geothermal reservoirs. Alternatively, if the permeability in these interflow zones is less than 10-14 m2 at depth, it may be possible to use hydraulic and thermal stimulation to enhance the permeability of both the interflow zones and the natural jointing within the low-permeability interior portions of individual basalt flows in order to develop Enhanced/Engineered Geothermal System (EGS) reservoirs. The key challenge for an improved Columbia Plateau geothermal assessment is acquiring and interpreting comprehensive field data that can provide quantitative constraints on the recovery of heat from the Columbia River Basalts at depths greater than those currently tested by deep boreholes.

","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings, 41st Workshop on Geothermal Reservoir Engineering","largerWorkSubtype":{"id":19,"text":"Conference Paper"},"conferenceTitle":"41st Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 22-24, 2016","conferenceLocation":"Stanford, CA","language":"English","publisher":"Stanford University","publisherLocation":"Stanford, CA","usgsCitation":"Burns, E.R., Williams, C.F., Tolan, T., and Kaven, J.O., 2016, Are the Columbia River Basalts, Columbia Plateau, Idaho, Oregon, and Washington, USA, a viable geothermal target? A preliminary analysis, in Proceedings, 41st Workshop on Geothermal Reservoir Engineering, Stanford, CA, February 22-24, 2016, 11 p.","productDescription":"11 p.","ipdsId":"IP-071284","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":340099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon, Washington","otherGeospatial":"Columbia Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.25,\n 44.25\n ],\n [\n -115.25,\n 44.25\n ],\n [\n -115.25,\n 48.5\n ],\n [\n -122.25,\n 48.5\n ],\n [\n -122.25,\n 44.25\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58fb1a4ee4b0c3010a8087c5","contributors":{"authors":[{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":3094,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":623483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Colin F. 0000-0003-2196-5496 colin@usgs.gov","orcid":"https://orcid.org/0000-0003-2196-5496","contributorId":274,"corporation":false,"usgs":true,"family":"Williams","given":"Colin","email":"colin@usgs.gov","middleInitial":"F.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":623484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tolan, Terry","contributorId":55489,"corporation":false,"usgs":true,"family":"Tolan","given":"Terry","affiliations":[],"preferred":false,"id":623485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaven, Joern Ole","contributorId":148002,"corporation":false,"usgs":false,"family":"Kaven","given":"Joern","email":"","middleInitial":"Ole","affiliations":[],"preferred":false,"id":623486,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170108,"text":"70170108 - 2016 - Efficiency of portable antennas for detecting passive integrated transponder tags in stream-dwelling salmonids","interactions":[],"lastModifiedDate":"2016-04-06T17:03:16","indexId":"70170108","displayToPublicDate":"2016-02-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Efficiency of portable antennas for detecting passive integrated transponder tags in stream-dwelling salmonids","docAbstract":"

Portable antennas have become an increasingly common technique for tracking fish marked with passive integrated transponder (PIT) tags. We used logistic regression to evaluate how species, fish length, and physical habitat characteristics influence portable antenna detection efficiency in stream-dwelling brown trout (Salmo trutta), bull trout (Salvelinus confluentus), and redband trout (Oncorhynchus mykiss newberrii) marked with 12-mm PIT tags. We redetected 56% (20/36) of brown trout, 34% (68/202) of bull trout, and 33% (20/61) of redband trout after a recovery period of 21 to 46 hours. Models indicate support for length and species and minor support for percent boulder, large woody debris, and percent cobble as parameters important for describing variation in detection efficiency, although 95% confidence intervals for estimates were large. The odds of detecting brown trout (1.5 ± 2.2 [mean ± SE]) are approximately four times as high as bull trout (0.4 ± 1.6) or redband trout (0.3 ± 1.8) and species-specific differences may be related to length. Our reported detection efficiency for brown trout falls within the range of other studies, but is the first reported for bull trout and redband trout. Portable antennas may be a relatively unbiased way of redetecting varying sizes of all three salmonid species.

","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0149898","usgsCitation":"Banish, N.P., Burdick, S.M., and Moyer, K.R., 2016, Efficiency of portable antennas for detecting passive integrated transponder tags in stream-dwelling salmonids: PLoS ONE, v. 11, no. 2, e0149898, 10 p., https://doi.org/10.1371/journal.pone.0149898.","productDescription":"e0149898, 10 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052642","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":471214,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0149898","text":"Publisher Index Page"},{"id":319877,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","county":"Klamath County, Lake County","otherGeospatial":"Boulder Creek, Brownsworth Creek, Klamath River basin, Leonard Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.9,\n 42.45\n ],\n [\n -120.9,\n 42.55\n ],\n [\n -120.8,\n 42.55\n ],\n [\n -120.8,\n 42.45\n ],\n [\n -120.9,\n 42.45\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-22","publicationStatus":"PW","scienceBaseUri":"572485fde4b0b13d39159452","contributors":{"authors":[{"text":"Banish, Nolan P.","contributorId":168511,"corporation":false,"usgs":false,"family":"Banish","given":"Nolan","email":"","middleInitial":"P.","affiliations":[{"id":25313,"text":"U.S. Fish and Wildlife Service, Klamath Falls Fish and Wildlife Office, 1936 California Avenue, Klamath Falls, Oregon, 97601, USA","active":true,"usgs":false}],"preferred":false,"id":626212,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burdick, Summer M. 0000-0002-3480-5793 sburdick@usgs.gov","orcid":"https://orcid.org/0000-0002-3480-5793","contributorId":3448,"corporation":false,"usgs":true,"family":"Burdick","given":"Summer","email":"sburdick@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":626211,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moyer, Katherine R.","contributorId":168512,"corporation":false,"usgs":false,"family":"Moyer","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":25314,"text":"Conservation and Land Management Internship Program, Chicago Botanic Garden, 1000 Lake Cook Road, Glencoe, Illinois, 60022, USA","active":true,"usgs":false}],"preferred":false,"id":626213,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70177889,"text":"70177889 - 2016 - Toward a quantitative and empirical dissolved organic carbon budget for the Gulf of Maine, a semienclosed shelf sea","interactions":[],"lastModifiedDate":"2016-10-26T14:12:02","indexId":"70177889","displayToPublicDate":"2016-02-20T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Toward a quantitative and empirical dissolved organic carbon budget for the Gulf of Maine, a semienclosed shelf sea","docAbstract":"A time series of organic carbon export from Gulf of Maine (GoM) watersheds was compared to a time series of biological, chemical, bio-optical, and hydrographic properties, measured across the GoM between Yarmouth, NS, Canada, and Portland, ME, U.S. Optical proxies were used to quantify the dissolved organic carbon (DOC) and particulate organic carbon in the GoM. The Load Estimator regression model applied to river discharge data demonstrated that riverine DOC export (and its decadal variance) has increased over the last 80 years. Several extraordinarily wet years (2006–2010) resulted in a massive pulse of chromophoric dissolved organic matter (CDOM; proxy for DOC) into the western GoM along with unidentified optically scattering material (<0.2 μm diameter). A survey of DOC in the GoM and Scotian Shelf showed the strong influence of the Gulf of Saint Lawrence on the DOC that enters the GoM. A deep plume of CDOM-rich water was observed near the coast of Maine which decreased in concentration eastward. The Forel-Ule color scale was derived and compared to the same measurements made in 1912–1913 by Henry Bigelow. Results show that the GoM has yellowed in the last century, particularly in the region of the extension of the Eastern Maine Coastal Current. Time lags between DOC discharge and its appearance in the GoM increased with distance from the river mouths. Algae were also a significant source of DOC but not CDOM. Gulf-wide algal primary production has decreased. Increases in precipitation and DOC discharge to the GoM are predicted over the next century.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015GB005332","usgsCitation":"Balch, W., Huntington, T.G., Aiken, G.R., Drapeau, D., Bowler, B., Lubelczyk, L., and Butler, K.D., 2016, Toward a quantitative and empirical dissolved organic carbon budget for the Gulf of Maine, a semienclosed shelf sea: Global Biogeochemical Cycles, v. 30, no. 2, p. 268-292, https://doi.org/10.1002/2015GB005332.","productDescription":"25 p.","startPage":"268","endPage":"292","ipdsId":"IP-072221","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471216,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gb005332","text":"Publisher Index Page"},{"id":330416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Gulf of Maine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72,\n 42\n ],\n [\n -72,\n 47\n ],\n [\n -65,\n 47\n ],\n [\n -65,\n 42\n ],\n [\n -72,\n 42\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-20","publicationStatus":"PW","scienceBaseUri":"5811c0f3e4b0f497e79a5a7f","contributors":{"authors":[{"text":"Balch, William","contributorId":176267,"corporation":false,"usgs":false,"family":"Balch","given":"William","affiliations":[],"preferred":false,"id":652037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huntington, Thomas G. 0000-0002-9427-3530 thunting@usgs.gov","orcid":"https://orcid.org/0000-0002-9427-3530","contributorId":1884,"corporation":false,"usgs":true,"family":"Huntington","given":"Thomas","email":"thunting@usgs.gov","middleInitial":"G.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652036,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drapeau, David","contributorId":176268,"corporation":false,"usgs":false,"family":"Drapeau","given":"David","email":"","affiliations":[],"preferred":false,"id":652039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bowler, Bruce","contributorId":176269,"corporation":false,"usgs":false,"family":"Bowler","given":"Bruce","email":"","affiliations":[],"preferred":false,"id":652040,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lubelczyk, Laura","contributorId":176270,"corporation":false,"usgs":false,"family":"Lubelczyk","given":"Laura","email":"","affiliations":[],"preferred":false,"id":652041,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Butler, Kenna D. kebutler@usgs.gov","contributorId":3283,"corporation":false,"usgs":true,"family":"Butler","given":"Kenna","email":"kebutler@usgs.gov","middleInitial":"D.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":652042,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70173794,"text":"70173794 - 2016 - Potential foraging decisions by a desert ungulate to balance water and nutrient intake in a water-stressed environment","interactions":[],"lastModifiedDate":"2016-06-10T13:21:40","indexId":"70173794","displayToPublicDate":"2016-02-19T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Potential foraging decisions by a desert ungulate to balance water and nutrient intake in a water-stressed environment","docAbstract":"

Arid climates have unpredictable precipitation patterns, and wildlife managers often provide supplemental water to help desert ungulates endure the hottest, driest periods. When surface water is unavailable, the only source of water for ungulates comes from the forage they consume, and they must make resourceful foraging decisions to meet their requirements. We compared two desert bighorn sheep (Ovis canadensis nelsoni) populations in Arizona, USA: a treatment population with supplemental water removed during treatment, and a control population. We examined whether sheep altered their seasonal diets without supplemental water. We calculated water and nutrient intake and metabolic water production from dry matter intake and forage moisture and nitrogen content, to determine whether sheep could meet their seasonal daily water and nutrient requirements solely from forage. Diets of sheep were higher in protein (all seasons) and moisture (autumn and winter) during treatment compared to pretreatment. During treatment, sheep diet composition was similar between the treatment and control populations, which suggests, under the climatic conditions of this study, water removal did not influence sheep diets. We estimated that under drought conditions, without any surface water available (although small ephemeral potholes would contain water after rains), female and male sheep would be unable to meet their daily water requirements in all seasons, except winter, when reproductive females had a nitrogen deficit. We determined that sheep could achieve water and nutrient balances in all seasons by shifting their total diet proportions by 8–55% from lower to higher moisture and nitrogen forage species. We elucidate how seasonal forage quality and foraging decisions by desert ungulates allow them to cope with their xeric and uncertain environment, and suggest that, with the forage conditions observed in our study area during this study period, providing supplemental water during water-stressed periods may not be necessary for desert bighorn sheep.

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\"}}]}","volume":"11","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-19","publicationStatus":"PW","scienceBaseUri":"575be4ace4b04f417c27f531","contributors":{"authors":[{"text":"Gedir, Jay V.","contributorId":171735,"corporation":false,"usgs":false,"family":"Gedir","given":"Jay","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":638454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":638371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krausman, Paul R.","contributorId":31467,"corporation":false,"usgs":true,"family":"Krausman","given":"Paul","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":638455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, Jamison D.","contributorId":171736,"corporation":false,"usgs":false,"family":"Allen","given":"Jamison","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":638456,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duff, Glenn C.","contributorId":171737,"corporation":false,"usgs":false,"family":"Duff","given":"Glenn","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":638457,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morgart, John R.","contributorId":10891,"corporation":false,"usgs":true,"family":"Morgart","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":638458,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70164420,"text":"ds980 - 2016 - Terrestrial-based lidar beach topography of Fire Island, New York, June 2014","interactions":[],"lastModifiedDate":"2016-08-03T08:45:50","indexId":"ds980","displayToPublicDate":"2016-02-19T12:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"980","title":"Terrestrial-based lidar beach topography of Fire Island, New York, June 2014","docAbstract":"

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) in Florida and the USGS Lower Mississippi-Gulf Water Science Center (LMG WSC) in Montgomery, Alabama, collaborated to gather alongshore terrestrial-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on June 11, 2014, to characterize beach topography and document ongoing beach evolution and recovery, and is part of the ongoing beach monitoring within the Hurricane Sandy Supplemental Project GS2-2B. This USGS data series includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds980","usgsCitation":"Brenner, O.T., Hapke, C.J., Lee, K.G., and Kimbrow, D.R., 2016, Terrestrial-based lidar beach topography of Fire Island, New York, June 2014: U.S. Geological Survey Data Series 980, https://dx.doi.org/10.3133/ds980.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070657","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":318152,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":318151,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0980/index.html","text":"Report (HTML)","description":"DS 980"},{"id":325917,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://dx.doi.org/10.3133/ds921","text":"Data Series 921- Ground-Based Lidar Beach Topography of Fire Island, New York, April 2013","description":"DS 980"},{"id":325918,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F77H1GNN","text":"USGS data release - Ground-Based Lidar Beach Topography of Fire Island, New York, April 2014"},{"id":325919,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7862DKH","text":"USGS data release - Terrestrial-Based Lidar Beach Topography of Fire Island, New York, May 2015"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.83197402954102,\n 40.743225290205785\n ],\n [\n -72.83111572265625,\n 40.74101426921151\n ],\n [\n -72.84811019897461,\n 40.73633186448861\n ],\n [\n -72.86785125732422,\n 40.7302182289573\n ],\n [\n -72.88639068603516,\n 40.72384384060296\n ],\n [\n -72.894287109375,\n 40.721892375167045\n ],\n [\n -72.89445877075195,\n 40.72345355209305\n ],\n [\n -72.88055419921875,\n 40.728397037445035\n ],\n [\n -72.86476135253906,\n 40.73360030952804\n ],\n [\n -72.84965515136719,\n 40.738152838822934\n ],\n [\n -72.83197402954102,\n 40.743225290205785\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.92415618896484,\n 40.71577741296778\n ],\n [\n -72.9550552368164,\n 40.704586878965245\n ],\n [\n -72.99522399902344,\n 40.689229364982054\n ],\n [\n -73.04328918457031,\n 40.67360792349548\n ],\n [\n -73.07968139648438,\n 40.66188943992171\n ],\n [\n -73.10474395751953,\n 40.65720146993478\n ],\n [\n -73.14319610595703,\n 40.64912697157757\n ],\n [\n -73.16654205322266,\n 40.64339608963903\n ],\n [\n -73.19503784179688,\n 40.63740418690266\n ],\n [\n -73.22628021240234,\n 40.63115119323159\n ],\n [\n -73.22525024414062,\n 40.62541876792774\n ],\n [\n -73.18920135498047,\n 40.634017221357695\n ],\n [\n -73.15074920654297,\n 40.64261456761013\n ],\n [\n -73.10405731201172,\n 40.65251317049883\n ],\n [\n -73.09341430664062,\n 40.65459689980922\n ],\n [\n -73.08860778808594,\n 40.653294576616204\n ],\n [\n -73.08002471923828,\n 40.65772237175813\n ],\n [\n -73.05461883544922,\n 40.6639728763869\n ],\n [\n -73.037109375,\n 40.669441587473884\n ],\n [\n -72.98355102539062,\n 40.68844837985795\n ],\n [\n -72.92381286621094,\n 40.71135347314246\n ],\n [\n -72.91145324707031,\n 40.71577741296778\n ],\n [\n -72.91351318359375,\n 40.718379593199494\n ],\n [\n -72.92415618896484,\n 40.71577741296778\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502-8000
http://coastal.er.usgs.gov/

","tableOfContents":"","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"publishedDate":"2016-02-19","noUsgsAuthors":false,"publicationDate":"2016-02-19","publicationStatus":"PW","scienceBaseUri":"56c83cace4b0b3c9ae37b20f","contributors":{"authors":[{"text":"Brenner, Owen T. 0000-0002-1588-721X obrenner@usgs.gov","orcid":"https://orcid.org/0000-0002-1588-721X","contributorId":4933,"corporation":false,"usgs":true,"family":"Brenner","given":"Owen","email":"obrenner@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":597190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":597191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Kathryn G.","contributorId":108009,"corporation":false,"usgs":true,"family":"Lee","given":"Kathryn G.","affiliations":[],"preferred":false,"id":597192,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kimbrow, Dustin R. dkimbrow@usgs.gov","contributorId":3915,"corporation":false,"usgs":true,"family":"Kimbrow","given":"Dustin","email":"dkimbrow@usgs.gov","middleInitial":"R.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":597193,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70162131,"text":"sir20155184 - 2016 - Regression equations to estimate seasonal flow duration, n-day high-flow frequency, and n-day low-flow frequency at sites in North Dakota using data through water year 2009","interactions":[],"lastModifiedDate":"2017-10-12T19:59:47","indexId":"sir20155184","displayToPublicDate":"2016-02-19T09:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5184","title":"Regression equations to estimate seasonal flow duration, n-day high-flow frequency, and n-day low-flow frequency at sites in North Dakota using data through water year 2009","docAbstract":"

Seasonal mean daily flow data from 119 U.S. Geological Survey streamflow-gaging stations in North Dakota; the surrounding states of Montana, Minnesota, and South Dakota; and the Canadian provinces of Manitoba and Saskatchewan with 10 or more years of unregulated flow record were used to develop regression equations for flow duration, n-day high flow and n-day low flow using ordinary least-squares and Tobit regression techniques. Regression equations were developed for seasonal flow durations at the 10th, 25th, 50th, 75th, and 90th percent exceedances; the 1-, 7-, and 30-day seasonal mean high flows for the 10-, 25-, and 50-year recurrence intervals; and the 1-, 7-, and 30-day seasonal mean low flows for the 2-, 5-, and 10-year recurrence intervals. Basin and climatic characteristics determined to be significant explanatory variables in one or more regression equations included drainage area, percentage of basin drainage area that drains to isolated lakes and ponds, ruggedness number, stream length, basin compactness ratio, minimum basin elevation, precipitation, slope ratio, stream slope, and soil permeability. The adjusted coefficient of determination for the n-day high-flow regression equations ranged from 55.87 to 94.53 percent. The Chi2 values for the duration regression equations ranged from 13.49 to 117.94, whereas the Chi2 values for the n-day low-flow regression equations ranged from 4.20 to 49.68.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155184","collaboration":"Prepared in cooperation with the North Dakota State Water Commission, North Dakota Department of Transportation, North Dakota Department of Health, Red River Joint Water Resources Board, and Devils Lake Basin Joint Water Resource Board","usgsCitation":"Williams-Sether, Tara, and Gross, T.A., 2016, Regression equations to estimate seasonal flow duration, n-day high-flow frequency, and n-day low-flow frequency at sites in North Dakota using data through water year 2009: U.S. Geological Survey Scientific Investigations Report 2015–5184, 12 p., https://dx.doi.org/10.3133/sir20155184.","productDescription":"Report: iv, 12 p.; 1 Table","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069878","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":316691,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5184/sir20155184_table1.xlsx","text":"Table 1","size":"72.0 kb","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5184 Table 1"},{"id":316670,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5184/sir20155184.pdf","text":"Report","size":"3.85 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5184"},{"id":316669,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5184/coverthb.jpg"}],"country":"Canada, United States","state":"Manitoba, Minnesota, Montana, North Dakota, Saskatchewan, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.31591796875,\n 49.63917719651036\n ],\n [\n -101.854248046875,\n 49.94415035164548\n ],\n [\n -103.128662109375,\n 50.21206446065373\n ],\n [\n -104.359130859375,\n 50.240178884797025\n ],\n [\n -105.13916015625,\n 49.90171121726089\n ],\n [\n -105.3369140625,\n 48.64016871811908\n ],\n [\n -105.567626953125,\n 47.39834920035926\n ],\n [\n -105.27099609375,\n 46.59661864884465\n ],\n [\n -105.128173828125,\n 45.71385093029221\n ],\n [\n -105.46875,\n 44.574817404670306\n ],\n [\n -103.9306640625,\n 44.62175409623324\n ],\n [\n -103.524169921875,\n 45.54483149242463\n ],\n [\n -102.513427734375,\n 45.43700828867389\n ],\n [\n -101.019287109375,\n 45.205263456162385\n ],\n [\n -99.635009765625,\n 44.98811302615805\n ],\n [\n -98.668212890625,\n 45.0502402697946\n ],\n [\n -97.85522460937499,\n 44.89479576469787\n ],\n [\n -96.339111328125,\n 44.56699093657141\n ],\n [\n -95.185546875,\n 44.91813929958515\n ],\n [\n -95.987548828125,\n 45.95878764035642\n ],\n [\n -95.701904296875,\n 47.03269459852135\n ],\n [\n -95.767822265625,\n 47.82053186746053\n ],\n [\n -96.0205078125,\n 48.62564740882851\n ],\n [\n -96.427001953125,\n 49.24629332459796\n ],\n [\n -96.99829101562499,\n 49.986552130506176\n ],\n [\n -97.5146484375,\n 49.66762782262192\n ],\n [\n -97.97607421875,\n 49.50380954152213\n ],\n [\n -98.6572265625,\n 49.75997752330658\n ],\n [\n -99.29443359375,\n 49.61070993807422\n ],\n [\n -100.008544921875,\n 49.489538473066474\n ],\n [\n -100.34912109375,\n 49.36806633482156\n ],\n [\n -101.31591796875,\n 49.63917719651036\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, USGS North Dakota Water Science Center
821 East Interstate Avenue
Bismarck, North Dakota 58503

http://nd.water.usgs.gov/

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-02-09","noUsgsAuthors":false,"publicationDate":"2016-02-09","publicationStatus":"PW","scienceBaseUri":"56c83ca8e4b0b3c9ae37b200","contributors":{"authors":[{"text":"Williams-Sether, Tara 0000-0001-6515-9416 tjsether@usgs.gov","orcid":"https://orcid.org/0000-0001-6515-9416","contributorId":152247,"corporation":false,"usgs":true,"family":"Williams-Sether","given":"Tara","email":"tjsether@usgs.gov","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":588641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gross, Tara A.","contributorId":85308,"corporation":false,"usgs":true,"family":"Gross","given":"Tara A.","affiliations":[],"preferred":false,"id":597580,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168751,"text":"70168751 - 2016 - Experimental studies and model analysis of noble gas fractionation in porous media","interactions":[],"lastModifiedDate":"2018-08-09T12:26:25","indexId":"70168751","displayToPublicDate":"2016-02-19T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Experimental studies and model analysis of noble gas fractionation in porous media","docAbstract":"

The noble gases, which are chemically inert under normal terrestrial conditions but vary systematically across a wide range of atomic mass and diffusivity, offer a multicomponent approach to investigating gas dynamics in unsaturated soil horizons, including transfer of gas between saturated zones, unsaturated zones, and the atmosphere. To evaluate the degree to which fractionation of noble gases in the presence of an advective–diffusive flux agrees with existing theory, a simple laboratory sand column experiment was conducted. Pure CO2 was injected at the base of the column, providing a series of constant CO2 fluxes through the column. At five fixed sampling depths within the system, samples were collected for CO2 and noble gas analyses, and ambient pressures were measured. Both the advection–diffusion and dusty gas models were used to simulate the behavior of CO2 and noble gases under the experimental conditions, and the simulations were compared with the measured depth-dependent concentration profiles of the gases. Given the relatively high permeability of the sand column (5 ´ 10−11 m2), Knudsen diffusion terms were small, and both the dusty gas model and the advection–diffusion model accurately predicted the concentration profiles of the CO2 and atmospheric noble gases across a range of CO2 flux from ?700 to 10,000 g m−2 d−1. The agreement between predicted and measured gas concentrations demonstrated that, when applied to natural systems, the multi-component capability provided by the noble gases can be exploited to constrain component and total gas fluxes of non-conserved (CO2) and conserved (noble gas) species or attributes of the soil column relevant to gas transport, such as porosity, tortuosity, and gas saturation.

","language":"English","publisher":"Soil Science Society of America","doi":"10.2136/vzj2015.06.0095","usgsCitation":"Ding, X., Kennedy, B.M., Evans, W.C., and Stonestrom, D.A., 2016, Experimental studies and model analysis of noble gas fractionation in porous media: Vadose Zone Journal, v. 15, no. 2, p. 1-12, https://doi.org/10.2136/vzj2015.06.0095.","productDescription":"13 p.","startPage":"1","endPage":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066461","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471219,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2136/vzj2015.06.0095","text":"Publisher Index Page"},{"id":318477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-19","publicationStatus":"PW","scienceBaseUri":"56d6cb5de4b015c306f32cef","contributors":{"authors":[{"text":"Ding, Xin","contributorId":167275,"corporation":false,"usgs":false,"family":"Ding","given":"Xin","email":"","affiliations":[{"id":6670,"text":"Lawrence Berkeley National Laboratory, Berkeley, CA","active":true,"usgs":false}],"preferred":false,"id":621640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, B. Mack.","contributorId":167276,"corporation":false,"usgs":false,"family":"Kennedy","given":"B.","email":"","middleInitial":"Mack.","affiliations":[{"id":6670,"text":"Lawrence Berkeley National Laboratory, Berkeley, CA","active":true,"usgs":false}],"preferred":false,"id":621641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evans, William C. 0000-0001-5942-3102 wcevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5942-3102","contributorId":2353,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"wcevans@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":621642,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stonestrom, David A. 0000-0001-7883-3385 dastones@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-3385","contributorId":2280,"corporation":false,"usgs":true,"family":"Stonestrom","given":"David","email":"dastones@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":621639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168641,"text":"70168641 - 2016 - Structured heterogeneity in a marine terrace chronosequence: Upland mottling","interactions":[],"lastModifiedDate":"2016-02-22T13:48:55","indexId":"70168641","displayToPublicDate":"2016-02-19T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Structured heterogeneity in a marine terrace chronosequence: Upland mottling","docAbstract":"

Soil mottles generally are interpreted as a product of reducing conditions during periods of water saturation. The upland soils of the Santa Cruz, CA, marine terrace chronosequence display an evolving sequence of reticulate mottling from the youngest soil (65 ka) without mottles to the oldest soil (225 ka) with well-developed mottles. The mottles consist of an interconnected network of clay and C-enriched regions (gray, 2.5Y 6/1) bordered by leached parent material (white, 2.5Y 8/1) within a diminishing matrix of oxidized parent material (orange, 7.5YR 5/8). The mottles develop in soils that formed from relatively uniform nearshore sediments and occur below the depth of soil bioturbation. To explore how a presumably wetland feature occurs in an unsaturated upland soil, physical and chemical characteristics of mottle separates (orange, gray, and white) were compared through the deep time represented by the soil chronosequence. Mineralogical, isotopic, and surface-area differences among mottle separates indicate that rhizogenic centimeter-scale mass transfer acting across millennia is an integral part of weathering, pedogenesis, and C and nutrient transfer. Elemental analysis, electron microscopy, and Fe-isotope systematics indicate that mottle development is driven by deep roots together with their fungal and microbial symbionts. Taken together, these data suggest that deep soil horizons on old stable landforms can develop reticulate mottling as the long-term imprint of rhizospheric processes. The processes of rhizogenic mottle formation appear to regulate pedogenesis, nutrients, and C sequestration at depth in unsaturated zones.

","language":"English","publisher":"Soil Science Society of America","publisherLocation":"Madison, WI","doi":"10.2136/vzj2015.07.0102","usgsCitation":"Schulz, M., Stonestrom, D.A., Lawrence, C.R., Bullen, T.D., Fitzpatrick, J., Kyker-Snowman, E., Manning, J., and Mnich, M., 2016, Structured heterogeneity in a marine terrace chronosequence: Upland mottling: Vadose Zone Journal, v. 15, no. 2, 14 p., https://doi.org/10.2136/vzj2015.07.0102.","productDescription":"14 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066928","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471218,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2136/vzj2015.07.0102","text":"Publisher Index Page"},{"id":318284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.15,\n 36.95\n ],\n [\n -122.15,\n 37\n ],\n [\n -122.1,\n 37\n ],\n [\n -122.1,\n 36.95\n ],\n [\n -122.15,\n 36.95\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-19","publicationStatus":"PW","scienceBaseUri":"56cc4003e4b059daa47e46b5","contributors":{"authors":[{"text":"Schulz, Marjorie S. 0000-0001-5597-6447 mschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-6447","contributorId":3720,"corporation":false,"usgs":true,"family":"Schulz","given":"Marjorie S.","email":"mschulz@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - 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Western Branch","active":true,"usgs":true}],"preferred":true,"id":621147,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70168541,"text":"70168541 - 2016 - Bivalve grazing can shape phytoplankton communities","interactions":[],"lastModifiedDate":"2017-10-30T09:49:38","indexId":"70168541","displayToPublicDate":"2016-02-18T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Bivalve grazing can shape phytoplankton communities","docAbstract":"

The ability of bivalve filter feeders to limit phytoplankton biomass in shallow waters is well-documented, but the role of bivalves in shaping phytoplankton communities is not. The coupled effect of bivalve grazing at the sediment-water interface and sinking of phytoplankton cells to that bottom filtration zone could influence the relative biomass of sinking (diatoms) and non-sinking phytoplankton. Simulations with a pseudo-2D numerical model showed that benthic filter feeding can interact with sinking to alter diatom:non-diatom ratios. Cases with the smallest proportion of diatom biomass were those with the fastest sinking speeds and strongest bivalve grazing rates. Hydrodynamics modulated the coupled sinking-grazing influence on phytoplankton communities. For example, in simulations with persistent stratification, the non-sinking forms accumulated in the surface layer away from bottom grazers while the sinking forms dropped out of the surface layer toward bottom grazers. Tidal-scale stratification also influenced vertical gradients of the two groups in opposite ways. The model was applied to Suisun Bay, a low-salinity habitat of the San Francisco Bay system that was transformed by the introduction of the exotic clam Potamocorbula amurensis. Simulation results for this Bay were similar to (but more muted than) those for generic habitats, indicating that P. amurensis grazing could have caused a disproportionate loss of diatoms after its introduction. Our model simulations suggest bivalve grazing affects both phytoplankton biomass and community composition in shallow waters. We view these results as hypotheses to be tested with experiments and more complex modeling approaches.

","language":"English","publisher":"Frontiers Research Foundation","publisherLocation":"Lausanne, Switzerland","doi":"10.3389/fmars.2016.00014","usgsCitation":"Lucas, L., Cloern, J.E., Thompson, J.K., Stacey, M., and Koseff, J., 2016, Bivalve grazing can shape phytoplankton communities: Frontiers in Marine Science, v. 3, Article 14; 17 p., https://doi.org/10.3389/fmars.2016.00014.","productDescription":"Article 14; 17 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069327","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":471221,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2016.00014","text":"Publisher Index Page"},{"id":318171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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jthompso@usgs.gov","orcid":"https://orcid.org/0000-0002-1528-8452","contributorId":1009,"corporation":false,"usgs":true,"family":"Thompson","given":"Janet","email":"jthompso@usgs.gov","middleInitial":"K.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":620814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stacey, Mark T.","contributorId":13367,"corporation":false,"usgs":true,"family":"Stacey","given":"Mark T.","affiliations":[],"preferred":false,"id":620816,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koseff, Jeffrey K.","contributorId":167033,"corporation":false,"usgs":false,"family":"Koseff","given":"Jeffrey K.","affiliations":[{"id":24597,"text":"Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, 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A previously calibrated two-dimensional hydrodynamic and water-quality model (CE-QUAL-W2) of Detroit Lake in western Oregon was used in conjunction with inflows derived from Precipitation-Runoff Modeling System (PRMS) hydrologic models to examine in-lake and downstream water temperature effects under future climate conditions. Current and hypothetical operations and structures at Detroit Dam were imposed on boundary conditions derived from downscaled General Circulation Models in base (1990–1999) and future (2059–2068) periods. Compared with the base period, future air temperatures were about 2 °C warmer year-round. Higher air temperature and lower precipitation under the future period resulted in a 23% reduction in mean annual PRMS-simulated discharge and a 1 °C increase in mean annual estimated stream temperatures flowing into the lake compared to the base period. Simulations incorporating current operational rules and minimum release rates at Detroit Dam to support downstream habitat, irrigation, and water supply during key times of year resulted in lower future lake levels. That scenario results in a lake level that is above the dam’s spillway crest only about half as many days in the future compared to historical frequencies. Managing temperature downstream of Detroit Dam depends on the ability to blend warmer water from the lake’s surface with cooler water from deep in the lake, and the spillway is an important release point near the lake’s surface. Annual average in-lake and release temperatures from Detroit Lake warmed 1.1 °C and 1.5 °C from base to future periods under present-day dam operational rules and fill schedules. Simulated dam operations such as beginning refill of the lake 30 days earlier or reducing minimum release rates (to keep more water in the lake to retain the use of the spillway) mitigated future warming to 0.4 and 0.9 °C below existing operational scenarios during the critical autumn spawning period for endangered salmonids. A hypothetical floating surface withdrawal at Detroit Dam improved temperature control in summer and autumn (0.6 °C warmer in summer, 0.6 °C cooler in autumn compared to existing structures) without altering release rates or lake level management rules.

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Spatial capture–recapture (SCR) is a relatively recent development in ecological statistics that provides a spatial context for estimating abundance and space use patterns, and improves inference about absolute population density. SCR has been applied to individual encounter data collected noninvasively using methods such as camera traps, hair snares, and scat surveys. Despite the widespread use of capture-based surveys to monitor amphibians and reptiles, there are few applications of SCR in the herpetological literature. We demonstrate the utility of the application of SCR for studies of reptiles and amphibians by analyzing capture–recapture data from Red-Backed Salamanders, Plethodon cinereus, collected using artificial cover boards. Using SCR to analyze spatial encounter histories of marked individuals, we found evidence that density differed little among four sites within the same forest (on average, 1.59 salamanders/m2) and that salamander detection probability peaked in early October (Julian day 278) reflecting expected surface activity patterns of the species. The spatial scale of detectability, a measure of space use, indicates that the home range size for this population of Red-Backed Salamanders in autumn was 16.89 m2. Surveying reptiles and amphibians using artificial cover boards regularly generates spatial encounter history data of known individuals, which can readily be analyzed using SCR methods, providing estimates of absolute density and inference about the spatial scale of habitat use.

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