{"pageNumber":"366","pageRowStart":"9125","pageSize":"25","recordCount":68867,"records":[{"id":70195067,"text":"70195067 - 2017 - Using carbon dioxide in fisheries and aquatic invasive species management","interactions":[],"lastModifiedDate":"2018-02-28T14:27:19","indexId":"70195067","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","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":"Using carbon dioxide in fisheries and aquatic invasive species management","docAbstract":"<p><span>To restore native fish populations, fisheries programs often depend on active removal of aquatic invasive species. Chemical removal can be an effective method of eliminating aquatic invasive species, but chemicals can induce mortality in nontarget organisms and persist in the environment. Carbon dioxide (CO</span><sub>2</sub><span>) is an emerging alternative to traditional chemical control agents because it has been demonstrated to be toxic to fish, but is naturally occurring and readily neutralized. In addition, CO</span><sub>2</sub><span><span>&nbsp;</span>is a commercially available gas, is highly soluble, and has high absorption efficiency. When these characteristics are paired with advances in modern, large-scale gas delivery technologies, opportunities to use CO</span><sub>2</sub><span><span>&nbsp;</span>in natural or artificial (e.g., canals) waters to manage fish become increasingly feasible. Our objective is to describe the history of CO</span><sub>2</sub><span><span>&nbsp;</span>use in fisheries and outline potential future applications of CO</span><sub>2</sub><span><span>&nbsp;</span>to suppress and manipulate aquatic species in field and aquaculture settings.</span></p>","language":"English","publisher":"Wiley","doi":"10.1080/03632415.2017.1383903","usgsCitation":"Treanor, H.B., Ray, A.M., Layhee, M., Watten, B.J., Gross, J.A., Gresswell, R.E., and Webb, M.A., 2017, Using carbon dioxide in fisheries and aquatic invasive species management: Fisheries, v. 42, no. 12, p. 621-628, https://doi.org/10.1080/03632415.2017.1383903.","productDescription":"8 p.","startPage":"621","endPage":"628","ipdsId":"IP-073368","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":438138,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U3X5XW","text":"USGS data release","linkHelpText":"Carbon dioxide-induced mortality of four species of North American fishes data"},{"id":351342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-12","publicationStatus":"PW","scienceBaseUri":"5a7d7001e4b00f54eb2441e9","contributors":{"authors":[{"text":"Treanor, Hilary B.","contributorId":200249,"corporation":false,"usgs":false,"family":"Treanor","given":"Hilary","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":726785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ray, Andrew M.","contributorId":167601,"corporation":false,"usgs":false,"family":"Ray","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":726786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Layhee, Megan J.","contributorId":201692,"corporation":false,"usgs":false,"family":"Layhee","given":"Megan J.","affiliations":[{"id":36231,"text":"Central Sierra Environmental Resource Center","active":true,"usgs":false}],"preferred":false,"id":726787,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watten, Barnaby J. 0000-0002-2227-8623 bwatten@usgs.gov","orcid":"https://orcid.org/0000-0002-2227-8623","contributorId":2002,"corporation":false,"usgs":true,"family":"Watten","given":"Barnaby","email":"bwatten@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":726788,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gross, Jason A.","contributorId":201693,"corporation":false,"usgs":false,"family":"Gross","given":"Jason","email":"","middleInitial":"A.","affiliations":[{"id":27848,"text":"Smith-Root, Inc.","active":true,"usgs":false}],"preferred":false,"id":726789,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gresswell, Robert E. 0000-0003-0063-855X bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":147914,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":726784,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Webb, Molly A. H.","contributorId":152118,"corporation":false,"usgs":false,"family":"Webb","given":"Molly","email":"","middleInitial":"A. H.","affiliations":[{"id":18870,"text":"Bozeman Fish Technology Center, U.S. Fish and Wildlife Service, Bozeman, Montana 59715","active":true,"usgs":false}],"preferred":false,"id":726790,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70196276,"text":"70196276 - 2017 - Genetic implications of bottleneck effects of differing severities on genetic diversity in naturally recovering populations: An example from Hawaiian coot and Hawaiian gallinule","interactions":[],"lastModifiedDate":"2018-03-30T10:46:58","indexId":"70196276","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Genetic implications of bottleneck effects of differing severities on genetic diversity in naturally recovering populations: An example from Hawaiian coot and Hawaiian gallinule","docAbstract":"<p><span>The evolutionary trajectory of populations through time is influenced by the interplay of forces (biological, evolutionary, and anthropogenic) acting on the standing genetic variation. We used microsatellite and mitochondrial loci to examine the influence of population declines, of varying severity, on genetic diversity within two Hawaiian endemic waterbirds, the Hawaiian coot and Hawaiian gallinule, by comparing historical (samples collected in the late 1800s and early 1900s) and modern (collected in 2012–2013) populations. Population declines simultaneously experienced by Hawaiian coots and Hawaiian gallinules differentially shaped the evolutionary trajectory of these two populations. Within Hawaiian coot, large reductions (between −38.4% and −51.4%) in mitochondrial diversity were observed, although minimal differences were observed in the distribution of allelic and haplotypic frequencies between sampled time periods. Conversely, for Hawaiian gallinule, allelic frequencies were strongly differentiated between time periods, signatures of a genetic bottleneck were detected, and biases in means of the effective population size were observed at microsatellite loci. The strength of the decline appears to have had a greater influence on genetic diversity within Hawaiian gallinule than Hawaiian coot, coincident with the reduction in census size. These species exhibit similar life history characteristics and generation times; therefore, we hypothesize that differences in behavior and colonization history are likely playing a large role in how allelic and haplotypic frequencies are being shaped through time. Furthermore, differences in patterns of genetic diversity within Hawaiian coot and Hawaiian gallinule highlight the influence of demographic and evolutionary processes in shaping how species respond genetically to ecological stressors.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3530","usgsCitation":"Sonsthagen, S.A., Wilson, R.E., and Underwood, J.G., 2017, Genetic implications of bottleneck effects of differing severities on genetic diversity in naturally recovering populations: An example from Hawaiian coot and Hawaiian gallinule: Ecology and Evolution, v. 7, no. 23, p. 9925-9934, https://doi.org/10.1002/ece3.3530.","productDescription":"10 p.","startPage":"9925","endPage":"9934","ipdsId":"IP-085014","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":469288,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3530","text":"Publisher Index Page"},{"id":352990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"23","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-20","publicationStatus":"PW","scienceBaseUri":"5afee79ee4b0da30c1bfc318","contributors":{"authors":[{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":732031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":732032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Underwood, Jared G.","contributorId":198606,"corporation":false,"usgs":false,"family":"Underwood","given":"Jared","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":732033,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70197079,"text":"70197079 - 2017 - Meeting the challenge of interacting threats in freshwater ecosystems: A call to scientists and managers","interactions":[],"lastModifiedDate":"2018-05-16T16:26:16","indexId":"70197079","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3888,"text":"Elementa: Science of the Anthropocene","active":true,"publicationSubtype":{"id":10}},"title":"Meeting the challenge of interacting threats in freshwater ecosystems: A call to scientists and managers","docAbstract":"<p><span>Human activities create threats that have consequences for freshwater ecosystems and, in most watersheds, observed ecological responses are the result of complex interactions among multiple threats and their associated ecological alterations. Here we discuss the value of considering multiple threats in research and management, offer suggestions for filling knowledge gaps, and provide guidance for addressing the urgent management challenges posed by multiple threats in freshwater ecosystems. There is a growing literature assessing responses to multiple alterations, and we build off this background to identify three areas that require greater attention: linking observed alterations to threats, understanding when and where threats overlap, and choosing metrics that best quantify the effects of multiple threats. Advancing science in these areas will help us understand existing ecosystem conditions and predict future risk from multiple threats. Because addressing the complex issues and novel ecosystems that arise from the interaction of multiple threats in freshwater ecosystems represents a significant management challenge, and the risks of management failure include loss of biodiversity, ecological goods, and ecosystem services, we also identify actions that could improve decision-making and management outcomes. These actions include drawing insights from management of individual threats, using threat attributes (e.g., causes and spatio-temporal dynamics) to identify suitable management approaches, testing management strategies that are likely to be successful despite uncertainties about the nature of interactions among threats, avoiding unintended consequences, and maximizing conservation benefits. We also acknowledge the broadly applicable challenges of decision-making within a socio-political and economic framework, and suggest that multidisciplinary teams will be needed to innovate solutions to meet the current and future challenge of interacting threats in freshwater ecosystems.</span><span class=\"Apple-converted-space\">&nbsp;</span></p>","language":"English","publisher":"University of California Press","doi":"10.1525/elementa.256","usgsCitation":"Craig, L.S., Olden, J., Arthington, A., Entrekin, S., Hawkins, C.P., Kelly, J.J., Kennedy, T., Maitland, B.M., Rosi, E.J., Roy, A.H., Strayer, D.L., Tank, J., West, A.O., and Wooten, M.S., 2017, Meeting the challenge of interacting threats in freshwater ecosystems: A call to scientists and managers: Elementa: Science of the Anthropocene, Article 72; 15 p., https://doi.org/10.1525/elementa.256.","productDescription":"Article 72; 15 p.","ipdsId":"IP-088263","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469284,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1525/elementa.256","text":"Publisher Index Page"},{"id":354229,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-06","publicationStatus":"PW","scienceBaseUri":"5afee79ce4b0da30c1bfc2f2","contributors":{"authors":[{"text":"Craig, Laura S.","contributorId":195611,"corporation":false,"usgs":false,"family":"Craig","given":"Laura","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":735545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olden, Julian D.","contributorId":66951,"corporation":false,"usgs":true,"family":"Olden","given":"Julian D.","affiliations":[],"preferred":false,"id":735546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arthington, Angela","contributorId":169474,"corporation":false,"usgs":false,"family":"Arthington","given":"Angela","affiliations":[{"id":25525,"text":"Australian Rivers Institute","active":true,"usgs":false}],"preferred":false,"id":735547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Entrekin, Sally","contributorId":147949,"corporation":false,"usgs":false,"family":"Entrekin","given":"Sally","affiliations":[{"id":16964,"text":"University of Central Arkansas","active":true,"usgs":false}],"preferred":false,"id":735548,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hawkins, Charles P.","contributorId":198331,"corporation":false,"usgs":false,"family":"Hawkins","given":"Charles","email":"","middleInitial":"P.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":735549,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelly, John J.","contributorId":204954,"corporation":false,"usgs":false,"family":"Kelly","given":"John","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":735550,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kennedy, Theodore A. tkennedy@usgs.gov","contributorId":3320,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore A.","email":"tkennedy@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":735551,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Maitland, Bryan M. bmaitland@usgs.gov","contributorId":5168,"corporation":false,"usgs":true,"family":"Maitland","given":"Bryan","email":"bmaitland@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":735552,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rosi, Emma J.","contributorId":201758,"corporation":false,"usgs":false,"family":"Rosi","given":"Emma","email":"","middleInitial":"J.","affiliations":[{"id":36248,"text":"Cary Institute of Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":735553,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":735499,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Strayer, David L.","contributorId":90682,"corporation":false,"usgs":true,"family":"Strayer","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":735554,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Tank, Jennifer L.","contributorId":103870,"corporation":false,"usgs":true,"family":"Tank","given":"Jennifer L.","affiliations":[],"preferred":false,"id":735555,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"West, Amie O.","contributorId":204955,"corporation":false,"usgs":false,"family":"West","given":"Amie","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":735556,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Wooten, Matthew S.","contributorId":204956,"corporation":false,"usgs":false,"family":"Wooten","given":"Matthew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":735557,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70197073,"text":"70197073 - 2017 - Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data","interactions":[],"lastModifiedDate":"2018-05-21T14:18:05","indexId":"70197073","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data","docAbstract":"<p><span>Predictive modeling of nested geospatial data is a challenging problem as the models must take into account potential interactions among variables defined at different spatial scales. These cross-scale interactions, as they are commonly known, are particularly important to understand relationships among ecological properties at macroscales. In this paper, we present a novel, multi-level multi-task learning framework for modeling nested geospatial data in the lake ecology domain. Specifically, we consider region-specific models to predict lake water quality from multi-scaled factors. Our framework enables distinct models to be developed for each region using both its local and regional information. The framework also allows information to be shared among the region-specific models through their common set of latent factors. Such information sharing helps to create more robust models especially for regions with limited or no training data. In addition, the framework can automatically determine cross-scale interactions between the regional variables and the local variables that are nested within them. Our experimental results show that the proposed framework outperforms all the baseline methods in at least 64% of the regions for 3 out of 4 lake water quality datasets evaluated in this study. Furthermore, the latent factors can be clustered to obtain a new set of regions that is more aligned with the response variables than the original regions that were defined a priori from the ecology domain.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2017 IEEE International Conference on Data Mining (ICDM)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"IEEE","doi":"10.1109/ICDM.2017.154","usgsCitation":"Yuan, S., Zhou, J., Tan, P., Fergus, E., Wagner, T., and Sorrano, P., 2017, Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data, <i>in</i> 2017 IEEE International Conference on Data Mining (ICDM), https://doi.org/10.1109/ICDM.2017.154.","ipdsId":"IP-084708","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":354362,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155e00e4b092d9651e1ba4","contributors":{"authors":[{"text":"Yuan, Shuai","contributorId":204925,"corporation":false,"usgs":false,"family":"Yuan","given":"Shuai","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":735482,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhou, Jiayu","contributorId":204926,"corporation":false,"usgs":false,"family":"Zhou","given":"Jiayu","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":735483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tan, Pang-Ning","contributorId":204927,"corporation":false,"usgs":false,"family":"Tan","given":"Pang-Ning","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":735484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fergus, Emi","contributorId":204928,"corporation":false,"usgs":false,"family":"Fergus","given":"Emi","email":"","affiliations":[{"id":37008,"text":"National Research Council","active":true,"usgs":false}],"preferred":false,"id":735485,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":735481,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sorrano, Patricia","contributorId":204929,"corporation":false,"usgs":false,"family":"Sorrano","given":"Patricia","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":735486,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70196469,"text":"70196469 - 2017 - LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes","interactions":[],"lastModifiedDate":"2018-04-10T10:56:16","indexId":"70196469","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5091,"text":"GigaScience","active":true,"publicationSubtype":{"id":10}},"title":"LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes","docAbstract":"<p>Understanding the factors that affect water quality and the ecological services provided by freshwater ecosystems is an urgent global environmental issue. Predicting how water quality will respond to global changes not only requires water quality data, but also information about the ecological context of individual water bodies across broad spatial extents. Because lake water quality is usually sampled in limited geographic regions, often for limited time periods, assessing the environmental controls of water quality requires compilation of many data sets across broad regions and across time into an integrated database. LAGOS-NE accomplishes this goal for lakes in the northeastern-most 17 US states.</p><p>LAGOS-NE contains data for 51 101 lakes and reservoirs larger than 4 ha in 17 lake-rich US states. The database includes 3 data modules for: lake location and physical characteristics for all lakes; ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes; and in situ measurements of lake water quality for a subset of the lakes from the past 3 decades for approximately 2600–12 000 lakes depending on the variable. The database contains approximately 150 000 measures of total phosphorus, 200 000 measures of chlorophyll, and 900 000 measures of Secchi depth. The water quality data were compiled from 87 lake water quality data sets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This database is one of the largest and most comprehensive databases of its type because it includes both in situ measurements and ecological context data. Because ecological context can be used to study a variety of other questions about lakes, streams, and wetlands, this database can also be used as the foundation for other studies of freshwaters at broad spatial and ecological scales.</p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/gigascience/gix101","usgsCitation":"Soranno, P.A., Bacon, L.C., Beauchene, M., Bednar, K.E., Bissell, E.G., Boudreau, C.K., Boyer, M.G., Bremigan, M.T., Carpenter, S.R., Carr, J.W., Cheruvelil, K.S., Christel, S.T., Claucherty, M., Collins, S.M., Conroy, J.D., Downing, J.A., Dukett, J., Fergus, C.E., Filstrup, C.T., Funk, C., Gonzalez, M.J., Green, L.T., Gries, C., Halfman, J.D., Hamilton, S.K., Hanson, P.C., Henry, E.N., Herron, E.M., Hockings, C., Jackson, J.R., Jacobson-Hedin, K., Janus, L.L., Jones, W.W., Jones, J., Keson, C.M., King, K.B., Kishbaugh, S.A., Lapierre, J., Lathrop, B., Latimore, J.A., Lee, Y., Lottig, N.R., Lynch, J.A., Matthews, L.J., McDowell, W.H., Moore, K.E., Neff, B., Nelson, S.J., Oliver, S., Pace, M.L., Pierson, D.C., Poisson, A.C., Pollard, A.I., Post, D.M., Reyes, P.O., Rosenberry, D., Roy, K.M., Rudstam, L.G., Sarnelle, O., Schuldt, N.J., Scott, C.E., Skaff, N.K., Smith, N.J., Spinelli, N.R., Stachelek, J.J., Stanley, E.H., Stoddard, J.L., Stopyak, S.B., Stow, C.A., Tallant, J.M., Tan, P., Thorpe, A.P., Vanni, M.J., Wagner, T., Watkins, G., Weathers, K.C., Webster, K.E., White, J., Wilmes, M.K., and Yuan, S., 2017, LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes: GigaScience, v. 6, no. 12, p. 1-22, https://doi.org/10.1093/gigascience/gix101.","productDescription":"22 p.","startPage":"1","endPage":"22","ipdsId":"IP-088165","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":469264,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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(Ohio)","active":true,"usgs":false}],"preferred":false,"id":733109,"contributorType":{"id":1,"text":"Authors"},"rank":73},{"text":"Wagner, Tyler","contributorId":204107,"corporation":false,"usgs":false,"family":"Wagner","given":"Tyler","affiliations":[{"id":36847,"text":"Pennsylvania Cooperative Fish and Wildlife Research Institute, Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":733110,"contributorType":{"id":1,"text":"Authors"},"rank":74},{"text":"Watkins, Gretchen","contributorId":204108,"corporation":false,"usgs":false,"family":"Watkins","given":"Gretchen","email":"","affiliations":[{"id":36818,"text":"Water Resources Program, Lac du Flambeau Tribal Natural Resources","active":true,"usgs":false}],"preferred":false,"id":733111,"contributorType":{"id":1,"text":"Authors"},"rank":75},{"text":"Weathers, Kathleen 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K.","contributorId":204110,"corporation":false,"usgs":false,"family":"Wilmes","given":"Marcy","email":"","middleInitial":"K.","affiliations":[{"id":36849,"text":"Department of Environmental Quality, State of Michigan","active":true,"usgs":false}],"preferred":false,"id":733115,"contributorType":{"id":1,"text":"Authors"},"rank":79},{"text":"Yuan, Shuai","contributorId":172187,"corporation":false,"usgs":false,"family":"Yuan","given":"Shuai","affiliations":[],"preferred":false,"id":733116,"contributorType":{"id":1,"text":"Authors"},"rank":80}]}}
,{"id":70195756,"text":"70195756 - 2017 - Effects of thermal variability on broadband seismometers: Controlled experiments, observations, and implications","interactions":[],"lastModifiedDate":"2018-07-03T11:34:14","indexId":"70195756","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Effects of thermal variability on broadband seismometers: Controlled experiments, observations, and implications","docAbstract":"<p><span>Isolating seismic instruments from temperature fluctuations is routine practice within the seismological community. However, the necessary degree of thermal stability required in broadband installations to avoid generating noise or compromising the fidelity in the seismic records is largely unknown and likely application dependent. To quantify the temperature sensitivity of seismometers over a broad range of frequencies, we artificially induced local temperature changes on three different models of seismometers to measure the effect of thermal variations on seismometer output. We found that diurnal temperature changes above 0.002°C root mean square (rms) showed significant changes in velocity and acceleration output in comparison to thermally stable reference measurements. We also found that sensor incoherent self‐noise increased with temperature variation; these increases in noise can be modeled as&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mn xmlns=&quot;&quot;>1</mn><mo xmlns=&quot;&quot;>/</mo><mi xmlns=&quot;&quot;>f</mi></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"mn\">1</span><span id=\"MathJax-Span-4\" class=\"mo\">/</span><span id=\"MathJax-Span-5\" class=\"mi\">f</span></span></span></span></span></span></span><span><span>&nbsp;</span>noise (pink noise), and are unlikely to be easily corrected for. These experimental results are compared with the data from Incorporated Research Institutions for Seismology (IRIS) U.S. Geological Survey (USGS) Global Seismographic Network (GSN) station TUC (Tucson, Arizona). This station is well instrumented with temperature sensors and has three different broadband seismometers, each of which uses a different method of thermal isolation. We show that the water bricks and borehole installations give ample temperature attenuation to thermally isolate seismometers from diurnal thermal variability that would compromise seismic data. We find that seismometer installations that provide thermal stability below 0.002°C rms could help to improve long‐period vertical seismic data across the GSN by decreasing temperature‐driven<span>&nbsp;</span></span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mn xmlns=&quot;&quot;>1</mn><mo xmlns=&quot;&quot;>/</mo><mi xmlns=&quot;&quot;>f</mi></math>\"><span id=\"MathJax-Span-6\" class=\"math\"><span><span><span id=\"MathJax-Span-7\" class=\"mrow\"><span id=\"MathJax-Span-8\" class=\"mn\">1</span><span id=\"MathJax-Span-9\" class=\"mo\">/</span><span id=\"MathJax-Span-10\" class=\"mi\">f</span></span></span></span></span></span></span><span><span>&nbsp;</span>noise.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170233","usgsCitation":"Doody, C., Ringler, A.T., Anthony, R.E., Wilson, D.C., Holland, A., Hutt, C.R., and Sandoval, L., 2017, Effects of thermal variability on broadband seismometers: Controlled experiments, observations, and implications: Bulletin of the Seismological Society of America, v. 108, no. 1, p. 493-502, https://doi.org/10.1785/0120170233.","productDescription":"10 p.","startPage":"493","endPage":"502","ipdsId":"IP-091363","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":352146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"108","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-26","publicationStatus":"PW","scienceBaseUri":"5afee7aae4b0da30c1bfc333","contributors":{"authors":[{"text":"Doody, Claire","contributorId":202828,"corporation":false,"usgs":false,"family":"Doody","given":"Claire","email":"","affiliations":[],"preferred":false,"id":729802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":729803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":729804,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":729805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holland, Austin 0000-0002-7843-1981 aaholland@usgs.gov","orcid":"https://orcid.org/0000-0002-7843-1981","contributorId":173969,"corporation":false,"usgs":true,"family":"Holland","given":"Austin","email":"aaholland@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":729806,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hutt, Charles R. 0000-0001-9033-9195 bhutt@usgs.gov","orcid":"https://orcid.org/0000-0001-9033-9195","contributorId":1622,"corporation":false,"usgs":true,"family":"Hutt","given":"Charles","email":"bhutt@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":729807,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sandoval, Leo lsandoval@usgs.gov","contributorId":202830,"corporation":false,"usgs":true,"family":"Sandoval","given":"Leo","email":"lsandoval@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":729808,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70197056,"text":"70197056 - 2017 - Walleye age estimation using otoliths and dorsal spines: Preparation techniques and sampling guidelines based on sex and total length","interactions":[],"lastModifiedDate":"2018-05-17T14:21:53","indexId":"70197056","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Walleye age estimation using otoliths and dorsal spines: Preparation techniques and sampling guidelines based on sex and total length","docAbstract":"<p><span>We used dorsal spines and otoliths from 735 Walleye&nbsp;</span><i>Sander vitreus</i><span><span>&nbsp;</span>collected from 35 Wisconsin water bodies to evaluate whether 1) otolith and dorsal spine cross sections provided age estimates similar to simpler methods of preparation (e.g., whole otoliths and dorsal spines, cracked otoliths); and 2) between-reader precision and differences between spine and otolith ages varied in relation to total length (TL), sex, and growth rate. Ages estimated from structures prepared using simpler techniques were generally similar to ages estimated using thin sections of dorsal spines and otoliths, suggesting that, in some instances, much of the additional processing time and specialized equipment associated with thin sectioning could be avoided. Overall, between-reader precision was higher for sectioned otoliths (mean coefficient of variation [CV] = 3.28%; standard error [SE] = 0.33%) than for sectioned dorsal spines (mean CV = 9.20%; SE = 0.56%). When using sectioned otoliths for age assignment, between-reader precision did not vary between sexes or growth categories (i.e., fast, moderate, slow), but between-reader precision was higher for females than males when using sectioned dorsal spines. Dorsal spines were generally effective at replicating otolith ages for male Walleye &lt;450 mm TL and female Walleye &lt;600 mm TL, suggesting that dorsal spines can be used to estimate ages for male Walleye &lt;450 mm TL and female Walleye &lt;600 mm TL. If sex is unknown, we suggest dorsal spines be used to estimate ages for Walleye &lt;450 mm TL, but that otoliths be used for fish &gt;450 mm TL. Our results provide useful guidance on structure and preparation technique selection for Walleye age estimation, thereby allowing biologists to develop sampling guidelines that could be implemented using information that is always (TL) or often (sex) available at the time of fish collection.</span></p>","language":"English","publisher":"Scientific Journals","doi":"10.3996/052017-JFWM-038","usgsCitation":"Dembkowski, D., Isermann, D.A., and Koenigs, R.P., 2017, Walleye age estimation using otoliths and dorsal spines: Preparation techniques and sampling guidelines based on sex and total length: Journal of Fish and Wildlife Management, v. 8, no. 2, p. 474-486, https://doi.org/10.3996/052017-JFWM-038.","productDescription":"13 p.","startPage":"474","endPage":"486","ipdsId":"IP-082128","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":487229,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/052017-jfwm-038","text":"Publisher Index Page"},{"id":354272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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P.","contributorId":191473,"corporation":false,"usgs":false,"family":"Koenigs","given":"Ryan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":735699,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194514,"text":"70194514 - 2017 - Mineralogical characterization of weathered outcrops as a tool for constraining water chemistry predictions during project planning","interactions":[],"lastModifiedDate":"2017-12-06T10:45:16","indexId":"70194514","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Mineralogical characterization of weathered outcrops as a tool for constraining water chemistry predictions during project planning","docAbstract":"Weathered samples from naturally exposed outcrops of troctolite associated with a magmatic\nNi-Cu sulphide deposit were characterized by synchrotron-based micro-X-ray fluorescence mapping\n(µ-XRF) and X-ray absorption spectroscopy (XAS), as well as by lab-based X-ray diffraction, electron\nmicroscopy, Raman spectroscopy and wet chemical methods. Metal mobility in weathered samples\nwas assessed using a sequential leach procedure. Results are interpreted in the context of predictions\nfor future mine water chemistry and used to refine the conceptual model for metal mobility following\nweathering of waste rock at a potential future mine site.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of IMWA 2017","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"International Mine Water Association","usgsCitation":"Diedrich, T., Fix, P., and Foster, A.L., 2017, Mineralogical characterization of weathered outcrops as a tool for constraining water chemistry predictions during project planning, <i>in</i> Proceedings of IMWA 2017, p. 712-719.","productDescription":"8 p.","startPage":"712","endPage":"719","ipdsId":"IP-083887","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":349749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349605,"type":{"id":15,"text":"Index Page"},"url":"https://imwa.info/imwaconferencesandcongresses/proceedings/300-proceedings-2017.html"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf8e4b06e28e9c22a34","contributors":{"authors":[{"text":"Diedrich, Tamara","contributorId":201055,"corporation":false,"usgs":false,"family":"Diedrich","given":"Tamara","email":"","affiliations":[],"preferred":false,"id":724214,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fix, Paul","contributorId":201056,"corporation":false,"usgs":false,"family":"Fix","given":"Paul","email":"","affiliations":[],"preferred":false,"id":724215,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foster, Andrea L. 0000-0003-1362-0068 afoster@usgs.gov","orcid":"https://orcid.org/0000-0003-1362-0068","contributorId":1740,"corporation":false,"usgs":true,"family":"Foster","given":"Andrea","email":"afoster@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724213,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194508,"text":"70194508 - 2017 - Quantifying animal movement for caching foragers: the path identification index (PII) and cougars, Puma concolor","interactions":[],"lastModifiedDate":"2017-12-01T11:54:14","indexId":"70194508","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Quantifying animal movement for caching foragers: the path identification index (PII) and cougars, <i>Puma concolor</i>","title":"Quantifying animal movement for caching foragers: the path identification index (PII) and cougars, Puma concolor","docAbstract":"Relocation studies of animal movement have focused on directed versus area restricted movement, which rely on correlations between step-length and turn angles, along with a degree of stationarity through time to define behavioral states.  Although these approaches may work well for grazing foraging strategies in a patchy landscape, species that do not spend a significant amount of time searching out and gathering small dispersed food items, but instead feed for short periods on large, concentrated sources or cache food result in movements that maybe difficult to analyze using turning and velocity alone.  We use GPS telemetry collected from a prey-caching predator, the cougar (Puma concolor), to test whether adding additional movement metrics capturing site recursion, to the more traditional velocity and turning, improve the ability to identify behaviors.  We evaluated our movement index’s ability to identify behaviors using field investigations.  We further tested for statistical stationarity across behaviors for use of topographic view-sheds.  We found little correlation between turn angle, velocity, tortuosity, and site fidelity and combined them into a movement index used to identify movement paths (temporally autocorrelated movements) related to fast directed movements (taxis), area restricted movements (search), and prey caching (foraging).  Changes in the frequency and duration of these movements were helpful for identifying seasonal activities such as migration and denning in females.   Comparison of field investigations of cougar activities to behavioral classes defined using the movement index and found an overall classification accuracy of 81%.  Changes in behaviors resulted in changes in how cougars used topographic view-sheds, showing statistical non-stationarity over time.   The movement index shows promise for identifying behaviors in species that frequently return to specific locations such as food caches, watering holes, or dens, and highlights the role memory and cognitive abilities may play in determining animal movements.  With the addition of measures capturing site recursion the temporal structure in movements of a caching forager was revealed.","language":"English","publisher":"BioMed Central","doi":"10.1186/s40462-017-0115-z","usgsCitation":"Ironside, K.E., Mattson, D.J., Theimer, T., Jansen, B., Holton, B., Arundel, T.R., Peters, M., Sexton, J.O., and Edwards, T., 2017, Quantifying animal movement for caching foragers: the path identification index (PII) and cougars, Puma concolor: Movement Ecology, v. 5, p. 1-17, https://doi.org/10.1186/s40462-017-0115-z.","productDescription":"Article 24; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-071574","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469273,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-017-0115-z","text":"Publisher Index Page"},{"id":438141,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A93HRF","text":"USGS data release","linkHelpText":"Puma concolor GPS Telemetry and Path Identification Index (2003-2013), Southwest Region, USA"},{"id":349627,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-23","publicationStatus":"PW","scienceBaseUri":"5a60faf8e4b06e28e9c22a3b","contributors":{"authors":[{"text":"Ironside, Kirsten E. 0000-0003-1166-3793 kironside@usgs.gov","orcid":"https://orcid.org/0000-0003-1166-3793","contributorId":3379,"corporation":false,"usgs":true,"family":"Ironside","given":"Kirsten","email":"kironside@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":724176,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mattson, David J.","contributorId":191920,"corporation":false,"usgs":false,"family":"Mattson","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":724177,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Theimer, Tad","contributorId":191914,"corporation":false,"usgs":false,"family":"Theimer","given":"Tad","affiliations":[],"preferred":false,"id":724178,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jansen, Brian","contributorId":191917,"corporation":false,"usgs":false,"family":"Jansen","given":"Brian","email":"","affiliations":[],"preferred":false,"id":724179,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holton, Brandon","contributorId":191915,"corporation":false,"usgs":false,"family":"Holton","given":"Brandon","affiliations":[],"preferred":false,"id":724180,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arundel, Terence R. 0000-0003-0324-4249 tarundel@usgs.gov","orcid":"https://orcid.org/0000-0003-0324-4249","contributorId":139242,"corporation":false,"usgs":true,"family":"Arundel","given":"Terence","email":"tarundel@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":724181,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peters, Michael","contributorId":191919,"corporation":false,"usgs":false,"family":"Peters","given":"Michael","email":"","affiliations":[],"preferred":false,"id":724182,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sexton, Joseph O.","contributorId":191918,"corporation":false,"usgs":false,"family":"Sexton","given":"Joseph","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":724265,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Edwards, Thomas C. Jr. 0000-0002-0773-0909 tce@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-0909","contributorId":191916,"corporation":false,"usgs":true,"family":"Edwards","given":"Thomas C.","suffix":"Jr.","email":"tce@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":724183,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70191922,"text":"70191922 - 2017 - CO2 cycle","interactions":[],"lastModifiedDate":"2017-12-18T11:13:13","indexId":"70191922","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"displayTitle":"CO<sub>2</sub> cycle","title":"CO2 cycle","docAbstract":"This chapter discusses the use of models, observations, and laboratory experiments to understand the cycling of CO2 between the atmosphere and seasonal Martian polar caps. This cycle is primarily controlled by the polar heat budget, and thus the emphasis here is on its components, including solar and infrared radiation, the effect of clouds (water- and CO2-ice), atmospheric transport, and subsurface heat conduction. There is a discussion about cap properties including growth and regression rates, albedos and emissivities, grain sizes and dust and/or water-ice contamination, and curious features like cold gas jets and araneiform (spider-shaped) terrain. The nature of the residual south polar cap is discussed as well as its long-term stability and ability to buffer atmospheric pressures. There is also a discussion of the consequences of the CO2 cycle as revealed by the non-condensable gas enrichment observed by Odyssey and modeled by various groups.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The atmosphere and climate of Mars","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Cambridge University Press","doi":"10.1017/9781139060172.012","usgsCitation":"Titus, T.N., Byrne, S., Colaprete, A., Forget, F., Michaels, T.I., and Prettyman, T.H., 2017, CO2 cycle, chap. <i>of</i> The atmosphere and climate of Mars, p. 374-404, https://doi.org/10.1017/9781139060172.012.","productDescription":"31 p.","startPage":"374","endPage":"404","ipdsId":"IP-050666","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":350068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf9e4b06e28e9c22a61","contributors":{"authors":[{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":713710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrne, Shane","contributorId":192609,"corporation":false,"usgs":false,"family":"Byrne","given":"Shane","email":"","affiliations":[],"preferred":false,"id":713711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colaprete, Anthony","contributorId":197548,"corporation":false,"usgs":false,"family":"Colaprete","given":"Anthony","email":"","affiliations":[],"preferred":false,"id":713712,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forget, Francois","contributorId":197549,"corporation":false,"usgs":false,"family":"Forget","given":"Francois","email":"","affiliations":[],"preferred":false,"id":713713,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Michaels, Timothy I.","contributorId":197550,"corporation":false,"usgs":false,"family":"Michaels","given":"Timothy","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":713714,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prettyman, Thomas H.","contributorId":197551,"corporation":false,"usgs":false,"family":"Prettyman","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":713715,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70191867,"text":"70191867 - 2017 - Energetic requirements of green sturgeon (Acipenser medirostris) feeding on burrowing shrimp (Neotrypaea californiensis) in estuaries: importance of temperature, reproductive investment, and residence time","interactions":[],"lastModifiedDate":"2018-03-29T13:31:29","indexId":"70191867","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Energetic requirements of green sturgeon (<i>Acipenser medirostris</i>) feeding on burrowing shrimp (<i>Neotrypaea californiensis</i>) in estuaries: importance of temperature, reproductive investment, and residence time","title":"Energetic requirements of green sturgeon (Acipenser medirostris) feeding on burrowing shrimp (Neotrypaea californiensis) in estuaries: importance of temperature, reproductive investment, and residence time","docAbstract":"<p><span>Habitat use can be complex, as tradeoffs among physiology, resource abundance, and predator avoidance affect the suitability of different environments for different species. Green sturgeon (</span><i class=\"EmphasisTypeItalic \">Acipenser medirostris</i><span>), an imperiled species along the west coast of North America, undertake extensive coastal migrations and occupy estuaries during the summer and early fall. Warm water and abundant prey in estuaries may afford a growth opportunity. We applied a bioenergetics model to investigate how variation in estuarine temperature, spawning frequency, and duration of estuarine residence affect consumption and growth potential for individual green sturgeon. We assumed that green sturgeon achieve observed annual growth by feeding solely in conditions represented by Willapa Bay, Washington, an estuary annually frequented by green sturgeon and containing extensive tidal flats that harbor a major prey source (burrowing shrimp,<span>&nbsp;</span></span><i class=\"EmphasisTypeItalic \">Neotrypaea californiensis</i><span>). Modeled consumption rates increased little with reproductive investment (&lt;0.4%), but responded strongly (10–50%) to water temperature and duration of residence, as higher temperatures and longer residence required greater consumption to achieve equivalent growth. Accordingly, although green sturgeon occupy Willapa Bay from May through September, acoustically-tagged individuals are observed over much shorter durations (34 d&nbsp;+&nbsp;41 d SD,<span>&nbsp;</span></span><i class=\"EmphasisTypeItalic \">N</i><span>&nbsp;=&nbsp;89). Simulations of &lt;34 d estuarine residence required unrealistically high consumption rates to achieve observed growth, whereas longer durations required sustained feeding, and therefore higher total intake, to compensate for prolonged exposure to warm temperatures. Model results provide a range of per capita consumption rates by green sturgeon feeding in estuaries to inform management decisions regarding resource and habitat protection for this protected species.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10641-017-0665-3","usgsCitation":"Borin, J.M., Moser, M.L., Hansen, A.G., Beauchamp, D.A., Corbett, S.C., Dumbauld, B.R., Pruitt, C., Ruesink, J.L., and Donoghue, C., 2017, Energetic requirements of green sturgeon (Acipenser medirostris) feeding on burrowing shrimp (Neotrypaea californiensis) in estuaries: importance of temperature, reproductive investment, and residence time: Environmental Biology of Fishes, v. 100, no. 12, p. 1561-1573, https://doi.org/10.1007/s10641-017-0665-3.","productDescription":"13 p.","startPage":"1561","endPage":"1573","ipdsId":"IP-087984","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":488604,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10641-017-0665-3","text":"Publisher Index Page"},{"id":352947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-21","publicationStatus":"PW","scienceBaseUri":"5afee7abe4b0da30c1bfc353","contributors":{"authors":[{"text":"Borin, Joshua M.","contributorId":197414,"corporation":false,"usgs":false,"family":"Borin","given":"Joshua","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":713458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moser, Mary L.","contributorId":195100,"corporation":false,"usgs":false,"family":"Moser","given":"Mary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":713459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Adam G.","contributorId":197415,"corporation":false,"usgs":false,"family":"Hansen","given":"Adam","email":"","middleInitial":"G.","affiliations":[{"id":34919,"text":"Colorado Parks and Wildlife, 317 West Prospect Road, Fort Collins, Colorado 80526, USA","active":true,"usgs":false}],"preferred":false,"id":713460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beauchamp, David A. 0000-0002-3592-8381 fadave@usgs.gov","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":4205,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","email":"fadave@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":713457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corbett, Stephen C.","contributorId":197416,"corporation":false,"usgs":false,"family":"Corbett","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":713461,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dumbauld, Brett R.","contributorId":197417,"corporation":false,"usgs":false,"family":"Dumbauld","given":"Brett","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":713462,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pruitt, Casey","contributorId":197418,"corporation":false,"usgs":false,"family":"Pruitt","given":"Casey","email":"","affiliations":[],"preferred":false,"id":713463,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ruesink, Jennifer L.","contributorId":197419,"corporation":false,"usgs":false,"family":"Ruesink","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":713464,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Donoghue, Cinde","contributorId":197420,"corporation":false,"usgs":false,"family":"Donoghue","given":"Cinde","email":"","affiliations":[],"preferred":false,"id":713465,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70191050,"text":"70191050 - 2017 - Vulnerability of coral reefs to bioerosion from land-based sources of pollution","interactions":[],"lastModifiedDate":"2022-11-14T16:57:56.217623","indexId":"70191050","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Vulnerability of coral reefs to bioerosion from land-based sources of pollution","docAbstract":"<p><span>Ocean acidification (OA), the gradual decline in ocean pH and [&nbsp;</span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017JC013264/asset/equation/jgrc22505-math-0001.png?v=1&amp;s=072cd767753a34f47b463713a2956f9820b549ae\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017JC013264/asset/equation/jgrc22505-math-0001.png?v=1&amp;s=072cd767753a34f47b463713a2956f9820b549ae\"></span></span><span>] caused by rising levels of atmospheric CO</span><sub>2</sub><span>, poses a significant threat to coral reef ecosystems, depressing rates of calcium carbonate (CaCO</span><sub>3</sub><span>) production, and enhancing rates of bioerosion and dissolution. As ocean pH and [<span>&nbsp;</span></span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/2017JC013264/asset/equation/jgrc22505-math-0002.png?v=1&amp;s=8d7349d4f1044b6572dca5422a94b5c951e16126\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/2017JC013264/asset/equation/jgrc22505-math-0002.png?v=1&amp;s=8d7349d4f1044b6572dca5422a94b5c951e16126\"></span></span><span>] decline globally, there is increasing emphasis on managing local stressors that can exacerbate the vulnerability of coral reefs to the effects of OA. We show that sustained, nutrient rich, lower pH submarine groundwater discharging onto nearshore coral reefs off west Maui lowers the pH of seawater and exposes corals to nitrate concentrations 50 times higher than ambient. Rates of coral calcification are substantially decreased, and rates of bioerosion are orders of magnitude higher than those observed in coral cores collected in the Pacific under equivalent low pH conditions but living in oligotrophic waters. Heavier coral nitrogen isotope (δ</span><sup>15</sup><span>N) values pinpoint not only site-specific eutrophication, but also a sewage nitrogen source enriched in<span>&nbsp;</span></span><sup>15</sup><span>N. Our results show that eutrophication of reef seawater by land-based sources of pollution can magnify the effects of OA through nutrient driven-bioerosion. These conditions could contribute to the collapse of coastal coral reef ecosystems sooner than current projections predict based only on ocean acidification.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/2017JC013264","usgsCitation":"Prouty, N.G., Anne Cohen, Yates, K.K., Storlazzi, C.D., Swarzenski, P.W., and White, D., 2017, Vulnerability of coral reefs to bioerosion from land-based sources of pollution: Journal of Geophysical Research C: Oceans, v. 122, no. 12, p. 9319-9331, https://doi.org/10.1002/2017JC013264.","productDescription":"13 p.","startPage":"9319","endPage":"9331","ipdsId":"IP-083486","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488732,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jc013264","text":"Publisher Index Page"},{"id":349902,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -156.6944,\n              20.9361\n            ],\n            [\n              -156.6889,\n              20.9361\n            ],\n            [\n              -156.6889,\n              20.9472\n            ],\n            [\n              -156.6944,\n              20.9472\n            ],\n            [\n              -156.6944,\n              20.9361\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"122","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf9e4b06e28e9c22a67","contributors":{"authors":[{"text":"Prouty, Nancy G. 0000-0002-8922-0688 nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anne Cohen","contributorId":191409,"corporation":false,"usgs":false,"family":"Anne Cohen","affiliations":[],"preferred":false,"id":711060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yates, Kimberly K. 0000-0001-8764-0358 kyates@usgs.gov","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":420,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"kyates@usgs.gov","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711061,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":711062,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711063,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"White, Darla","contributorId":194122,"corporation":false,"usgs":false,"family":"White","given":"Darla","affiliations":[],"preferred":false,"id":711064,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70196963,"text":"70196963 - 2017 - Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, Crassostrea virginica: A meta-analysis using 40 years of monitoring data","interactions":[],"lastModifiedDate":"2018-05-15T17:03:36","indexId":"70196963","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2455,"text":"Journal of Shellfish Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, <i>Crassostrea virginica</i>: A meta-analysis using 40 years of monitoring data","title":"Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, Crassostrea virginica: A meta-analysis using 40 years of monitoring data","docAbstract":"<p><span>Despite nearly a century of exploitation and scientific study, predicting growth and mortality rates of the eastern oyster (</span><i>Crassostrea virginica</i><span>) as a means to inform local harvest and management activities remains difficult. Ensuring that models reflect local population responses to varying salinity and temperature combinations requires locally appropriate models. Using long-term (1988 to 2015) monitoring data from Louisiana's public oyster reefs, we develop regionally specific models of temperature- and salinity-driven mortality (sack oysters only) and growth for spat (&lt;25 mm), seed (25–75 mm), and sack (&gt;75 mm) oyster size classes. The results demonstrate that the optimal combination of temperature and salinity where Louisiana oysters experience reduced mortality and fast growth rates is skewed toward lower salinities and higher water temperatures than previous models have suggested. Outside of that optimal range, oysters are commonly exposed to combinations of temperature and salinity that are correlated with high mortality and reduced growth. How these combinations affect growth, and to a lesser degree mortality, appears to be size class dependent. Given current climate predictions for the region and ongoing large-scale restoration activities in coastal Louisiana, the growth and mortality models are a critical step toward ensuring sustainable oyster reefs for long-term harvest and continued delivery of the ecological services in a changing environment.</span></p>","language":"English","publisher":"National Shellfisheries Association","doi":"10.2983/035.036.0318","collaboration":"National Fish and Wildlife Foundation, Louisiana,Department of Wildlife and Fisheries, Louisiana State University","usgsCitation":"Lowe, M.R., Sehlinger, T., Soniat, T.M., and LaPeyre, M.K., 2017, Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, Crassostrea virginica: A meta-analysis using 40 years of monitoring data: Journal of Shellfish Research, v. 36, no. 3, p. 683-697, https://doi.org/10.2983/035.036.0318.","productDescription":"15 p.","startPage":"683","endPage":"697","ipdsId":"IP-088282","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94,\n              29\n            ],\n            [\n              -89,\n              29\n            ],\n            [\n              -89,\n              30.5\n            ],\n            [\n              -94,\n              30.5\n            ],\n            [\n              -94,\n              29\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee79ce4b0da30c1bfc2fa","contributors":{"authors":[{"text":"Lowe, Michael R. 0000-0002-4645-9429","orcid":"https://orcid.org/0000-0002-4645-9429","contributorId":10539,"corporation":false,"usgs":true,"family":"Lowe","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":735465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sehlinger, Troy","contributorId":204922,"corporation":false,"usgs":false,"family":"Sehlinger","given":"Troy","email":"","affiliations":[],"preferred":false,"id":735466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soniat, Thomas M.","contributorId":11109,"corporation":false,"usgs":true,"family":"Soniat","given":"Thomas","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":735467,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":735149,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196268,"text":"70196268 - 2017 - Metabarcoding of environmental DNA samples to explore the use of uranium mine containment ponds as a water source for wildlife","interactions":[],"lastModifiedDate":"2018-03-29T10:23:16","indexId":"70196268","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Metabarcoding of environmental DNA samples to explore the use of uranium mine containment ponds as a water source for wildlife","docAbstract":"<p><span>Understanding how anthropogenic impacts on the landscape affect wildlife requires a knowledge of community assemblages. Species surveys are the first step in assessing community structure, and recent molecular applications such as metabarcoding and environmental DNA analyses have been proposed as an additional and complementary wildlife survey method. Here, we test eDNA metabarcoding as a survey tool to examine the potential use of uranium mine containment ponds as water sources by wildlife. We tested samples from surface water near mines and from one mine containment pond using two markers, 12S and 16S rRNA gene amplicons, to survey for vertebrate species. We recovered large numbers of sequence reads from taxa expected to be in the area and from less common or hard to observe taxa such as the tiger salamander and gray fox. Detection of these two species is of note because they were not observed in a previous species assessment, and tiger salamander DNA was found in the mine containment pond sample. We also found that sample concentration by centrifugation was a more efficient and more feasible method than filtration in these highly turbid surface waters. Ultimately, the use of eDNA metabarcoding could allow for a better understanding of the area’s overall biodiversity and community composition as well as aid current ecotoxicological risk assessment work.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/d9040054","usgsCitation":"Klymus, K.E., Richter, C.A., Thompson, N., and Hinck, J.E., 2017, Metabarcoding of environmental DNA samples to explore the use of uranium mine containment ponds as a water source for wildlife: Diversity, v. 9, no. 4, Article 54; 18 p., https://doi.org/10.3390/d9040054.","productDescription":"Article 54; 18 p.","ipdsId":"IP-091285","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":461341,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d9040054","text":"Publisher Index Page"},{"id":438133,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QC02Q5","text":"USGS data release","linkHelpText":"eDNA sampling sites in the Grand Canyon region near breccia pipe uranium mines_2015_2016"},{"id":352922,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-21","publicationStatus":"PW","scienceBaseUri":"5afee79ee4b0da30c1bfc31a","contributors":{"authors":[{"text":"Klymus, Katy E. 0000-0002-8843-6241 kklymus@usgs.gov","orcid":"https://orcid.org/0000-0002-8843-6241","contributorId":5043,"corporation":false,"usgs":true,"family":"Klymus","given":"Katy","email":"kklymus@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":731996,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richter, Catherine A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":138994,"corporation":false,"usgs":true,"family":"Richter","given":"Catherine","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":731997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Nathan 0000-0002-1372-6340 nthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-1372-6340","contributorId":196133,"corporation":false,"usgs":true,"family":"Thompson","given":"Nathan","email":"nthompson@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":731998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hinck, Jo Ellen 0000-0002-4912-5766 jhinck@usgs.gov","orcid":"https://orcid.org/0000-0002-4912-5766","contributorId":2743,"corporation":false,"usgs":true,"family":"Hinck","given":"Jo","email":"jhinck@usgs.gov","middleInitial":"Ellen","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":731999,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70195325,"text":"70195325 - 2017 - A statistical method to predict flow permanence in dryland streams from time series of stream temperature","interactions":[],"lastModifiedDate":"2018-02-08T13:51:52","indexId":"70195325","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"A statistical method to predict flow permanence in dryland streams from time series of stream temperature","docAbstract":"<p><span>Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs), to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD) of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels) between April and August (2015–2016). We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%), but a portion of them showed one or more shifts among states (17%). We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w9120946","usgsCitation":"Arismendi, I., Dunham, J.B., Heck, M., Schultz, L., and Hockman-Wert, D., 2017, A statistical method to predict flow permanence in dryland streams from time series of stream temperature: Water, v. 9, no. 12, p. 1-13, https://doi.org/10.3390/w9120946.","productDescription":"Article 946; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-087892","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469281,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w9120946","text":"Publisher Index Page"},{"id":438137,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JQ0ZW2","text":"USGS data release","linkHelpText":"Stream temperature and drying data from Willow/Whitehorse watersheds, southeast Oregon, 2014-16, and Willow/Rock/Frazer watersheds, northern Nevada, 2015-2016"},{"id":351364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Oregon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118,\n              42\n            ],\n            [\n              -118,\n              42.33\n            ],\n            [\n              -118.33,\n              42.33\n            ],\n            [\n              -118.33,\n              42\n            ],\n            [\n              -118,\n              42\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.33,\n              41.1667\n            ],\n            [\n              -116.8333,\n              41.1667\n            ],\n            [\n              -116.8333,\n              41.4167\n            ],\n            [\n              -116.33,\n              41.4167\n            ],\n            [\n              -116.33,\n              41.1667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-05","publicationStatus":"PW","scienceBaseUri":"5a7d6ffee4b00f54eb2441c0","contributors":{"authors":[{"text":"Arismendi, Ivan 0000-0002-8774-9350","orcid":"https://orcid.org/0000-0002-8774-9350","contributorId":202207,"corporation":false,"usgs":false,"family":"Arismendi","given":"Ivan","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":727859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":727858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heck, Michael 0000-0001-8858-7325 mheck@usgs.gov","orcid":"https://orcid.org/0000-0001-8858-7325","contributorId":4796,"corporation":false,"usgs":true,"family":"Heck","given":"Michael","email":"mheck@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":727860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schultz, Luke 0000-0002-6751-4626 lschultz@usgs.gov","orcid":"https://orcid.org/0000-0002-6751-4626","contributorId":193171,"corporation":false,"usgs":true,"family":"Schultz","given":"Luke","email":"lschultz@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":727861,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hockman-Wert, David 0000-0003-2436-6237 dhockman-wert@usgs.gov","orcid":"https://orcid.org/0000-0003-2436-6237","contributorId":3891,"corporation":false,"usgs":true,"family":"Hockman-Wert","given":"David","email":"dhockman-wert@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":727862,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196791,"text":"70196791 - 2017 - Evaluating the potential for weed seed dispersal based on waterfowl consumption and seed viability","interactions":[],"lastModifiedDate":"2018-05-01T14:13:39","indexId":"70196791","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3035,"text":"Pest Management Science","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the potential for weed seed dispersal based on waterfowl consumption and seed viability","docAbstract":"<div id=\"ps4710-sec-0001\" class=\"article-section__content\"><p class=\"article-section__sub-title\"><strong>BACKGROUND</strong></p><p>Migratory waterfowl have often been implicated in the movement of troublesome agronomic and wetland weed species. However, minimal research has been conducted to investigate the dispersal of agronomically important weed species by waterfowl. The two objectives for this project were to determine what weed species are being consumed by ducks and snow geese, and to determine the recovery rate and viability of 13 agronomic weed species after passage through a duck's digestive system.</p></div><div id=\"ps4710-sec-0002\" class=\"article-section__content\"><p class=\"article-section__sub-title\"><strong>RESULTS</strong></p><p>Seed recovered from digestive tracts of 526 ducks and geese harvested during a 2‐year field study had 35 020 plants emerge. A greater variety of plant species emerged from ducks each year (47 and 31 species) compared to geese (11 and 3 species). Viable seed from 11 of 13 weed species fed to ducks in a controlled feeding study were recovered. Viability rate and gut retention times indicated potential dispersal up to 2900&nbsp;km from the source depending on seed characteristics and variability in waterfowl dispersal distances.</p></div><div id=\"ps4710-sec-0003\" class=\"article-section__content\"><p class=\"article-section__sub-title\"><strong>CONCLUSIONS</strong></p><p>Study results confirm that waterfowl are consuming seeds from a variety of agronomically important weed species, including Palmer amaranth, which can remain viable after passage through digestive tracts and have potential to be dispersed over long distances by waterfowl.</p></div>","language":"English","publisher":"Wiley","doi":"10.1002/ps.4710","usgsCitation":"Farmer, J.A., Webb, E.B., Pierce, R.A., and Bradley, K.W., 2017, Evaluating the potential for weed seed dispersal based on waterfowl consumption and seed viability: Pest Management Science, v. 73, no. 12, p. 2592-2603, https://doi.org/10.1002/ps.4710.","productDescription":"12 p.","startPage":"2592","endPage":"2603","ipdsId":"IP-079701","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":353888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-27","publicationStatus":"PW","scienceBaseUri":"5afee79ce4b0da30c1bfc302","contributors":{"authors":[{"text":"Farmer, Jaime A.","contributorId":204585,"corporation":false,"usgs":false,"family":"Farmer","given":"Jaime","email":"","middleInitial":"A.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":734420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734419,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pierce, Robert A. II","contributorId":204586,"corporation":false,"usgs":false,"family":"Pierce","given":"Robert","suffix":"II","email":"","middleInitial":"A.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":734421,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradley, Kevin W.","contributorId":204587,"corporation":false,"usgs":false,"family":"Bradley","given":"Kevin","email":"","middleInitial":"W.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":734422,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70195374,"text":"70195374 - 2017 - Sea turtles, light pollution, and citizen science: A preliminary report","interactions":[],"lastModifiedDate":"2018-10-20T12:36:34","indexId":"70195374","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Sea turtles, light pollution, and citizen science: A preliminary report","docAbstract":"Sea turtles are an important ecological resource for Gulf Islands National Seashore’s (Gulf Islands) waters and shorelines. Regionally, sea turtles face anthropogenic threats from situations\nsuch as entanglement in fishing gear and ingestion of marine debris, as well as possible changes in sex ratios due to increasing temperatures related to human-induced global warming. Locally, light pollution from residential, commercial, and industrial neighborhoods from nearby cities impacts the entirety of Gulf Islands, which spans 160 miles along the Gulf Coast, from Florida to Mississippi, and includes critical habitat for threatened and endangered sea turtles. Because light pollution has been hypothesized to negatively impact sea turtle nesting and hatchling survival, Gulf Islands undertook an effort to understand the relationship between light pollution and sea turtles and create unique educational and outreach opportunities by launching a citizen science program called Turtle Teens Helping in the Seashore (Turtle THIS). At the onset, the Turtle THIS program had two primary goals: quantify the association between light pollution and sea turtle nesting and hatching events using rigorous scientific methods; and initiate a citizen science volunteer program to provide youth with hands-on science and environmental stewardship roles, where they also gain employable skills and career opportunities. With multiple scientific hypotheses to consider, the development of a citizen science program became crucial. Such circumstances allowed Turtle THIS to grow a volunteer and intern program, quantify hypothesized light effects on sea turtles through developed methods, and begin to gather preliminary findings.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Connections across people, place, and time: Proceedings of the 2017 George Wright Society Conference on Parks, Protected Areas, and Cultural Sites","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"George Wright Society","usgsCitation":"Afford, H., Teel, S., Nicholas, M., Stanley, T.R., and White, J., 2017, Sea turtles, light pollution, and citizen science: A preliminary report, <i>in</i> Connections across people, place, and time: Proceedings of the 2017 George Wright Society Conference on Parks, Protected Areas, and Cultural Sites, p. 9-15.","productDescription":"7 p.","startPage":"9","endPage":"15","ipdsId":"IP-088000","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":351533,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.georgewright.org/proceedings2017"},{"id":351534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Gulf Islands National Seashore, Pensacola Beach","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.42645263671875,\n              30.289310339324643\n            ],\n            [\n              -86.91146850585938,\n              30.289310339324643\n            ],\n            [\n              -86.91146850585938,\n              30.387684205387366\n            ],\n            [\n              -87.42645263671875,\n              30.387684205387366\n            ],\n            [\n              -87.42645263671875,\n              30.289310339324643\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee7aae4b0da30c1bfc33f","contributors":{"authors":[{"text":"Afford, Heather","contributorId":202360,"corporation":false,"usgs":false,"family":"Afford","given":"Heather","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":728240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Teel, Susan","contributorId":202361,"corporation":false,"usgs":false,"family":"Teel","given":"Susan","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":728241,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nicholas, Mark","contributorId":202362,"corporation":false,"usgs":false,"family":"Nicholas","given":"Mark","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":728242,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanley, Thomas R. 0000-0002-8393-0005 stanleyt@usgs.gov","orcid":"https://orcid.org/0000-0002-8393-0005","contributorId":209928,"corporation":false,"usgs":true,"family":"Stanley","given":"Thomas","email":"stanleyt@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":728239,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Jeremy","contributorId":202363,"corporation":false,"usgs":false,"family":"White","given":"Jeremy","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":728243,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196769,"text":"70196769 - 2017 - Macroscale patterns of synchrony identify complex relationships among spatial and temporal ecosystem drivers","interactions":[],"lastModifiedDate":"2018-05-01T13:49:25","indexId":"70196769","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Macroscale patterns of synchrony identify complex relationships among spatial and temporal ecosystem drivers","docAbstract":"<p><span>Ecology has a rich history of studying ecosystem dynamics across time and space that has been motivated by both practical management needs and the need to develop basic ideas about pattern and process in nature. In situations in which both spatial and temporal observations are available, similarities in temporal behavior among sites (i.e., synchrony) provide a means of understanding underlying processes that create patterns over space and time. We used pattern analysis algorithms and data spanning 22–25&nbsp;yr from 601 lakes to ask three questions: What are the temporal patterns of lake water clarity at sub‐continental scales? What are the spatial patterns (i.e., geography) of synchrony for lake water clarity? And, what are the drivers of spatial and temporal patterns in lake water clarity? We found that the synchrony of water clarity among lakes is not spatially structured at sub‐continental scales. Our results also provide strong evidence that the drivers related to spatial patterns in water clarity are not related to the temporal patterns of water clarity. This analysis of long‐term patterns of water clarity and possible drivers contributes to understanding of broad‐scale spatial patterns in the geography of synchrony and complex relationships between spatial and temporal patterns across ecosystems.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2024","usgsCitation":"Lottig, N.R., Tan, P., Wagner, T., Cheruvelil, K.S., Soranno, P.A., Stanley, E.H., Scott, C.E., Stow, C.A., and Yuan, S., 2017, Macroscale patterns of synchrony identify complex relationships among spatial and temporal ecosystem drivers: Ecosphere, v. 8, no. 12, p. 1-11, https://doi.org/10.1002/ecs2.2024.","productDescription":"e02024; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-088150","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469271,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2024","text":"Publisher Index Page"},{"id":353883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-13","publicationStatus":"PW","scienceBaseUri":"5afee79de4b0da30c1bfc306","contributors":{"authors":[{"text":"Lottig, Noah R.","contributorId":172031,"corporation":false,"usgs":false,"family":"Lottig","given":"Noah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":734433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tan, Pang-Ning","contributorId":172193,"corporation":false,"usgs":false,"family":"Tan","given":"Pang-Ning","affiliations":[],"preferred":false,"id":734434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734305,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cheruvelil, Kendra Spence","contributorId":150607,"corporation":false,"usgs":false,"family":"Cheruvelil","given":"Kendra","email":"","middleInitial":"Spence","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":734435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soranno, Patricia A.","contributorId":172104,"corporation":false,"usgs":false,"family":"Soranno","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":734436,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":734437,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Scott, Caren E.","contributorId":172184,"corporation":false,"usgs":false,"family":"Scott","given":"Caren","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":734438,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stow, Craig A.","contributorId":204103,"corporation":false,"usgs":false,"family":"Stow","given":"Craig","email":"","middleInitial":"A.","affiliations":[{"id":36843,"text":"NOAA, Great Lakes Environmental Research Lab","active":true,"usgs":false}],"preferred":false,"id":734439,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yuan, Shuai","contributorId":172187,"corporation":false,"usgs":false,"family":"Yuan","given":"Shuai","affiliations":[],"preferred":false,"id":734440,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70196793,"text":"70196793 - 2017 - Thermal tolerances of fishes occupying groundwater and surface-water dominated streams","interactions":[],"lastModifiedDate":"2018-05-01T14:48:45","indexId":"70196793","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Thermal tolerances of fishes occupying groundwater and surface-water dominated streams","docAbstract":"<p><span>A thermal tolerance study mimicking different stream environments could improve our ecological understanding of how increasing water temperatures affect stream ectotherms and improve our ability to predict organism responses based on river classification schemes. Our objective was to compare the thermal tolerances of stream fishes of different habitat guilds among 3 exposure periods: critical thermal maximum (CTmax, increase of 2°C/h until loss of equilibrium [LOE] and death [D]), and 2 longer-term treatments (net daily increase of 1°C) that mimicked spring-fed (SF; 4°C daily increase) and non-spring-fed (NSF; 8°C daily increase) conditions. Fishes in the pelagic habitat guild had a 1°C higher average CTmax than benthic fishes. Thermal responses of species depended on exposure period with higher and increased variation in tolerances associated with the SF and NSF exposure periods. Logperch, Orangebelly Darter, Orangethroat Darter, and Southern Redbelly Dace were more sensitive to thermal increases regardless of SF or NSF treatment than were the 3 remaining species (Brook Silverside, Central Stoneroller, and Redspot Chub), which represented average thermal responses among the species tested. The 3 species that had a higher thermal response to CTmax-D (lethal endpoint of death) also were able to increase their tolerances more than other species in both SF and NSF treatments. Our data indicate finer guild designations may be useful for predicting thermal-response patterns. A diel thermal refuge increases the thermal responses of ectotherms to daily maxima, but the patterns across our SF and NSF treatments were similar suggesting minimum refuge temperatures may be more important than maximums. Nonetheless, stream temperature cooling over a 24-h period is important to ectotherm thermal tolerances, a result suggesting that sources of cooler water to streams might benefit from protection.</span></p>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/694781","usgsCitation":"Farless, N., and Brewer, S.K., 2017, Thermal tolerances of fishes occupying groundwater and surface-water dominated streams: Freshwater Science, v. 36, no. 4, p. 866-876, https://doi.org/10.1086/694781.","productDescription":"11 p.","startPage":"866","endPage":"876","ipdsId":"IP-079936","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":353891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee79ce4b0da30c1bfc300","contributors":{"authors":[{"text":"Farless, Nicole","contributorId":141040,"corporation":false,"usgs":false,"family":"Farless","given":"Nicole","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":734465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":734424,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70194119,"text":"70194119 - 2017 - Food web conceptual model","interactions":[],"lastModifiedDate":"2017-12-15T13:29:05","indexId":"70194119","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":5573,"text":"Interagency Ecological Program Technical Report","active":true,"publicationSubtype":{"id":4}},"seriesNumber":"91","title":"Food web conceptual model","docAbstract":"<p>This chapter describes a general model of food webs within tidal wetlands and represents how physical features of the wetland affect the structure and function of the food web. This conceptual model focuses on how the food web provides support for (or may reduce support for) threatened fish species. This model is part of a suite of conceptual models designed to guide monitoring of restoration sites throughout the San Francisco Estuary (SFE), but particularly within the Sacramento-San Joaquin Delta (Delta) and Suisun Marsh. The conceptual models have been developed based on the Delta Regional Ecosystem Restoration Implementation Plan (DRERIP) models, and are designed to aid in the identification and evaluation of monitoring metrics for tidal wetland restoration projects. </p><p>Many tidal restoration sites in the Delta are being constructed to comply with environmental regulatory requirements associated with the operation of the Central Valley Project and State Water Project. These include the Biological Opinions for Delta Smelt (Hypomesus transpacificus) and salmonids (U.S. Fish and Wildlife Service 2008; National Marine Fisheries Service 2009), and the Incidental Take Permit for Longfin Smelt (Spirinchus thaleichthyes) (California Department of Fish and Wildlife 2009). </p><p>These regulatory requirements are based on the hypothesis that the decline of listed fish species is due in part to a decline in productivity of the food web (phytoplankton and zooplankton in particular) or alterations in the food web such that production is consumed by other species in the Estuary (Sommer et al. 2007; Baxter et al. 2010; Brown et al. 2016a). Intertidal wetlands and shallow subtidal habitat can be highly productive, so restoring areas of tidal wetlands may result in a net increase in productivity that will provide food web support for these fish species. However, other factors such as invasive bivalves that reduce phytoplankton and zooplankton biomass and invasive predatory fishes that may compete with or prey upon listed fishes can limit the utility of tidal wetlands for food web support (Lucas and Thompson 2012; Herbold et al. 2014). </p><p>This model utilizes information from the previous DRERIP models for Delta food webs (Durand 2008) and tidal wetlands (Kneib et al. 2008), an updated DRERIP model (Durand 2015), and the State of BayDelta Science 2016 review of recent Delta food web literature (Brown et al. 2016a).</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Effects of tidal wetland restoration on fish: A suite of conceptual models","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"California Department of Water Resources","usgsCitation":"Hartman, R., Brown, L.R., and Hobbs, J., 2017, Food web conceptual model: Interagency Ecological Program Technical Report 91, 38 p.","productDescription":"38 p.","startPage":"143","endPage":"180","ipdsId":"IP-082772","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":350040,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":348890,"type":{"id":11,"text":"Document"},"url":"https://www.water.ca.gov/iep/docs/tech_rpts/TR91.Wetland_CM_2Nov2017.pdf"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf8e4b06e28e9c22a45","contributors":{"authors":[{"text":"Hartman, Rosemary","contributorId":200388,"corporation":false,"usgs":false,"family":"Hartman","given":"Rosemary","email":"","affiliations":[],"preferred":false,"id":722155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":722154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hobbs, Jim","contributorId":200389,"corporation":false,"usgs":false,"family":"Hobbs","given":"Jim","email":"","affiliations":[],"preferred":false,"id":722156,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194511,"text":"70194511 - 2017 - Attaching transmitters to waterbirds using one versus two subcutaneous anchors: Retention and survival trade-offs","interactions":[],"lastModifiedDate":"2018-01-05T13:54:16","indexId":"70194511","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Attaching transmitters to waterbirds using one versus two subcutaneous anchors: Retention and survival trade-offs","docAbstract":"<p><span>A major challenge of wildlife telemetry is choosing an attachment technique that maximizes transmitter retention while minimizing negative side effects. For waterbirds, attachment of transmitters with subcutaneous anchors has been an effective and well-established technique, having been used on &gt;40 species. This method was recently modified to include a second subcutaneous anchor, presumably increasing transmitter retention beyond that of single-anchor attachments. This putative benefit may be offset, however, by increased health risks related to additional incisions and subcutaneous protrusions. To test this potential trade-off, we attached radiotransmitters to molting and wintering surf (</span><i>Melanitta perspicillata</i><span>) and white-winged scoters (</span><i>M. fusca</i><span>) during 2008 and 2009 in Washington State and southeast Alaska, USA, using single- (121 scoters) and double-anchor (128 scoters) attachment techniques. We estimated daily probabilities of survival and radio retention for each group, this being apparent retention for wintering scoters because we could not differentiate shed transmitters from flighted emigration. For scoters during the flightless remigial molt, we found that addition of a second anchor increased cumulative retention probability (±SE) over a 49-day period from 0.69 ± 0.11 for single-anchor to 0.88 ± 0.07 for double-anchor attachments, while having no effect on survival. However, during winter, scoters with double-anchor attachments experienced no improvement in apparent retention, while having significantly lower survival during their first 14 days following transmitter attachment; of 15 mortalities during this period, 11 had 2 subcutaneous anchors. From day 15 onward, winter survival rates were nearly identical for single- versus double-anchor attachments, indicating that adverse effects of subcutaneous anchors were mainly limited to the 14-day postattachment period. Overall, given that the survival cost of adding a second subcutaneous anchor was substantial for wintering scoters—decreasing 14-day survival by 12% for adults and 23% for juveniles—we recommend that researchers opt for single-anchor attachments under most circumstances, especially during winter when birds may be energetically challenged.<span>&nbsp;</span></span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.833","usgsCitation":"Lewis, T., Esler, D., Uher-Koch, B.D., Dickson, R.D., Anderson, E.M., Evenson, J.R., Hupp, J.W., and Flint, P.L., 2017, Attaching transmitters to waterbirds using one versus two subcutaneous anchors: Retention and survival trade-offs: Wildlife Society Bulletin, v. 41, no. 4, p. 691-700, https://doi.org/10.1002/wsb.833.","productDescription":"10 p.","startPage":"691","endPage":"700","ipdsId":"IP-084591","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":500044,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/0444e913129c4df68e3a7e61bc40a972","text":"External Repository"},{"id":438136,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79S1PZJ","text":"USGS data release","linkHelpText":"Data for Evaluating Efficacy of 1- versus 2-prong Radio Transmitter Attachment for Scoters in Alaska and Washington, 2008-2010"},{"id":349626,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-23","publicationStatus":"PW","scienceBaseUri":"5a60faf8e4b06e28e9c22a37","contributors":{"authors":[{"text":"Lewis, Tyler 0000-0002-4998-3031 tlewis@usgs.gov","orcid":"https://orcid.org/0000-0002-4998-3031","contributorId":169307,"corporation":false,"usgs":true,"family":"Lewis","given":"Tyler","email":"tlewis@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":724198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esler, Daniel 0000-0001-5501-4555 desler@usgs.gov","orcid":"https://orcid.org/0000-0001-5501-4555","contributorId":5465,"corporation":false,"usgs":true,"family":"Esler","given":"Daniel","email":"desler@usgs.gov","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":724199,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Uher-Koch, Brian D. 0000-0002-1885-0260 buher-koch@usgs.gov","orcid":"https://orcid.org/0000-0002-1885-0260","contributorId":5117,"corporation":false,"usgs":true,"family":"Uher-Koch","given":"Brian","email":"buher-koch@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":724200,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dickson, Rian D.","contributorId":138554,"corporation":false,"usgs":false,"family":"Dickson","given":"Rian","email":"","middleInitial":"D.","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":false,"id":724201,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Eric M.","contributorId":138556,"corporation":false,"usgs":false,"family":"Anderson","given":"Eric","email":"","middleInitial":"M.","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":false,"id":724202,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Evenson, Joseph R.","contributorId":138555,"corporation":false,"usgs":false,"family":"Evenson","given":"Joseph","email":"","middleInitial":"R.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":724203,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hupp, Jerry W. 0000-0002-6439-3910 jhupp@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-3910","contributorId":127803,"corporation":false,"usgs":true,"family":"Hupp","given":"Jerry","email":"jhupp@usgs.gov","middleInitial":"W.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":724204,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":724205,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70190237,"text":"sir20175072 - 2017 - Groundwater model of the Great Basin carbonate and alluvial aquifer system version 3.0: Incorporating revisions in southwestern Utah and east central Nevada","interactions":[],"lastModifiedDate":"2017-12-04T10:30:46","indexId":"sir20175072","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5072","title":"Groundwater model of the Great Basin carbonate and alluvial aquifer system version 3.0: Incorporating revisions in southwestern Utah and east central Nevada","docAbstract":"<p><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">The groundwater model described in this report is a new version of previously published steady-state numerical groundwater flow models of the Great Basin carbonate and alluvial aquifer system, and was developed in conjunction with U.S. Geological Survey studies in Parowan, Pine, and Wah Wah Valleys, Utah. This version of the model is GBCAAS v. 3.0 and supersedes previous versions. The objectives of the model for Parowan Valley were to simulate revised conceptual estimates of recharge and discharge, to estimate simulated aquifer storage properties and the amount of reduction in storage as a result of historical groundwater withdrawals, and to assess reduction in groundwater withdrawals necessary to mitigate groundwater-level declines in the basin. The objectives of the model for the area near Pine and Wah Wah Valleys were to recalibrate the model using new observations of groundwater levels and evapotranspiration of groundwater; to provide new estimates of simulated recharge, hydraulic conductivity, and interbasin flow; and to simulate the effects of proposed groundwater withdrawals on the regional flow system. Meeting these objectives required the addition of 15 transient calibration stress periods and 14 projection stress periods, aquifer storage properties, historical withdrawals in Parowan Valley, and observations of water-level changes in Parowan Valley.&nbsp;</span></p><p><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">Recharge in Parowan Valley and withdrawal from wells in Parowan Valley and two nearby wells in Cedar City Valley vary for each calibration stress period representing conditions from March 1940 to November 2013. Stresses, including recharge, are the same in each stress period as in the steady-state stress period for all areas outside of Parowan Valley. The model was calibrated to transient conditions only in Parowan Valley. Simulated storage properties outside of Parowan Valley were set the same as the Parowan Valley properties and are not considered calibrated.&nbsp;</span></p><p><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">Model observations in GBCAAS v. 3.0 are groundwater levels at wells and discharge locations; water-level changes; and discharge to springs, evapotranspiration of groundwater, rivers, and lakes. All observations in the model outside of Parowan Valley are considered to represent steady-state conditions. Composite scaled sensitivities indicate the observations of discharge to rivers and springs provide more information about model parameters in the model focus area than&nbsp;</span><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">do water-level observations. Water levels and water-level changes, however, provide the only information about specific yield and specific storage parameters and provide more information about recharge and withdrawals in Parowan Valley than any other observation group.&nbsp;</span></p><p><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">Comparisons of simulated water levels and measured water levels in Parowan Valley indicated that the model fits the overall trend of declining water levels and provides reasonable estimates of long-term reduction in storage and of storage changes from 2012 to 2013. The conceptual and simulated groundwater budgets for Parowan Valley from November 2012 to November 2013 are similar, with recharge of about 20,000 acre-feet and discharge of about 45,000 acre-feet. In the simulation, historical withdrawals averaging about 28,000 acre-feet per year (acre-ft/yr) cause major changes in the groundwater system in Parowan Valley. These changes include the cessation of almost all natural discharge in the valley and the long-term removal of water from storage.&nbsp;</span></p><p><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">Simulated recharge in Pine Valley of 11,000 acre-ft/yr and in Wah Wah Valley of 3,200 acre-ft/yr is substantially less in GBCAAS v. 3.0 than that simulated by previous model versions. In addition, the valleys have less simulated inflow from and outflow to other hydrographic areas than were simulated by previous model versions. The effects of groundwater development in these valleys, however, are independent of the amount of water recharging in and flowing through the valleys. Groundwater withdrawals in Pine and Wah Wah Valleys will decrease groundwater storage (causing drawdown) until discharge in surrounding areas and mountain springs around the two valleys is reduced by the rate of withdrawal.&nbsp;</span></p><p><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">The model was used to estimate that reducing withdrawals in Parowan Valley from 35,000 to about 22,000 acre-ft/yr would likely stabilize groundwater levels in the valley if recharge varies as it did from about 1950 to 2012. The model was also used to demonstrate that withdrawals of 15,000 acre-ft/yr from Pine Valley and 6,500 acre-ft/yr from Wah Wah Valley could ultimately cause long-term steady-state water-level declines of about 1,900 feet near the withdrawal wells and of more than 5 feet in an area of about 10,500 square miles. The timing of drawdown and capture and the ultimate amount of drawdown are dependent on the proximity to areas of simulated natural groundwater discharge, simulated transmissivity, and simulated storage properties. The model projections are a representation of possible effects.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175072","collaboration":"Prepared in cooperation with the Utah Department of Natural Resources and the U.S. Bureau of Land Management","usgsCitation":"Brooks, L.E., 2017, Groundwater model of the Great Basin carbonate and alluvial aquifer system version 3.0: Incorporating revisions in southwestern Utah and east central Nevada: U.S. Geological Survey Scientific Investigations Report 2017–5072, 77 p., 2 appendixes, https://doi.org/10.3133/sir20175072.","productDescription":"Report: x, 77 p.; Appendix Tables; Data Release","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-073792","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":349442,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5072/sir20175072.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5072"},{"id":349441,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5072/coverthb.jpg"},{"id":349505,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/sir2017-5072.xml","text":"Data Release","description":"SIR 2017-5072","linkHelpText":"MODFLOW-LGR data sets for the Great Basin carbonate and alluvial aquifer system model version 3.0: Revisions in southwestern Utah and east central Nevada"},{"id":349444,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5072/sir20175072_appendix1table5_6.zip","text":"Appendix 1 Tables 5 and 6","size":"400 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2017-5072"}],"country":"United States","state":"Nevada, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.25,\n              37.5\n            ],\n            [\n              -111.75,\n              37.5\n            ],\n            [\n              -111.75,\n              40\n            ],\n            [\n              -114.25,\n              40\n            ],\n            [\n              -114.25,\n              37.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://ut.water.usgs.gov/about/employeedirectory.html\" data-mce-href=\"https://ut.water.usgs.gov/about/employeedirectory.html\">Director</a>,<br><a href=\"http://ut.water.usgs.gov/\" data-mce-href=\"http://ut.water.usgs.gov/\">Utah Water Science Center<br></a><a href=\"http://usgs.gov/\" data-mce-href=\"http://usgs.gov/\">U.S. Geological Survey<br></a>2329 West Orton Circle<br>Salt Lake City, UT 84119-2047</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Transient Model<br></li><li>Boundary Conditions<br></li><li>Hydraulic Properties<br></li><li>Observations Used in Model Calibration<br></li><li>Need for Recalibration<br></li><li>Calibration<br></li><li>Model Evaluation<br></li><li>Model Results<br></li><li>Model Projection<br></li><li>Model Limitations<br></li><li>Appropriate Uses of the Model<br></li><li>Summary<br></li><li>References<br></li><li>Appendixes<br></li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2017-12-01","noUsgsAuthors":false,"publicationDate":"2017-12-01","publicationStatus":"PW","scienceBaseUri":"5a60fafae4b06e28e9c22a6d","contributors":{"authors":[{"text":"Brooks, Lynette E. 0000-0002-9074-0939 lebrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-9074-0939","contributorId":2718,"corporation":false,"usgs":true,"family":"Brooks","given":"Lynette","email":"lebrooks@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":708044,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70192991,"text":"70192991 - 2017 - Determining quantity and quality of retained oil in mature marly chalk and marlstone of the Cretaceous Niobrara Formation by low-temperature hydrous pyrolysis","interactions":[],"lastModifiedDate":"2017-12-18T12:41:02","indexId":"70192991","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Determining quantity and quality of retained oil in mature marly chalk and marlstone of the Cretaceous Niobrara Formation by low-temperature hydrous pyrolysis","docAbstract":"<p>Low-temperature hydrous pyrolysis (LTHP) at 300°C (572°F) for 24 h released retained oils from 12- to 20-meshsize samples of mature Niobrara marly chalk and marlstone cores. The released oil accumulated on the water surface of the reactor, and is compositionally similar to oil produced from the same well. The quantities of oil released from the marly chalk and marlstone by LTHP are respectively 3.4 and 1.6 times greater than those determined by tight rock analyses (TRA) on aliquots of the same samples. Gas chromatograms indicated this difference is a result of TRA oils losing more volatiles and volatilizing less heavy hydrocarbons during collection than LTHP oils. Characterization of the rocks before and after LTPH by programmable open-system pyrolysis (HAWK) indicate that under LTHP conditions no significant oil is generated and only preexisting retained oil is released. Although LTHP appears to provide better predictions of quantity and quality of retained oil in a mature source rock, it is not expected to replace the more time and sample-size efficacy of TRA. However, LTHP can be applied to composited samples from key intervals or lithologies originally recognized by TRA. Additional studies on duration, temperature, and sample size used in LTHP may further optimize its utility. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":" Unconventional Resources Technology Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":" Unconventional Resources Technology Conference","usgsCitation":"Lewan, M., and Sonnenfeld, M.D., 2017, Determining quantity and quality of retained oil in mature marly chalk and marlstone of the Cretaceous Niobrara Formation by low-temperature hydrous pyrolysis, <i>in</i>  Unconventional Resources Technology Conference, 8 p.","productDescription":"8 p.","ipdsId":"IP-085370","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":350077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347665,"type":{"id":15,"text":"Index Page"},"url":"https://archives.datapages.com/data/urtec/2017/2670700.htm"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf9e4b06e28e9c22a57","contributors":{"authors":[{"text":"Lewan, Michael 0000-0001-6347-1553 mlewan@usgs.gov","orcid":"https://orcid.org/0000-0001-6347-1553","contributorId":173938,"corporation":false,"usgs":true,"family":"Lewan","given":"Michael","email":"mlewan@usgs.gov","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":717546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sonnenfeld, Mark D.","contributorId":198886,"corporation":false,"usgs":false,"family":"Sonnenfeld","given":"Mark","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":717547,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70195672,"text":"70195672 - 2017 - Evaluating factors driving population densities of mayfly nymphs in Western Lake Erie","interactions":[],"lastModifiedDate":"2018-02-27T09:53:47","indexId":"70195672","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating factors driving population densities of mayfly nymphs in Western Lake Erie","docAbstract":"<p><span>Mayfly (</span><i>Hexagenia</i><span><span>&nbsp;</span>spp.) nymphs have been widely used as indicators of water and substrate quality in lakes. Thermal stratification and the subsequent formation of benthic hypoxia may result in nymph mortality. Our goal was to identify potential associations between recent increases in temperature and eutrophication, which exacerbate hypoxic events in lakes, and mayfly populations in Lake Erie. Nymphs were collected during April–May 1999–2014. We used wind and temperature data to calculate four measures of thermal stratification, which drives hypoxic events, during summers of 1998–2013. Bottom trawl data collected during August 1998–2013 were used to estimate annual biomass of fishes known to be predators of mayfly nymphs. We used Akaike's Information Criterion to identify the best one- and two-predictor regression models of annual population densities (</span><i>N</i><span>/m</span><sup>2</sup><span>) of age-1 and age-2 nymphs, in which candidate predictors included the four measures of stratification, predator fish biomass, competition, and population densities of age-2 (for age-1) and age-1 (for age-2) nymphs from the previous year. Densities of both age classes of nymphs declined over the time series. Population densities of age-1 and age-2 nymphs from the previous year best predicted annual population densities of nymphs of both age classes. However, hypoxic conditions (indicated by stratification) and predation both had negative effects on annual population density of mayflies. Compared with predation, hypoxia had an inconsistent effect on annual nymph density. The increases in temperature and eutrophication in Lake Erie, which exacerbate hypoxic events, may have drastic effects on the mayfly populations.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2017.09.007","usgsCitation":"Stapanian, M.A., Kocovsky, P., and Bodamer Scarbro, B.L., 2017, Evaluating factors driving population densities of mayfly nymphs in Western Lake Erie: Journal of Great Lakes Research, v. 43, no. 6, p. 1111-1118, https://doi.org/10.1016/j.jglr.2017.09.007.","productDescription":"8 p.","startPage":"1111","endPage":"1118","ipdsId":"IP-081809","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":352054,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Erie","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.50296020507811,\n              41.40462579877838\n            ],\n            [\n              -82.496337890625,\n              41.40462579877838\n            ],\n            [\n              -82.496337890625,\n              42.097203425683055\n            ],\n            [\n              -83.50296020507811,\n              42.097203425683055\n            ],\n            [\n              -83.50296020507811,\n              41.40462579877838\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"43","issue":"6","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee7aae4b0da30c1bfc335","contributors":{"authors":[{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":729633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":729635,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bodamer Scarbro, Betsy L. 0000-0002-9022-7027 bbodamerscarbro@usgs.gov","orcid":"https://orcid.org/0000-0002-9022-7027","contributorId":5857,"corporation":false,"usgs":true,"family":"Bodamer Scarbro","given":"Betsy","email":"bbodamerscarbro@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":729634,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70195185,"text":"70195185 - 2017 - The effect of beaver ponds on water quality in rural coastal plain streams","interactions":[],"lastModifiedDate":"2018-02-07T13:29:53","indexId":"70195185","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"The effect of beaver ponds on water quality in rural coastal plain streams","docAbstract":"<p><span>We compared water-quality effects of 13 beaver ponds on adjacent free-flowing control reaches in the Coastal Plain of rural North Carolina. We measured concentrations of nitrate, ammonium, soluble reactive phosphorus (SRP), and suspended sediment (SS) upstream and downstream of paired ponds and control reaches. Nitrate and SS concentrations decreased, ammonium concentrations increased, and SRP concentrations were unaffected downstream of the ponds and relative to the control reaches. The pond effect on nitrate concentration was a reduction of 112 ± 55 μg-N/L (19%) compared to a control-reach—influenced reduction of 28 ± 17 μg-N/L. The pond effect on ammonium concentration was an increase of 9.47 ± 10.9 μg-N/L (59%) compared to the control-reach—influenced reduction of 1.49 ± 1.37 μg-N/L. The pond effect on SS concentration was a decrease of 3.41 ± 1.68 mg/L (40%) compared to a control-reach—influenced increase of 0.56 ± 0.27 mg/L. Ponds on lower-order streams reduced nitrate concentrations by greater amounts compared to those in higher-order streams. Older ponds reduced SS concentrations by greater amounts compared to younger ponds. The findings of this study indicate that beaver ponds provide water-quality benefits to rural Coastal Plain streams by reducing concentrations of nitrate and suspended sediment.</span></p>","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/058.016.0408","usgsCitation":"Bason, C.W., Kroes, D., and Brinson, M., 2017, The effect of beaver ponds on water quality in rural coastal plain streams: Southeastern Naturalist, v. 16, no. 4, p. 584-602, https://doi.org/10.1656/058.016.0408.","productDescription":"19 p.","startPage":"584","endPage":"602","ipdsId":"IP-076120","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":351269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -77.75848388671875,\n              35.24225438307026\n            ],\n            [\n              -76.95236206054688,\n              35.24225438307026\n            ],\n            [\n              -76.95236206054688,\n              35.89795019335754\n            ],\n            [\n              -77.75848388671875,\n              35.89795019335754\n            ],\n            [\n              -77.75848388671875,\n              35.24225438307026\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"16","issue":"4","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e78e4b00f54eb229312","contributors":{"authors":[{"text":"Bason, Christopher W.","contributorId":201992,"corporation":false,"usgs":false,"family":"Bason","given":"Christopher","email":"","middleInitial":"W.","affiliations":[{"id":36316,"text":"Delaware Center for the Inland Bays","active":true,"usgs":false}],"preferred":false,"id":727336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kroes, Daniel 0000-0001-9104-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-9077","contributorId":3830,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":727335,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brinson, Mark M.","contributorId":45761,"corporation":false,"usgs":true,"family":"Brinson","given":"Mark M.","affiliations":[],"preferred":false,"id":727337,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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