{"pageNumber":"372","pageRowStart":"9275","pageSize":"25","recordCount":68867,"records":[{"id":70191874,"text":"ofr20171134 - 2017 - Health and condition of endangered young-of-the-year Lost River and Shortnose suckers relative to water quality in Upper Klamath Lake, Oregon, 2014–2015","interactions":[],"lastModifiedDate":"2017-10-20T13:08:22","indexId":"ofr20171134","displayToPublicDate":"2017-10-19T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1134","title":"Health and condition of endangered young-of-the-year Lost River and Shortnose suckers relative to water quality in Upper Klamath Lake, Oregon, 2014–2015","docAbstract":"<p>Most mortality of endangered Lost River (<i>Deltistes luxatus</i>) and shortnose (<i>Chasmistes brevirostris</i>) suckers in Upper Klamath Lake, Oregon, occurs within the first year of life. Juvenile suckers in Clear Lake Reservoir, California, survive longer and may even recruit to the spawning populations. In a previous (2013–2014) study, the health and condition of juvenile suckers and the dynamics of water quality between Upper Klamath Lake and Clear Lake Reservoir were compared. That study found that apparent signs of stress or exposure to irritants, such as peribiliary cuffing in liver tissue and mild inflammation and necrosis in gill tissues, were present in suckers from both lakes and were unlikely to be clues to the cause of differential mortality between lakes. Seasonal trends in energy storage as glycogen and triglycerides were also similar between lakes, indicating prey limitation was not a likely factor in differential mortality. To better understand the relationship between juvenile sucker health and water quality, we examined suckers collected in 2014–2015 from Upper Klamath Lake, where water quality can be dynamic and, at times, extreme.</p><p>While there were notable differences in water quality and fish health between years, we were not able to identify any specific water-quality-related causes for differential fish condition. Water quality was generally better in 2014 than in 2015. When considered together afflictions and abnormalities generally indicated healthier suckers in 2014 than 2015. Low dissolved-oxygen events (&lt; 4 milligrams per liter) were less frequent and occurred earlier; high pH events (≥ 9.5) were less frequent and shorter in duration; large diel fluctuations in pH (≥ 1.4) were less frequent; water temperatures were warmer, particularly in July and September; and concentrations of microcystin in both large and small fractions of samples were lower in 2014 than in 2015. Total and therefore also un-ionized ammonia were low in 2014–2015 relative to concentrations known to affect suckers. Petechial hemorrhages of the skin, attached <i>Lernaea</i> spp. and eosinophilic hyaline droplets in the kidney tubules were less prevalent in 2014 than in 2015; however, hyperplastic and hypertrophic gill tissue and trichodinids on the gills were observed more frequently in 2014. There were more suckers with normal liver color and texture in 2014 than in 2015. The prevalence of suckers with liver inflammation was greater in 2014 and only observed in suckers collected after August 5, whereas liver inflammation occurred intermittently in 2015. Liver glycogen among suckers decreased in late-August 2014 and increased from early August to mid-September 2015. Lost River suckers had greater whole-body triglyceride content but a larger proportion with an absence of visceral fat observed in 2014 than in 2015. In contrast, shortnose suckers were similar between years in regard to both whole-body triglyceride and visceral fat. Black-spot-forming parasites (trematode metacercariae) were observed in a higher prevalence on shortnose suckers but not Lost River suckers in 2014 than in 2015. Opercular deformities were less prevalent in both species in 2014 than in 2015.</p><p>Neither gross nor histological examination revealed a high prevalence of abnormalities in suckers that clearly indicate a primary mechanism for juvenile mortality in Upper Klamath Lake. Histological abnormalities were almost always focal and minimal or mild except where associated with parasites. Mild to severe focal abnormalities associated with <i>Lernaea</i> sp. attachment sites and encysted digenean (trematode) metacercariae are unlikely to be associated with mortality. Severe and diffuse inflammation and hyperplasia of the gills associated with<i> Ichthyobodo</i> sp. on one Lost River sucker, may indicate a potential cause of mortality. High mortality may have primarily occurred outside our study period (for example, in spring or over winter), or was caused by a factor that could not be detected with our methods (for example, predation). Alternatively, abnormalities in a small percentage of passively captured suckers in Upper Klamath Lake may indicate health-related issues that were more prevalent in populations than in our samples. Temporary decreases in liver glycogen stores may also indicate periods of stress, which may eventually lead to mortality of young suckers.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171134","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Burdick, S.M., Conway, C.M., Elliott, D.G., Hoy, M.S., Dolan-Caret, Amari, and Ostberg, C.O., 2017, Health and condition of endangered young-of-the-year Lost River and shortnose suckers relative to water quality in Upper Klamath Lake, Oregon, 2014–2015: U.S. Geological Survey Open-File Report 2017-1134, 40 p., https://doi.org/10.3133/ofr20171134.","productDescription":"vi, 41 p.","onlineOnly":"Y","ipdsId":"IP-089897","costCenters":[{"id":654,"text":"Western Fisheries Research 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Area<br></li><li>Methods<br></li><li>Results<br></li><li>Discussion&nbsp;<br></li><li>Conclusions<br></li><li>Acknowledgments<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2017-10-19","noUsgsAuthors":false,"publicationDate":"2017-10-19","publicationStatus":"PW","scienceBaseUri":"59e9b991e4b05fe04cd65c46","contributors":{"authors":[{"text":"Burdick, Summer M. 0000-0002-3480-5793 sburdick@usgs.gov","orcid":"https://orcid.org/0000-0002-3480-5793","contributorId":3448,"corporation":false,"usgs":true,"family":"Burdick","given":"Summer","email":"sburdick@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":713494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Carla M. 0000-0002-3851-3616 cmconway@usgs.gov","orcid":"https://orcid.org/0000-0002-3851-3616","contributorId":2946,"corporation":false,"usgs":true,"family":"Conway","given":"Carla","email":"cmconway@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":713495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, Diane G. 0000-0002-4809-6692 dgelliott@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-6692","contributorId":2947,"corporation":false,"usgs":true,"family":"Elliott","given":"Diane","email":"dgelliott@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":713496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoy, Marshal S. 0000-0003-2828-9697 mhoy@usgs.gov","orcid":"https://orcid.org/0000-0003-2828-9697","contributorId":3033,"corporation":false,"usgs":true,"family":"Hoy","given":"Marshal","email":"mhoy@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":713497,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dolan-Caret, Amari 0000-0001-9155-6116 amaridc@usgs.gov","orcid":"https://orcid.org/0000-0001-9155-6116","contributorId":149805,"corporation":false,"usgs":true,"family":"Dolan-Caret","given":"Amari","email":"amaridc@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":713498,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ostberg, Carl O. 0000-0003-1479-8458 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,{"id":70192061,"text":"70192061 - 2017 - At the forefront: evidence of the applicability of using environmental DNA to quantify the abundance of fish populations in natural lentic waters with additional sampling considerations","interactions":[],"lastModifiedDate":"2017-11-29T16:21:20","indexId":"70192061","displayToPublicDate":"2017-10-19T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"At the forefront: evidence of the applicability of using environmental DNA to quantify the abundance of fish populations in natural lentic waters with additional sampling considerations","docAbstract":"<p><span>Environmental DNA (eDNA) sampling has proven to be a valuable tool for detecting species in aquatic ecosystems. Within this rapidly evolving field, a promising application is the ability to obtain quantitative estimates of relative species abundance based on eDNA concentration rather than traditionally labor-intensive methods. We investigated the relationship between eDNA concentration and Arctic char (</span><i>Salvelinus alpinus</i><span>) abundance in five well-studied natural lakes; additionally, we examined the effects of different temporal (e.g., season) and spatial (e.g., depth) scales on eDNA concentration. Concentrations of eDNA were linearly correlated with char population estimates (</span><img id=\"_i1\" src=\"http://www.nrcresearchpress.com/na101/home/literatum/publisher/nrc/journals/content/cjfas/0/cjfas.ahead-of-print/cjfas-2017-0114/20170821/images/medium/cjfas-2017-0114ieq1.gif\" alt=\"\" data-mce-src=\"http://www.nrcresearchpress.com/na101/home/literatum/publisher/nrc/journals/content/cjfas/0/cjfas.ahead-of-print/cjfas-2017-0114/20170821/images/medium/cjfas-2017-0114ieq1.gif\"><span><span>&nbsp;</span>= 0.78) and exponentially correlated with char densities (</span><img id=\"_i2\" src=\"http://www.nrcresearchpress.com/na101/home/literatum/publisher/nrc/journals/content/cjfas/0/cjfas.ahead-of-print/cjfas-2017-0114/20170821/images/medium/cjfas-2017-0114ieq2.gif\" alt=\"\" data-mce-src=\"http://www.nrcresearchpress.com/na101/home/literatum/publisher/nrc/journals/content/cjfas/0/cjfas.ahead-of-print/cjfas-2017-0114/20170821/images/medium/cjfas-2017-0114ieq2.gif\"><span><span>&nbsp;</span>= 0.96 by area; 0.82 by volume). Across lakes, eDNA concentrations were greater and more homogeneous in the water column during mixis; however, when stratified, eDNA concentrations were greater in the hypolimnion. Overall, our findings demonstrate that eDNA techniques can produce effective estimates of relative fish abundance in natural lakes. These findings can guide future studies to improve and expand eDNA methods while informing research and management using rapid and minimally invasive sampling.</span></p>","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2017-0114","usgsCitation":"Klobucar, S., Rodgers, T.W., and Budy, P., 2017, At the forefront: evidence of the applicability of using environmental DNA to quantify the abundance of fish populations in natural lentic waters with additional sampling considerations: Canadian Journal of Fisheries and Aquatic Sciences, v. 74, no. 12, p. 2030-2034, https://doi.org/10.1139/cjfas-2017-0114.","productDescription":"5 p.","startPage":"2030","endPage":"2034","ipdsId":"IP-086031","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469423,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2017-0114","text":"External Repository"},{"id":346987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e9b98fe4b05fe04cd65c2d","contributors":{"authors":[{"text":"Klobucar, Stephen L.","contributorId":172291,"corporation":false,"usgs":false,"family":"Klobucar","given":"Stephen L.","affiliations":[],"preferred":false,"id":714079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rodgers, Torrey W.","contributorId":197683,"corporation":false,"usgs":false,"family":"Rodgers","given":"Torrey","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":714080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Budy, Phaedra E. 0000-0002-9918-1678 pbudy@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":140028,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":714041,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70188854,"text":"ofr20171073 - 2017 - Design and methods of the Midwest Stream Quality Assessment (MSQA), 2013","interactions":[],"lastModifiedDate":"2017-10-19T09:39:41","indexId":"ofr20171073","displayToPublicDate":"2017-10-18T16:45:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1073","title":"Design and methods of the Midwest Stream Quality Assessment (MSQA), 2013","docAbstract":"<p>During 2013, the U.S. Geological Survey (USGS) National Water-Quality Assessment Project (NAWQA), in collaboration with the USGS Columbia Environmental Research Center, the U.S. Environmental Protection Agency (EPA) National Rivers and Streams Assessment (NRSA), and the EPA Office of Pesticide Programs assessed stream quality across the Midwestern United States. This Midwest Stream Quality Assessment (MSQA) simultaneously characterized watershed and stream-reach water-quality stressors along with instream biological conditions, to better understand regional stressor-effects relations. The MSQA design focused on effects from the widespread agriculture in the region and urban development because of their importance as ecological stressors of particular concern to Midwest region resource managers.</p><p>A combined random stratified selection and a targeted selection based on land-use data were used to identify and select sites representing gradients in agricultural intensity across the region. During a 14-week period from May through August 2013, 100 sites were selected and sampled 12 times for contaminants, nutrients, and sediment. This 14-week water-quality “index” period culminated with an ecological survey of habitat, periphyton, benthic macroinvertebrates, and fish at all sites. Sediment was collected during the ecological survey for analysis of sediment chemistry and toxicity testing. Of the 100 sites, 50 were selected for the MSQA random stratified group from 154 NRSA sites planned for the region, and the other 50 MSQA sites were selected as targeted sites to more evenly cover agricultural and urban stressor gradients in the study area. Of the 50 targeted sites, 12 were in urbanized watersheds and 21 represented “good” biological conditions or “least disturbed” conditions. The remaining 17 targeted sites were selected to improve coverage of the agricultural intensity gradient or because of historical data collection to provide temporal context for the study.</p><p>This report provides a detailed description of the MSQA study components, including surveys of ecological conditions, routine water sampling, deployment of passive polar organic compound integrative samplers, and stream sediment sampling at all sites. Component studies that were completed to provide finer scale temporal data or more extensive analysis at selected sites, included continuous water-quality monitoring, daily pesticide sampling, laboratory and in-stream water toxicity testing efforts, and deployment of passive suspended-sediment samplers.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171073","collaboration":"National Water-Quality Program </br>Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Garrett, J.D., Frey, J.W., Van Metre, P.C., Journey, C.A., Nakagaki, Naomi, Button, D.T., and Howell, L.H., 2017, Design and methods of the Midwest Stream Quality Assessment (MSQA), 2013: U.S. Geological Survey Open-File Report 2017–1073, 59 p., 4 app., https://doi.org/10.3133/ofr20171073.","productDescription":"Report: x, 57 p.; 4 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,{"id":70189259,"text":"ofr20171086 - 2017 - HIF evaluation of In-Situ Aqua TROLL 400","interactions":[],"lastModifiedDate":"2017-10-19T10:19:36","indexId":"ofr20171086","displayToPublicDate":"2017-10-18T14:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1086","title":"HIF evaluation of In-Situ Aqua TROLL 400","docAbstract":"<p>The In-Situ Aqua TROLL 400 (Aqua TROLL 400) was tested at the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) against known standards over the Aqua TROLL 400’s operating temperature to verify the manufacturer’s stated accuracy specifications and the USGS recommendations for pH, dissolved oxygen (DO), and specific conductance (SC). The Aqua TROLL 400 manufacturer’s specifications are within the USGS recommendations for all parameters tested, except for DO, which is outside the USGS recommendation at DO concentrations of 8.0 milligrams per liter (mg/L) and higher. The Aqua TROLL 400 was compliant with Serial Digital Interface at 1200 baud (SDI-12) version 1.3. During laboratory testing of pH, the Aqua TROLL 400 sonde met the U.S. Geological Survey “National Field Manual for the Collection of Water-Quality Data” (NFM) recommendations for pH at all values tested, except at 4 degrees Celsius (°C) at pH 9.395 and pH 3.998. The Aqua TROLL 400 met the manufacturer specifications for pH at all values tested, except for pH buffers 3.998, 9.395, and 10.245 at 4 °C; pH 2.990 and 3.998 at 15 °C; and pH 3.040 at 40 °C. The Aqua TROLL 400 met the NFM recommendations at 93.7 percent of the SC values tested and met the manufacturer’s accuracy specifications at 56.3 percent of the SC values tested. During the laboratory testing for DO, the Aqua TROLL 400 met the manufacturer specifications, except at 5.55 mg/L, and met the NFM recommendations at all concentrations tested. An Aqua TROLL 400 was field tested at USGS Station 02492620, National Space Technology Laboratories (NSTL) Station, Mississippi, on the Pearl River for 6 weeks and showed good agreement with the well-maintained site sonde data for pH, DO, temperature, and SC.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171086","usgsCitation":"Tillman, E.F., 2017, HIF evaluation of In-Situ Aqua TROLL 400: U.S. Geological Survey Open-File Report, 2017–1086, 35 p., https://doi.org/10.3133/ofr20171086.","productDescription":"vi, 35 p.","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076079","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":346630,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1086/coverthb.jpg"},{"id":346631,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1086/ofr20171086.pdf","text":"Report","size":"856 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1086"}],"contact":"<p>Chief,<a href=\"http://water.usgs.gov/hif/\" data-mce-href=\"http://water.usgs.gov/hif/\"> Hydrologic Instrumentation Facility</a><br> U.S. Geological Survey<br> Building 2101<br> Stennis Space Center, MS 39529</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Description</li><li>Test Procedures</li><li>Field Test</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-10-18","noUsgsAuthors":false,"publicationDate":"2017-10-18","publicationStatus":"PW","scienceBaseUri":"59e8682de4b05fe04cd4d19c","contributors":{"authors":[{"text":"Tillman, Evan F. etillman@usgs.gov","contributorId":194342,"corporation":false,"usgs":true,"family":"Tillman","given":"Evan","email":"etillman@usgs.gov","middleInitial":"F.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":703783,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70191862,"text":"70191862 - 2017 - Linking functional response and bioenergetics to estimate juvenile salmon growth in a reservoir food web","interactions":[],"lastModifiedDate":"2017-10-18T14:35:46","indexId":"70191862","displayToPublicDate":"2017-10-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Linking functional response and bioenergetics to estimate juvenile salmon growth in a reservoir food web","docAbstract":"<p><span>Juvenile salmon (</span><i>Oncorhynchus</i><span><span>&nbsp;</span>spp.) use of reservoir food webs is understudied. We examined the feeding behavior of subyearling Chinook salmon (</span><i>O</i><span>.<span>&nbsp;</span></span><i>tshawytscha</i><span>) and its relation to growth by estimating the functional response of juvenile salmon to changes in the density of<span>&nbsp;</span></span><i>Daphnia</i><span>, an important component of reservoir food webs. We then estimated salmon growth across a broad range of water temperatures and daily rations of two primary prey,<span>&nbsp;</span></span><i>Daphnia</i><span><span>&nbsp;</span>and juvenile American shad (</span><i>Alosa sapidissima</i><span>) using a bioenergetics model. Laboratory feeding experiments yielded a Type-II functional response curve:<span>&nbsp;</span></span><i>C</i><span><span>&nbsp;</span>= 29.858<span>&nbsp;</span></span><i>P</i><span><span>&nbsp;</span>*(4.271 +<span>&nbsp;</span></span><i>P</i><span>)</span><sup>-1</sup><span><span>&nbsp;</span>indicating that salmon consumption (</span><i>C</i><span>) of<span>&nbsp;</span></span><i>Daphnia</i><span><span>&nbsp;</span>was not affected until<span>&nbsp;</span></span><i>Daphnia</i><span><span>&nbsp;</span>densities (</span><i>P</i><span>) were &lt; 30 · L</span><sup>-1</sup><span>. Past field studies documented<span>&nbsp;</span></span><i>Daphnia</i><span><span>&nbsp;</span>densities in lower Columbia River reservoirs of &lt; 3 · L</span><sup>-1</sup><span><span>&nbsp;</span>in July but as high as 40 · L</span><sup>-1</sup><span><span>&nbsp;</span>in August. Bioenergetics modeling indicated that subyearlings could not achieve positive growth above 22°C regardless of prey type or consumption rate. When feeding on<span>&nbsp;</span></span><i>Daphnia</i><span>, subyearlings could not achieve positive growth above 20°C (water temperatures they commonly encounter in the lower Columbia River during summer). At 16–18°C, subyearlings had to consume about 27,000<span>&nbsp;</span></span><i>Daphnia</i><span><span>&nbsp;</span>· day</span><sup>-1</sup><span><span>&nbsp;</span>to achieve positive growth. However, when feeding on juvenile American shad, subyearlings had to consume 20 shad · day</span><sup>-1</sup><span><span>&nbsp;</span>at 16–18°C, or at least 25 shad · day</span><sup>-1</sup><span><span>&nbsp;</span>at 20°C to achieve positive growth. Using empirical consumption rates and water temperatures from summer 2013, subyearlings exhibited negative growth during July (-0.23 to -0.29 g · d</span><sup>-1</sup><span>) and August (-0.05 to -0.07 g · d</span><sup>-1</sup><span>). By switching prey from<span>&nbsp;</span></span><i>Daphnia</i><span><span>&nbsp;</span>to juvenile shad which have a higher energy density, subyearlings can partially compensate for the effects of higher water temperatures they experience in the lower Columbia River during summer. However, achieving positive growth as piscivores requires subyearlings to feed at higher consumption rates than they exhibited empirically. While our results indicate compromised growth in reservoir habitats, the long-term repercussions to salmon populations in the Columbia River Basin are unknown.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0185933","usgsCitation":"Haskell, C.A., Beauchamp, D.A., and Bollens, S., 2017, Linking functional response and bioenergetics to estimate juvenile salmon growth in a reservoir food web: PLoS ONE, v. 10, no. 12, p. 1-21, https://doi.org/10.1371/journal.pone.0185933.","productDescription":"e0185933; 21 p.","startPage":"1","endPage":"21","ipdsId":"IP-084728","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":469425,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0185933","text":"Publisher Index Page"},{"id":346885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-11","publicationStatus":"PW","scienceBaseUri":"59e8682fe4b05fe04cd4d1b0","contributors":{"authors":[{"text":"Haskell, Craig A. 0000-0002-3604-1758 chaskell@usgs.gov","orcid":"https://orcid.org/0000-0002-3604-1758","contributorId":3458,"corporation":false,"usgs":true,"family":"Haskell","given":"Craig","email":"chaskell@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":713442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":713443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bollens, Stephen M.","contributorId":181850,"corporation":false,"usgs":false,"family":"Bollens","given":"Stephen M.","affiliations":[],"preferred":false,"id":713444,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191858,"text":"70191858 - 2017 - Shelf evolution along a transpressive transform margin, Santa Barbara Channel, California","interactions":[],"lastModifiedDate":"2017-12-19T16:48:08","indexId":"70191858","displayToPublicDate":"2017-10-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Shelf evolution along a transpressive transform margin, Santa Barbara Channel, California","docAbstract":"<p>High-resolution bathymetric and seismic reflection data provide new insights for understanding the post–Last Glacial Maximum (LGM, ca. 21&nbsp;ka) evolution of the ∼120-km-long Santa Barbara shelf, located within a transpressive segment of the transform continental margin of western North America. The goal is to determine how rising sea level, sediment supply, and tectonics combine to control shelf geomorphology and history. Morpho­logic, stratigraphic, and structural data highlight regional variability and support division of the shelf into three domains. (1) The eastern Santa Barbara shelf is south of and in the hanging wall of the blind south-dipping Oak Ridge fault. The broad gently dipping shelf has a convex-upward shape resulting from thick post-LGM sediment (mean&nbsp;= 24.7&nbsp;m) derived from the Santa Clara River. (2) The ∼5–8-km-wide Ventura Basin obliquely crosses the shelf and forms an asymmetric trough with thick post-LGM sediment fill (mean&nbsp;= 30.4&nbsp;m) derived from the Santa Clara and Ventura Rivers. The basin is between and in the footwalls of the Oak Ridge fault to the south and the blind north-dipping Pitas Point fault to the north. (3) The central and western Santa Barbara shelf is located north of and in the hanging wall of the North Channel–Pitas Point fault system. The concave-up shape of the shelf results from folding, marine erosion, and the relative lack of post-LGM sediment cover (mean&nbsp;= 3.8&nbsp;m). Sediment is derived from small steep coastal watersheds and largely stored in the Gaviota bar and other nearshore mouth bars. Three distinct upper slope morphologies result from a mix of progradation and submarine landsliding.</p><p>Ages and rates of deformation are derived from a local sea-level-rise model that incorporates an inferred LGM shoreline angle and the LGM wave-cut platform. Post-LGM slip rates on the offshore Oak Ridge fault are a mini­mum of 0.7&nbsp;± 0.1 mm/yr. Slip rates on the Pitas Point fault system are a minimum of 2.3&nbsp;± 0.3 mm/yr near Pitas Point, and decrease to the west across the Santa Barbara Channel. Documentation of fault lengths, slip rates, and rupture modes, as well as potential zones of submarine landsliding, provide essential information for enhanced regional earthquake and tsunami hazard assessment.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01387.1","usgsCitation":"Johnson, S.Y., Hartwell, S., Sorlien, C.C., Dartnell, P., and Ritchie, A., 2017, Shelf evolution along a transpressive transform margin, Santa Barbara Channel, California: Geosphere, v. 13, no. 6, p. 2041-2077, https://doi.org/10.1130/GES01387.1.","productDescription":"37 p.","startPage":"2041","endPage":"2077","ipdsId":"IP-076906","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469426,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01387.1","text":"Publisher Index Page"},{"id":346917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":" California","otherGeospatial":"Santa Barbara Channel","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.7012939453125,\n              33.8339199536547\n            ],\n            [\n              -119.06982421874999,\n              33.8339199536547\n            ],\n            [\n              -119.06982421874999,\n              34.59704151614417\n            ],\n            [\n              -120.7012939453125,\n              34.59704151614417\n            ],\n            [\n              -120.7012939453125,\n              33.8339199536547\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-02","publicationStatus":"PW","scienceBaseUri":"59e8682fe4b05fe04cd4d1b2","contributors":{"authors":[{"text":"Johnson, Samuel Y. 0000-0001-7972-9977 sjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-7972-9977","contributorId":2607,"corporation":false,"usgs":true,"family":"Johnson","given":"Samuel","email":"sjohnson@usgs.gov","middleInitial":"Y.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartwell, Stephen 0000-0002-3522-7526 shartwell@usgs.gov","orcid":"https://orcid.org/0000-0002-3522-7526","contributorId":146221,"corporation":false,"usgs":true,"family":"Hartwell","given":"Stephen","email":"shartwell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sorlien, Christopher C. 0000-0002-2359-9592","orcid":"https://orcid.org/0000-0002-2359-9592","contributorId":197404,"corporation":false,"usgs":false,"family":"Sorlien","given":"Christopher","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":713423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ritchie, Andrew C.","contributorId":139060,"corporation":false,"usgs":false,"family":"Ritchie","given":"Andrew C.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":713425,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70191837,"text":"70191837 - 2017 - Multistressor predictive models of invertebrate condition in the Corn Belt, USA","interactions":[],"lastModifiedDate":"2017-11-29T16:22:43","indexId":"70191837","displayToPublicDate":"2017-10-18T00:00:00","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":"Multistressor predictive models of invertebrate condition in the Corn Belt, USA","docAbstract":"<p><span>Understanding the complex relations between multiple environmental stressors and ecological conditions in streams can help guide resource-management decisions. During 14 weeks in spring/summer 2013, personnel from the US Geological Survey and the US Environmental Protection Agency sampled 98 wadeable streams across the Midwest Corn Belt region of the USA for water and sediment quality, physical and habitat characteristics, and ecological communities. We used these data to develop independent predictive disturbance models for 3 macroinvertebrate metrics and a multimetric index. We developed the models based on boosted regression trees (BRT) for 3 stressor categories, land use/land cover (geographic information system [GIS]), all in-stream stressors combined (nutrients, habitat, and contaminants), and for GIS plus in-stream stressors. The GIS plus in-stream stressor models had the best overall performance with an average cross-validation&nbsp;</span><i>R</i><sup>2</sup><span><span>&nbsp;</span>across all models of 0.41. The models were generally consistent in the explanatory variables selected within each stressor group across the 4 invertebrate metrics modeled. Variables related to riparian condition, substrate size or embeddedness, velocity and channel shape, nutrients (primarily NH</span><sub>3</sub><span>), and contaminants (pyrethroid degradates) were important descriptors of the invertebrate metrics. Models based on all measured in-stream stressors performed comparably to models based on GIS landscape variables, suggesting that the in-stream stressor characterization reasonably represents the dominant factors affecting invertebrate communities and that GIS variables are acting as surrogates for in-stream stressors that directly affect in-stream biota.</span></p>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/694894","usgsCitation":"Waite, I.R., and Van Metre, P., 2017, Multistressor predictive models of invertebrate condition in the Corn Belt, USA: Freshwater Science, v. 36, no. 4, p. 901-914, https://doi.org/10.1086/694894.","productDescription":"14 p.","startPage":"901","endPage":"914","ipdsId":"IP-069783","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":346921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Iowa, Kansas, Kentucky, Minnesota, Missouri, Nebraska, Ohio, South Dakota, Wisconsin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.41552734375,\n              37.61423141542417\n            ],\n            [\n              -82.30957031249999,\n              37.61423141542417\n            ],\n            [\n              -82.30957031249999,\n              44.77793589631623\n            ],\n            [\n              -98.41552734375,\n              44.77793589631623\n            ],\n            [\n              -98.41552734375,\n              37.61423141542417\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e86831e4b05fe04cd4d1c5","contributors":{"authors":[{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Metre, Peter C. 0000-0001-7564-9814 pcvanmet@usgs.gov","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":197363,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","email":"pcvanmet@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":713307,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70191842,"text":"70191842 - 2017 - Ephemeral seafloor sedimentation during dam removal: Elwha River, Washington","interactions":[],"lastModifiedDate":"2017-11-29T16:23:38","indexId":"70191842","displayToPublicDate":"2017-10-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Ephemeral seafloor sedimentation during dam removal: Elwha River, Washington","docAbstract":"<p><span>The removal of the Elwha and Glines Canyon dams from the Elwha River in Washington, USA, resulted in the erosion and transport of over 10 million m</span><sup>3</sup><span><span><span>&nbsp;</span>of sediment from the former reservoirs and into the river during the first two years of the dam removal process. Approximately 90% of this sediment was transported through the Elwha River and to the coast at the Strait of Juan de Fuca. To evaluate the<span> benthic</span><span>&nbsp;</span>dynamics of increased sediment loading to the<span> nearshore</span></span><span>, we deployed a tripod system in ten meters of water to the east of the Elwha River mouth that included a profiling current meter and a camera system. With these data, we were able to document the frequency and duration of sedimentation and turbidity events, and correlate these events to physical oceanographic and river conditions. We found that<span> seafloor</span><span>&nbsp;</span>sedimentation occurred regularly during the heaviest sediment loading from the river, but that this sedimentation was ephemeral and exhibited regular cycles of deposition and erosion caused by the strong tidal currents in the region. Understanding the frequency and duration of short-term sediment disturbance events is instrumental to interpreting the ecosystem-wide changes that are occurring in the nearshore habitats around the Elwha River delta.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2017.09.005","usgsCitation":"Foley, M.M., and Warrick, J.A., 2017, Ephemeral seafloor sedimentation during dam removal: Elwha River, Washington: Continental Shelf Research, v. 150, p. 36-47, https://doi.org/10.1016/j.csr.2017.09.005.","productDescription":"12 p.","startPage":"36","endPage":"47","ipdsId":"IP-084897","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469424,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2017.09.005","text":"Publisher Index Page"},{"id":438186,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CR5RW8","text":"USGS data release","linkHelpText":"Oceanographic measurements obtained offshore of the Elwha River delta in coordination with the Elwha River Restoration Project, Washington, USA, 2010-2014"},{"id":438185,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MC8XHX","text":"USGS data release","linkHelpText":"Characterization of seafloor photographs near the mouth of the Elwha River during the first two years of dam removal (2011-2013)"},{"id":346906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.59258651733398,\n              48.13424631889282\n            ],\n            [\n              -123.51722717285155,\n              48.13424631889282\n            ],\n            [\n              -123.51722717285155,\n              48.163566497754275\n            ],\n            [\n              -123.59258651733398,\n              48.163566497754275\n            ],\n            [\n              -123.59258651733398,\n              48.13424631889282\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"150","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e86831e4b05fe04cd4d1c1","contributors":{"authors":[{"text":"Foley, Melissa M. 0000-0002-5832-6404 mfoley@usgs.gov","orcid":"https://orcid.org/0000-0002-5832-6404","contributorId":4861,"corporation":false,"usgs":true,"family":"Foley","given":"Melissa","email":"mfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713357,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70191549,"text":"70191549 - 2017 - Millennial-scale variability in the local radiocarbon reservoir age of south Florida during the Holocene","interactions":[],"lastModifiedDate":"2017-10-17T10:34:50","indexId":"70191549","displayToPublicDate":"2017-10-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3216,"text":"Quaternary Geochronology","active":true,"publicationSubtype":{"id":10}},"title":"Millennial-scale variability in the local radiocarbon reservoir age of south Florida during the Holocene","docAbstract":"<p><span>A growing body of research suggests that the marine environments of south Florida provide a critical link between the tropical and high-latitude Atlantic. Changes in the characteristics of water masses off south Florida may therefore have important implications for our understanding of climatic and oceanographic variability over a broad spatial scale; however, the sources of variability within this oceanic corridor remain poorly understood. Measurements of ΔR, the local offset of the radiocarbon reservoir age, from shallow-water marine environments can serve as a powerful tracer of water-mass sources that can be used to reconstruct variability in local-to regional-scale oceanography and hydrology. We combined radiocarbon and U-series measurements of Holocene-aged corals from the shallow-water environments of the Florida Keys reef tract (FKRT) with robust statistical modeling to quantify the millennial-scale variability in ΔR at locations with (“nearshore”) and without (“open ocean”) substantial terrestrial influence. Our reconstructions demonstrate that there was significant spatial and temporal variability in ΔR on the FKRT during the Holocene. Whereas ΔR was similar throughout the region after ∼4000 years ago, nearshore ΔR was significantly higher than in the open ocean during the middle Holocene. We suggest that the elevated nearshore ΔR from ∼8000 to 5000 years ago was most likely the result of greater groundwater influence associated with lower sea level at this time. In the open ocean, which would have been isolated from the influence of groundwater, ΔR was lowest ∼7000 years ago, and was highest ∼3000 years ago. We evaluated our open-ocean model of ΔR variability against records of local-to regional-scale oceanography and conclude that local upwelling was not a significant driver of open-ocean radiocarbon variability in this region. Instead, the millennial-scale trends in open-ocean ΔR were more likely a result of broader-scale changes in western Atlantic circulation associated with an increase in the supply of equatorial South Atlantic water to the Caribbean and shifts in the character of South Atlantic waters resulting from variation in the intensity of upwelling off the southwest coast of Africa. Because accurate estimates of ΔR are critical to precise calibrations of radiocarbon dates from marine samples, we also developed models of nearshore and open-ocean ΔR versus conventional&nbsp;</span><sup>14</sup><span>C ages that can be used for regional radiocarbon calibrations for the Holocene. Our study provides new insights into the patterns and drivers of oceanographic and hydrologic variability in the Straits of Florida and highlights the value of the paleoceanographic records from south Florida to our understanding of Holocene changes in climate and ocean circulation throughout the Atlantic.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.quageo.2017.07.005","usgsCitation":"Toth, L., Cheng, H., Edwards, R., Ashe, E., and Richey, J.N., 2017, Millennial-scale variability in the local radiocarbon reservoir age of south Florida during the Holocene: Quaternary Geochronology, v. 42, p. 130-143, https://doi.org/10.1016/j.quageo.2017.07.005.","productDescription":"14 p.","startPage":"130","endPage":"143","ipdsId":"IP-084508","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":461385,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quageo.2017.07.005","text":"Publisher Index Page"},{"id":438188,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P8492Q","text":"USGS data release","linkHelpText":"Local Radiocarbon Reservoir Age (Delta-R) Variability from the Nearshore and Open-Ocean Environments of the Florida Keys Reef Tract During the Holocene and Associated U-Series and Radiocarbon Data"},{"id":346672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.04290771484374,\n              24.492147541216028\n            ],\n            [\n              -80.15625,\n              24.492147541216028\n            ],\n            [\n              -80.15625,\n              25.535006795752302\n            ],\n            [\n              -83.04290771484374,\n              25.535006795752302\n            ],\n            [\n              -83.04290771484374,\n              24.492147541216028\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"42","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e7168ee4b05fe04cd33178","contributors":{"authors":[{"text":"Toth, Lauren T. ltoth@usgs.gov","contributorId":149483,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren T.","email":"ltoth@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":712730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cheng, Hai","contributorId":85896,"corporation":false,"usgs":true,"family":"Cheng","given":"Hai","affiliations":[],"preferred":false,"id":712743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, R. Lawrence","contributorId":55752,"corporation":false,"usgs":true,"family":"Edwards","given":"R. Lawrence","affiliations":[],"preferred":false,"id":712744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ashe, Erica","contributorId":194112,"corporation":false,"usgs":false,"family":"Ashe","given":"Erica","affiliations":[],"preferred":false,"id":712745,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richey, Julie N. 0000-0002-2319-7980 jrichey@usgs.gov","orcid":"https://orcid.org/0000-0002-2319-7980","contributorId":5182,"corporation":false,"usgs":true,"family":"Richey","given":"Julie","email":"jrichey@usgs.gov","middleInitial":"N.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":712746,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70191664,"text":"70191664 - 2017 - The importance of parameterization when simulating the hydrologic response of vegetative land-cover change","interactions":[],"lastModifiedDate":"2020-05-19T17:59:45.012244","indexId":"70191664","displayToPublicDate":"2017-10-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"The importance of parameterization when simulating the hydrologic response of vegetative land-cover change","docAbstract":"<p><span>Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km</span><sup>2</sup><span><span>&nbsp;</span>watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as<span>&nbsp;</span></span><q>behavioral</q><span><span>&nbsp;</span>in that they reproduce daily mean streamflow acceptably well according to Nash–Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/hess-21-3975-2017","usgsCitation":"White, J.T., Stengel, V.G., Rendon, S.H., and Banta, J., 2017, The importance of parameterization when simulating the hydrologic response of vegetative land-cover change: Hydrology and Earth System Sciences, v. 21, p. 3975-3989, https://doi.org/10.5194/hess-21-3975-2017.","productDescription":"15 p.","startPage":"3975","endPage":"3989","ipdsId":"IP-087111","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":469514,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-21-3975-2017","text":"Publisher Index Page"},{"id":346738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-04","publicationStatus":"PW","scienceBaseUri":"59e7168ce4b05fe04cd33162","contributors":{"authors":[{"text":"White, Jeremy T. 0000-0002-4950-1469 jwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":167708,"corporation":false,"usgs":true,"family":"White","given":"Jeremy","email":"jwhite@usgs.gov","middleInitial":"T.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stengel, Victoria G. 0000-0003-0481-3159 vstengel@usgs.gov","orcid":"https://orcid.org/0000-0003-0481-3159","contributorId":5932,"corporation":false,"usgs":true,"family":"Stengel","given":"Victoria","email":"vstengel@usgs.gov","middleInitial":"G.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rendon, Samuel H. 0000-0001-5589-0563 srendon@usgs.gov","orcid":"https://orcid.org/0000-0001-5589-0563","contributorId":3940,"corporation":false,"usgs":true,"family":"Rendon","given":"Samuel","email":"srendon@usgs.gov","middleInitial":"H.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Banta, John 0000-0002-2226-7270 jbanta@usgs.gov","orcid":"https://orcid.org/0000-0002-2226-7270","contributorId":171808,"corporation":false,"usgs":true,"family":"Banta","given":"John","email":"jbanta@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":713005,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70191552,"text":"70191552 - 2017 - Forecast first: An argument for groundwater modeling in reverse","interactions":[],"lastModifiedDate":"2017-10-17T10:24:51","indexId":"70191552","displayToPublicDate":"2017-10-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Forecast first: An argument for groundwater modeling in reverse","docAbstract":"<p>Numerical groundwater models are important compo-nents of groundwater analyses that are used for makingcritical decisions related to the management of ground-water resources. In this support role, models are oftenconstructed to serve a specific purpose that is to provideinsights, through simulation, related to a specific func-tion of a complex aquifer system that cannot be observeddirectly (Anderson et al. 2015).</p><p>For any given modeling analysis, several modelinput datasets must be prepared. Herein, the datasetsrequired to simulate the historical conditions are referredto as the calibration model, and the datasets requiredto simulate the model’s purpose are referred to as theforecast model. Future groundwater conditions or otherunobserved aspects of the groundwater system may besimulated by the forecast model—the outputs of interestfrom the forecast model represent the purpose of themodeling analysis. Unfortunately, the forecast model,needed to simulate the purpose of the modeling analysis,is seemingly an afterthought—calibration is where themajority of time and effort are expended and calibrationis usually completed before the forecast model is evenconstructed. Herein, I am proposing a new groundwatermodeling workflow, referred to as the “forecast first”workflow, where the forecast model is constructed at anearlier stage in the modeling analysis and the outputsof interest from the forecast model are evaluated duringsubsequent tasks in the workflow.</p>","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12558","usgsCitation":"White, J.T., 2017, Forecast first: An argument for groundwater modeling in reverse: Groundwater, v. 55, no. 5, p. 660-664, https://doi.org/10.1111/gwat.12558.","productDescription":"5 p.","startPage":"660","endPage":"664","ipdsId":"IP-085148","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":346670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-03","publicationStatus":"PW","scienceBaseUri":"59e7168ee4b05fe04cd33174","contributors":{"authors":[{"text":"White, Jeremy T. 0000-0002-4950-1469 jwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":167708,"corporation":false,"usgs":true,"family":"White","given":"Jeremy","email":"jwhite@usgs.gov","middleInitial":"T.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712742,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70204371,"text":"70204371 - 2017 - The NorWeST summer stream temperature model and scenarios for the western U.S.: A crowd-sourced database and new geospatial tools foster a user-community and predict broad climate warming of rivers and streams","interactions":[],"lastModifiedDate":"2019-12-22T14:51:52","indexId":"70204371","displayToPublicDate":"2017-10-16T13:40:18","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"The NorWeST summer stream temperature model and scenarios for the western U.S.: A crowd-sourced database and new geospatial tools foster a user-community and predict broad climate warming of rivers and streams","docAbstract":"<p><span>Thermal regimes are fundamental determinants of aquatic ecosystems, which makes description and prediction of temperatures critical during a period of rapid global change. The advent of inexpensive temperature sensors dramatically increased monitoring in recent decades, and although most monitoring is done by individuals for agency‐specific purposes, collectively these efforts constitute a massive distributed sensing array that generates an untapped wealth of data. Using the framework provided by the National Hydrography Dataset, we organized temperature records from dozens of agencies in the western U.S. to create the NorWeST database that hosts &gt;220,000,000 temperature recordings from &gt;22,700 stream and river sites. Spatial‐stream‐network models were fit to a subset of those data that described mean August water temperatures (AugTw) during 63,641 monitoring site‐years to develop accurate temperature models (</span><i>r</i><sup>2</sup><span> = 0.91; RMSPE = 1.10°C; MAPE = 0.72°C), assess covariate effects, and make predictions at 1 km intervals to create summer climate scenarios. AugTw averaged 14.2°C (SD = 4.0°C) during the baseline period of 1993–2011 in 343,000 km of western perennial streams but trend reconstructions also indicated warming had occurred at the rate of 0.17°C/decade (SD = 0.067°C/decade) during the 40 year period of 1976–2015. Future scenarios suggest continued warming, although variation will occur within and among river networks due to differences in local climate forcing and stream responsiveness. NorWeST scenarios and data are available online in user‐friendly digital formats and are widely used to coordinate monitoring efforts among agencies, for new research, and for conservation planning.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017WR020969","usgsCitation":"Isaak, D.J., Wenger, S.J., Peterson, E.E., Ver Hoef, J.M., Nagel, D., Luce, C.H., Hostetler, S.W., Dunham, J.B., Roper, B.B., Wollrab, S., Chandler, G.L., Horan, D., and Parkes-Payne, S., 2017, The NorWeST summer stream temperature model and scenarios for the western U.S.: A crowd-sourced database and new geospatial tools foster a user-community and predict broad climate warming of rivers and streams: Water Resources Research, v. 53, no. 11, p. 9181-9205, https://doi.org/10.1002/2017WR020969.","productDescription":"25 p.","startPage":"9181","endPage":"9205","ipdsId":"IP-090157","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"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":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":469437,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr020969","text":"Publisher Index Page"},{"id":365806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, 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0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":766581,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":766574,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Roper, Brett B.","contributorId":120701,"corporation":false,"usgs":false,"family":"Roper","given":"Brett","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":766582,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wollrab, Sherry P","contributorId":217320,"corporation":false,"usgs":false,"family":"Wollrab","given":"Sherry P","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":766583,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Chandler, Gwynne L","contributorId":217321,"corporation":false,"usgs":false,"family":"Chandler","given":"Gwynne","email":"","middleInitial":"L","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":766584,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Horan, Dona L","contributorId":217322,"corporation":false,"usgs":false,"family":"Horan","given":"Dona L","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":766585,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Parkes-Payne, Sharon","contributorId":217323,"corporation":false,"usgs":false,"family":"Parkes-Payne","given":"Sharon","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":766586,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70191508,"text":"70191508 - 2017 - Increasing floodplain connectivity through urban stream restoration increases nutrient and sediment retention","interactions":[],"lastModifiedDate":"2017-10-16T09:50:37","indexId":"70191508","displayToPublicDate":"2017-10-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Increasing floodplain connectivity through urban stream restoration increases nutrient and sediment retention","docAbstract":"<p><span>Stream restoration practices frequently aim to increase connectivity between the stream channel and its floodplain to improve channel stability and enhance water quality through sediment trapping and nutrient retention. To measure the effectiveness of restoration and to understand the drivers of these functional responses, we monitored five restored urban streams that represent a range of channel morphology and restoration ages. High and low elevation floodplain plots were established in triplicate in each stream to capture variation in floodplain connectivity. We measured ecosystem geomorphic and soil attributes, sediment and nutrient loading, and rates of soil nutrient biogeochemistry processes (denitrification; N and P mineralization) then used boosted regression trees (BRT) to identify controls on sedimentation and nutrient processing. Local channel and floodplain morphology and position within the river network controlled connectivity with increased sedimentation at sites downstream of impaired reaches and at floodplain plots near the stream channel and at low elevations. We observed that nitrogen loading (both dissolved and particulate) was positively correlated with denitrification and N mineralization and dissolved phosphate loading positively influenced P mineralization; however, none of these input rates or transformations differed between floodplain elevation categories. Instead, continuous gradients of connectivity were observed rather than categorical shifts between inset and high floodplains. Organic matter and nutrient content in floodplain soils increased with the time since restoration, which highlights the importance of recovery time after construction that is needed for restored systems to increase ecosystem functions. Our results highlight the importance of restoring floodplains downstream of sources of impairment and building them at lower elevations so they flood frequently, not just during bankfull events. This integrated approach has the greatest potential for increasing trapping of sediment, nutrients, and associated pollutants in restored streams and thereby improving water quality in urban watersheds.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2017.08.006","usgsCitation":"McMillan, S., and Noe, G.E., 2017, Increasing floodplain connectivity through urban stream restoration increases nutrient and sediment retention: Ecological Engineering, v. 108, no. A, p. 284-295, https://doi.org/10.1016/j.ecoleng.2017.08.006.","productDescription":"12 p.","startPage":"284","endPage":"295","ipdsId":"IP-088155","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":346621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","county":"Mecklenburg County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-80.7823,35.5113],[-80.7867,35.5031],[-80.7889,35.4949],[-80.7831,35.4836],[-80.7819,35.475],[-80.7779,35.4668],[-80.7778,35.4614],[-80.7744,35.4578],[-80.7549,35.423],[-80.7525,35.4148],[-80.7553,35.4125],[-80.7638,35.4134],[-80.7693,35.402],[-80.7551,35.3944],[-80.7364,35.3786],[-80.7187,35.3624],[-80.704,35.3552],[-80.6983,35.3507],[-80.6822,35.3131],[-80.6677,35.2705],[-80.6214,35.2499],[-80.5954,35.2369],[-80.5485,35.2108],[-80.6245,35.1487],[-80.7328,35.0627],[-80.7645,35.0375],[-80.7684,35.0348],[-80.7746,35.0329],[-80.7858,35.0315],[-80.7892,35.0314],[-80.8009,35.0286],[-80.8155,35.0204],[-80.8194,35.019],[-80.8216,35.018],[-80.8216,35.0167],[-80.8288,35.0098],[-80.835,35.0061],[-80.8405,35.0016],[-80.8604,35.0246],[-80.8854,35.0535],[-80.9016,35.0716],[-80.9312,35.1049],[-80.9373,35.1018],[-81.0383,35.0452],[-81.0419,35.0432],[-81.0447,35.0468],[-81.0464,35.0482],[-81.0483,35.0507],[-81.0503,35.0527],[-81.0528,35.0557],[-81.0548,35.0582],[-81.0568,35.0611],[-81.0577,35.0636],[-81.0586,35.067],[-81.0582,35.0722],[-81.0577,35.0788],[-81.0566,35.0834],[-81.0554,35.0868],[-81.0541,35.0904],[-81.0533,35.0927],[-81.0523,35.0956],[-81.0503,35.0975],[-81.0487,35.099],[-81.0462,35.1003],[-81.0437,35.1014],[-81.042,35.1022],[-81.0391,35.1027],[-81.0369,35.1036],[-81.0352,35.1054],[-81.0344,35.1072],[-81.0341,35.1095],[-81.0341,35.1136],[-81.0358,35.1186],[-81.0363,35.1213],[-81.038,35.124],[-81.0408,35.1267],[-81.0425,35.1281],[-81.0454,35.1289],[-81.0476,35.1295],[-81.0499,35.1302],[-81.051,35.1313],[-81.0521,35.1335],[-81.0523,35.1365],[-81.0517,35.1392],[-81.0501,35.142],[-81.0476,35.1463],[-81.0448,35.1494],[-81.0238,35.1486],[-81.0176,35.1536],[-81.0109,35.1532],[-81.0076,35.1569],[-81.0088,35.165],[-81.0049,35.1728],[-81.0045,35.1814],[-81.0046,35.1864],[-81.0063,35.1923],[-81.0064,35.1973],[-81.0054,35.2055],[-81.0071,35.2109],[-81.0129,35.2231],[-81.0113,35.2309],[-81.012,35.2349],[-81.0082,35.2509],[-81.0139,35.2585],[-81.0152,35.2685],[-81.0143,35.2876],[-81.0133,35.293],[-81.0105,35.2944],[-81.0033,35.3017],[-81.0022,35.3045],[-80.9961,35.3113],[-80.9938,35.3132],[-80.9894,35.3205],[-80.9844,35.3237],[-80.9805,35.3287],[-80.9823,35.3341],[-80.984,35.3373],[-80.9818,35.3446],[-80.9706,35.3501],[-80.9656,35.3506],[-80.9593,35.3489],[-80.9537,35.3521],[-80.9442,35.3521],[-80.9374,35.3572],[-80.9285,35.3614],[-80.9268,35.3627],[-80.9296,35.3636],[-80.9432,35.3658],[-80.9505,35.3675],[-80.9563,35.3738],[-80.9597,35.3756],[-80.9625,35.3756],[-80.9647,35.3738],[-80.9669,35.3688],[-80.9697,35.3669],[-80.9742,35.3642],[-80.9776,35.3646],[-80.9844,35.3695],[-80.9868,35.38],[-80.9846,35.3822],[-80.9806,35.3823],[-80.9761,35.3828],[-80.9632,35.3901],[-80.9554,35.3925],[-80.9549,35.4006],[-80.959,35.4133],[-80.9569,35.4288],[-80.9587,35.436],[-80.9527,35.446],[-80.9465,35.4524],[-80.9421,35.457],[-80.9432,35.4602],[-80.9506,35.4656],[-80.9518,35.4701],[-80.948,35.481],[-80.947,35.486],[-80.951,35.4942],[-80.9612,35.4986],[-80.9664,35.509],[-80.9637,35.5131],[-80.9586,35.5163],[-80.9569,35.5177],[-80.7823,35.5113]]]},\"properties\":{\"name\":\"Mecklenburg\",\"state\":\"NC\"}}]}","volume":"108","issue":"A","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e5c519e4b05fe04cd1c9c6","contributors":{"authors":[{"text":"McMillan, Sara K.","contributorId":197089,"corporation":false,"usgs":false,"family":"McMillan","given":"Sara K.","affiliations":[],"preferred":false,"id":712530,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":712529,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70191491,"text":"70191491 - 2017 - Evaluating upstream passage and timing of approach by adult bigheaded carps at a gated dam on the Illinois River","interactions":[],"lastModifiedDate":"2017-10-16T10:09:52","indexId":"70191491","displayToPublicDate":"2017-10-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating upstream passage and timing of approach by adult bigheaded carps at a gated dam on the Illinois River","docAbstract":"<p><span>Dams are a conservation threat because they function as barriers to native fish movement; however, they may prevent the spread of invasive species. Invasive bigheaded carps (</span><i>Hypophthalmichthys</i><span><span>&nbsp;</span>spp.) threaten the Great Lakes ecosystem and are advancing towards Lake Michigan via the Illinois River. Navigation dams on the Illinois River may deter bigheaded carps' upstream movement. We investigated the permeability of the Starved Rock Lock and Dam (SRLD), the most downstream gated Illinois River dam, to bigheaded carps' migration by examining the timing of individuals approaching and passing through SRLD in relation to gate openness, tailwater elevation, and water temperature. Using acoustic telemetry of (</span><i>N</i><span>&nbsp;=&nbsp;~104 per year) tagged fish, 13 upstream passages of bigheaded carps occurred through SRLD between 2013 and 2016. Eleven passages occurred through the dam gates and 2 through the lock chamber, indicating deterrents (e.g., CO</span><sub>2</sub><span>) placed in SRLD lock chamber may only limit passage of a small proportion of all fish passing through the lock-and-dam structure. Passages were documented only in 2013 and 2015. Most of the dam gate passages occurred during high water when gates were completely out of the water. Timing of bigheaded carps approaching SRLD was positively correlated with rising water temperature and high tailwater elevation, and all fish approached during late March through mid-September. Movement through dams is rare; modifying gate operations to reduce gate openness during late spring and summer could further reduce the permeability of gated dams such as SRLD to bigheaded carps, slowing their upstream advance.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/rra.3180","usgsCitation":"Lubejko, M., Whitledge, G., Coulter, A.A., Brey, M.K., Oliver, D., and Garvey, J.E., 2017, Evaluating upstream passage and timing of approach by adult bigheaded carps at a gated dam on the Illinois River: River Research and Applications, v. 33, no. 8, p. 1268-1278, https://doi.org/10.1002/rra.3180.","productDescription":"11 p.","startPage":"1268","endPage":"1278","ipdsId":"IP-084443","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":346624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois River, Starved Rock Lock and Dam","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.04041290283203,\n              41.308502890261764\n            ],\n            [\n              -88.94634246826172,\n              41.308502890261764\n            ],\n            [\n              -88.94634246826172,\n              41.333513657873205\n            ],\n            [\n              -89.04041290283203,\n              41.333513657873205\n            ],\n            [\n              -89.04041290283203,\n              41.308502890261764\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"33","issue":"8","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-21","publicationStatus":"PW","scienceBaseUri":"59e5c51ae4b05fe04cd1c9ca","contributors":{"authors":[{"text":"Lubejko, Matthew","contributorId":195897,"corporation":false,"usgs":false,"family":"Lubejko","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":712426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whitledge, Greg","contributorId":195898,"corporation":false,"usgs":false,"family":"Whitledge","given":"Greg","affiliations":[],"preferred":false,"id":712427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coulter, Alison A.","contributorId":187652,"corporation":false,"usgs":false,"family":"Coulter","given":"Alison","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":712425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oliver, Devon","contributorId":195899,"corporation":false,"usgs":false,"family":"Oliver","given":"Devon","affiliations":[],"preferred":false,"id":712429,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garvey, James E.","contributorId":178007,"corporation":false,"usgs":false,"family":"Garvey","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":712430,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192246,"text":"70192246 - 2017 - Meta-analysis of field-saturated hydraulic conductivity recovery following wildland fire: Applications for hydrologic model parameterization and resilience assessment","interactions":[],"lastModifiedDate":"2017-10-25T10:54:04","indexId":"70192246","displayToPublicDate":"2017-10-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Meta-analysis of field-saturated hydraulic conductivity recovery following wildland fire: Applications for hydrologic model parameterization and resilience assessment","docAbstract":"<p><span>Hydrologic recovery after wildfire is critical for restoring the ecosystem services of protecting of human lives and infrastructure from hazards and delivering water supply of sufficient quality and quantity. Recovery of soil-hydraulic properties, such as field-saturated hydraulic conductivity (</span><i>K</i><sub><i>fs</i></sub><span>), is a key factor for assessing the duration of watershed-scale flash flood and debris flow risks after wildfire. Despite the crucial role of<span>&nbsp;</span></span><i>K</i><sub><i>fs</i></sub><span><span>&nbsp;</span>in parameterizing numerical hydrologic models to predict the magnitude of postwildfire run-off and erosion, existing quantitative relations to predict<span>&nbsp;</span></span><i>K</i><sub><i>fs</i></sub><span>recovery with time since wildfire are lacking. Here, we conduct meta-analyses of 5 datasets from the literature that measure or estimate<span>&nbsp;</span></span><i>K</i><sub><i>fs</i></sub><span><span>&nbsp;</span>with time since wildfire for longer than 3-year duration. The meta-analyses focus on fitting 2 quantitative relations (linear and non-linear logistic) to explain trends in<span>&nbsp;</span></span><i>K</i><sub><i>fs</i></sub><span><span>&nbsp;</span>temporal recovery. The 2 relations adequately described temporal recovery except for 1 site where macropore flow dominated infiltration and<span>&nbsp;</span></span><i>K</i><sub><i>fs</i></sub><span><span>&nbsp;</span>recovery. This work also suggests that<span>&nbsp;</span></span><i>K</i><sub><i>fs</i></sub><span><span>&nbsp;</span>can have low hydrologic resistance (large postfire changes), and moderate to high hydrologic stability (recovery time relative to disturbance recurrence interval) and resilience (recovery of hydrologic function and provision of ecosystem services). Future<span>&nbsp;</span></span><i>K</i><sub><i>fs</i></sub><span><span>&nbsp;</span>relations could more explicitly incorporate processes such as soil-water repellency, ground cover and soil structure regeneration, macropore recovery, and vegetation regrowth.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11288","usgsCitation":"Ebel, B.A., and Martin, D.A., 2017, Meta-analysis of field-saturated hydraulic conductivity recovery following wildland fire: Applications for hydrologic model parameterization and resilience assessment: Hydrological Processes, v. 31, no. 21, p. 3682-3696, https://doi.org/10.1002/hyp.11288.","productDescription":"15 p.","startPage":"3682","endPage":"3696","ipdsId":"IP-084869","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":347327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"21","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-30","publicationStatus":"PW","scienceBaseUri":"59f1a2a4e4b0220bbd9d9f34","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":714984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":168662,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":714985,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70190439,"text":"sir20175085 - 2017 - Simulated effects of Lower Floridan aquifer pumping on the Upper Floridan aquifer at Barbour Pointe, Chatham County, Georgia","interactions":[],"lastModifiedDate":"2017-10-26T15:49:51","indexId":"sir20175085","displayToPublicDate":"2017-10-13T03:00:00","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":"2017-5085","title":"Simulated effects of Lower Floridan aquifer pumping on the Upper Floridan aquifer at Barbour Pointe, Chatham County, Georgia","docAbstract":"<p>Steady-state simulations using a revised regional groundwater-flow model based on MODFLOW were run to assess the potential long-term effects on the Upper Floridan aquifer (UFA) of pumping the Lower Floridan aquifer (LFA) at well 36Q398, located at Barbour Pointe in coastal Georgia near Savannah. Simulated pumping of well 36Q398 at a rate of 750 gallons per minute (gal/min; or 1.08 million gallons per day [Mgal/d]) indicated a maximum drawdown of about 2.19 feet (ft) in the UFA directly above the pumped well and at least 1 ft of drawdown within a nearly 190-square-mile area (scenario A). Induced vertical leakage from the UFA provided about 98 percent of the water to the pumped well. Simulated pumping of well 36Q398 caused increased downward leakage in all layers above the LFA, decreased upward leakage in all layers above the LFA, increased inflow to and decreased outflow from lateral specified-head boundaries in the UFA and LFA, and an increase in the volume of induced inflow from the general-head boundary representing outcrop units. Water budgets for scenario A indicated that changes in inflows and outflows through general-head boundaries would compose about 45 percent of the simulated pumpage from well 36Q398, with the remaining 55 percent of the pumped water derived from flow across lateral specified-head boundaries.</p><p>Additional steady-state simulations were run to evaluate a pumping rate in the UFA of 240 gal/min (0.346 Mgal/d), which would produce an equivalent maximum drawdown in the UFA as pumping from well 36Q398 in the LFA at a rate of 750 gal/min (called the “drawdown offset”; scenario B). Simulated pumping in the UFA for the drawdown offset produced about 2.18 ft of drawdown, comparable to 2.19 ft of drawdown in the UFA simulated in scenario A. Water budgets for scenario B also provided favorable comparisons with scenario A, indicating that 42 percent of the drawdown-offset pumpage (0.346 Mgal/d) in the UFA originates as increased inflow and decreased outflow across general-head boundaries from overlying units in the surficial and Brunswick aquifer systems and that the remaining simulated pumpage originates as flow across general- and specified-head boundaries within the UFA and LFA.</p><p>The revised model was evaluated for sensitivity by first altering horizontal and vertical hydraulic conductivity in the Lower Floridan semiconfining unit and then adjusting horizontal and vertical hydraulic conductivity in the LFA to match the 35.6 ft of drawdown at pumping well 36Q398. These adjustments also affected the maximum simulated drawdown in the UFA and the equivalent offset pumping in the UFA that would produce the same amount of drawdown. The maximum drawdown in the UFA ranged from 1.82 to 2.57 ft and the equivalent offset pumping in the UFA ranged from 199 to 278 gal/min.</p><p>The revised model reasonably depicts changes in groundwater levels resulting from pumping the LFA at Barbour Pointe at a rate of 750 gal/min. Results are limited, however, by the same model assumptions and design as the original model, and placement of boundaries and type of boundary used exert the greatest control on overall groundwater flow and interaquifer leakage in the system. Simulation results have improved regional characterization of the Floridan aquifer system, which could be used by State officials in evaluating requests for groundwater withdrawal from the LFA.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175085","collaboration":"Prepared in cooperation with Consolidated Utilities LLC","usgsCitation":"Cherry, G.S., and Clarke, J.S., 2017, Simulated effects of Lower Floridan aquifer pumping on the Upper Floridan aquifer at Barbour Pointe, Chatham County, Georgia: U.S. Geological Survey Scientific Investigations Report 2017–5085, 34 p., https://doi.org/10.3133/sir20175085.","productDescription":"Report: vi, 34 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-045187","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":346501,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5085/sir20175085.pdf","text":"Report","description":"SIR 2017-5085"},{"id":346500,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5085/coverthb.jpg"},{"id":346502,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VH5KZ1","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"MODFLOW grid for simulations used to evaluate the potential effect of Lower Floridan aquifer groundwater pumpage on the Upper Floridan aquifer at Barbour Pointe community in Chatham County, Georgia"}],"country":"United States","state":"Georgia","county":"Chatham County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.3922119140625,\n              32.09595459833164\n            ],\n            [\n              -81.13883972167969,\n              31.717654042594468\n            ],\n            [\n              -80.82847595214842,\n              32.02146689475617\n            ],\n            [\n              -81.17729187011719,\n              32.24823229303316\n            ],\n            [\n              -81.3922119140625,\n              32.09595459833164\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://sc.water.usgs.gov/\" data-mce-href=\"https://sc.water.usgs.gov/\">South Atlantic Water Science Center</a><br> U.S. Geological Survey<br> 720 Gracern Road<br> Stephenson Center, Suite 129<br> Columbia, SC 29210</p>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-10-26","noUsgsAuthors":false,"publicationDate":"2017-10-26","publicationStatus":"PW","scienceBaseUri":"5a07e869e4b09af898c8cb68","contributors":{"authors":[{"text":"Cherry, Gregory S. 0000-0002-5567-1587 gccherry@usgs.gov","orcid":"https://orcid.org/0000-0002-5567-1587","contributorId":1567,"corporation":false,"usgs":true,"family":"Cherry","given":"Gregory","email":"gccherry@usgs.gov","middleInitial":"S.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clarke, John S.","contributorId":196060,"corporation":false,"usgs":false,"family":"Clarke","given":"John S.","affiliations":[],"preferred":false,"id":709154,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70190840,"text":"sir20175103 - 2017 - Hydraulic and biological analysis of the passability of select fish species at the U.S. Geological Survey streamgaging weir at Blackwells Mills, New Jersey","interactions":[],"lastModifiedDate":"2024-03-04T19:40:56.663002","indexId":"sir20175103","displayToPublicDate":"2017-10-13T03:00:00","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":"2017-5103","title":"Hydraulic and biological analysis of the passability of select fish species at the U.S. Geological Survey streamgaging weir at Blackwells Mills, New Jersey","docAbstract":"<p>Recent efforts to advance river connectivity for the Millstone River watershed in New Jersey have led to the evaluation of a low-flow gauging weir that spans the full width of the river. The methods and results of a desktop modelling exercise were used to evaluate the potential ability of three anadromous fish species (<i>Alosa sapidissima</i> [American shad], <i>Alosa pseudoharengus</i> [alewife], and <i>Alosa aestivalis</i> [blueback herring]) to pass upstream over the U.S. Geological Survey Blackwells Mills streamgage (01402000) and weir on the Millstone River, New Jersey, at various streamflows, and to estimate the probability that the weir will be passable during the spring migratory season.</p><p>&nbsp;Based on data from daily fishway counts downstream from the Blackwells Mills streamgage and weir between 1996 and 2014, the general migratory period was defined as April 14 to May 28. Recorded water levels and flow data were used to theoretically estimate water depths and velocities over the weir, as well as flow exceedances occurring during the migratory period.</p><p>Results indicate that the weir is a potential depth barrier to fish passage when streamflows are below 200 cubic feet per second using a 1-body-depth criterion for American shad (the largest fish among the target species). Streamflows in that range occur on average 35 percent of the time during the migratory period. An increase of the depth criterion to 2 body depths causes the weir to become a possible barrier to passage when flows are below 400 cubic feet per second. Streamflows in that range occur on average 73 percent of the time during the migration season. Average cross-sectional velocities at several points along the weir do not seem to be limiting to the fish migration, but maximum theoretical velocities estimated without friction loss over the face of the weir could be potentially limiting.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175103","usgsCitation":"Haro, Alex, Mulligan, Kevin, Suro, T.P., Noreika, John, and McHugh, Amy, 2017, Hydraulic and biological analysis of the passability of select fish species at the U.S. Geological Survey streamgaging weir at Blackwells Mills, New Jersey: U.S. Geological Survey Scientific Investigations Report 2017–5103, 15 p., https://doi.org/10.3133/sir20175103.","productDescription":"viii, 15 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-082637","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":346487,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5103/coverthb.jpg"},{"id":346491,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5103/sir20175103.pdf","text":"Report","size":"3.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5103"}],"country":"United States","state":"New Jersey","otherGeospatial":"Millstone River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.66995239257812,\n              40.45060475430765\n            ],\n            [\n              -74.48867797851562,\n              40.45060475430765\n            ],\n            [\n              -74.48867797851562,\n              40.567545853080496\n            ],\n            [\n              -74.66995239257812,\n              40.567545853080496\n            ],\n            [\n              -74.66995239257812,\n              40.45060475430765\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/eesc\" data-mce-href=\"https://www.usgs.gov/centers/eesc\">Eastern Ecological Science Center</a><br>U.S. Geological Survey<br>11649 Leetown Road<br>Kearneysville, WV 25430<br>Email: <a href=\"mailto:gs_nea_lsc_publications@usgs.gov\" data-mce-href=\"mailto:gs_nea_lsc_publications@usgs.gov\">gs_nea_lsc_publications@usgs.gov</a></p>","tableOfContents":"<ul><li>Acknowledgments<br></li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Fish Passability During the Period of Migration</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2017-10-16","noUsgsAuthors":false,"publicationDate":"2017-10-16","publicationStatus":"PW","scienceBaseUri":"59e5c51be4b05fe04cd1c9ce","contributors":{"authors":[{"text":"Haro, Alexander J. 0000-0002-7188-9172 aharo@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-9172","contributorId":2917,"corporation":false,"usgs":true,"family":"Haro","given":"Alexander","email":"aharo@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":710635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mulligan, Kevin B. 0000-0002-3534-4239 kmulligan@usgs.gov","orcid":"https://orcid.org/0000-0002-3534-4239","contributorId":177024,"corporation":false,"usgs":true,"family":"Mulligan","given":"Kevin","email":"kmulligan@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":710636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Suro, Thomas P. 0000-0002-9476-6829 tsuro@usgs.gov","orcid":"https://orcid.org/0000-0002-9476-6829","contributorId":2841,"corporation":false,"usgs":true,"family":"Suro","given":"Thomas","email":"tsuro@usgs.gov","middleInitial":"P.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":710638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noreika, John 0000-0002-6637-5812 jnoreika@usgs.gov","orcid":"https://orcid.org/0000-0002-6637-5812","contributorId":167858,"corporation":false,"usgs":true,"family":"Noreika","given":"John","email":"jnoreika@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":712533,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McHugh, Amy R. 0000-0002-7745-9886 amchugh@usgs.gov","orcid":"https://orcid.org/0000-0002-7745-9886","contributorId":192882,"corporation":false,"usgs":true,"family":"McHugh","given":"Amy","email":"amchugh@usgs.gov","middleInitial":"R.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710637,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70191482,"text":"70191482 - 2017 - Climatic history of the northeastern United States during the past 3000 years","interactions":[],"lastModifiedDate":"2017-10-13T16:11:47","indexId":"70191482","displayToPublicDate":"2017-10-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"Climatic history of the northeastern United States during the past 3000 years","docAbstract":"<p>Many ecosystem processes that influence Earth system feedbacks, including vegetation growth, water and nutrient cycling, and disturbance regimes, are strongly influenced by multi-decadal to millennial-scale variations in climate that cannot be captured by instrumental climate observations. Paleoclimate information is therefore essential for understanding contemporary ecosystems and their potential trajectories under a variety of future climate conditions. With the exception of fossil pollen records, there are a limited number of northeastern US (NE US) paleoclimate archives that can provide constraints on its temperature and hydroclimate history. Moreover, the records that do exist have not been considered together. Tree-ring data indicate that the 20th century was one of the wettest of the past 500 years in the eastern US (Pederson et al., 2014), and lake-level records suggest it was one of the wettest in the Holocene (Newby et al., 2014); how such results compare with other available data remains unclear, however. Here we conduct a systematic review, assessment, and comparison of paleotemperature and paleohydrological proxies from the NE US for the last 3000 years. Regional temperature reconstructions are consistent with the long-term cooling trend (1000 BCE–1700 CE) evident in hemispheric-scale reconstructions, but hydroclimate reconstructions reveal new information, including an abrupt transition from wet to dry conditions around 550–750 CE. NE US paleo data suggest that conditions during the Medieval Climate Anomaly were warmer and drier than during the Little Ice Age, and drier than today. There is some evidence for an acceleration over the past century of a longer-term wetting trend in the NE US, and coupled with the abrupt shift from a cooling trend to a warming trend from increased greenhouse gases, may have wide-ranging implications for species distributions, ecosystem dynamics, and extreme weather events. More work is needed to gather paleoclimate data in the NE US, make inter-proxy comparisons, and improve estimates of uncertainty in the reconstructions.</p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/cp-2016-104","usgsCitation":"Marlon, J.R., Pederson, N., Nolan, C., Goring, S., Shuman, B., Robertson, A., Booth, R.K., Bartlein, P.J., Berke, M.A., Clifford, M., Cook, E., Dieffenbacher-Krall, A., Dietze, M.C., Hessl, A., Hubeny, J.B., Jackson, S.T., Marsicek, J., McLachlan, J.S., Mock, C.J., Moore, D.J., Nichols, J., Peteet, D.M., Schaefer, K., Trouet, V., Umbanhowar, C., Williams, J.W., and Yu, Z., 2017, Climatic history of the northeastern United States during the past 3000 years: Climate of the Past, v. 13, p. 1355-1379, https://doi.org/10.5194/cp-2016-104.","productDescription":"25 p.","startPage":"1355","endPage":"1379","ipdsId":"IP-080505","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":461389,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-2016-104","text":"Publisher Index Page"},{"id":346607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"13","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e1d097e4b05fe04cd117a0","contributors":{"authors":[{"text":"Marlon, Jennifer R.","contributorId":23432,"corporation":false,"usgs":true,"family":"Marlon","given":"Jennifer","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":712391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pederson, Neil","contributorId":149422,"corporation":false,"usgs":false,"family":"Pederson","given":"Neil","email":"","affiliations":[{"id":17731,"text":"Research Scientist, Tree Ring Laboratory, Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":712392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nolan, Connor","contributorId":197051,"corporation":false,"usgs":false,"family":"Nolan","given":"Connor","affiliations":[],"preferred":false,"id":712393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goring, Simon","contributorId":167180,"corporation":false,"usgs":false,"family":"Goring","given":"Simon","affiliations":[],"preferred":false,"id":712491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shuman, Bryan","contributorId":99039,"corporation":false,"usgs":true,"family":"Shuman","given":"Bryan","affiliations":[],"preferred":false,"id":712492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robertson, Ann","contributorId":197075,"corporation":false,"usgs":false,"family":"Robertson","given":"Ann","email":"","affiliations":[],"preferred":false,"id":712493,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Booth, Robert K.","contributorId":17177,"corporation":false,"usgs":true,"family":"Booth","given":"Robert","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":712494,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bartlein, Patrick J.","contributorId":106879,"corporation":false,"usgs":true,"family":"Bartlein","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":712495,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Berke, Melissa A.","contributorId":197076,"corporation":false,"usgs":false,"family":"Berke","given":"Melissa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712496,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Clifford, Michael","contributorId":197077,"corporation":false,"usgs":false,"family":"Clifford","given":"Michael","email":"","affiliations":[],"preferred":false,"id":712497,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cook, Edward","contributorId":197078,"corporation":false,"usgs":false,"family":"Cook","given":"Edward","affiliations":[],"preferred":false,"id":712498,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Dieffenbacher-Krall, Ann","contributorId":197079,"corporation":false,"usgs":false,"family":"Dieffenbacher-Krall","given":"Ann","email":"","affiliations":[],"preferred":false,"id":712499,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dietze, Michael C.","contributorId":15908,"corporation":false,"usgs":true,"family":"Dietze","given":"Michael","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":712500,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hessl, Amy","contributorId":50594,"corporation":false,"usgs":true,"family":"Hessl","given":"Amy","affiliations":[],"preferred":false,"id":712501,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hubeny, J. Bradford","contributorId":197080,"corporation":false,"usgs":false,"family":"Hubeny","given":"J.","email":"","middleInitial":"Bradford","affiliations":[],"preferred":false,"id":712502,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Jackson, Stephen T. 0000-0002-1487-4652 stjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-1487-4652","contributorId":344,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen","email":"stjackson@usgs.gov","middleInitial":"T.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":560,"text":"South Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":712503,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Marsicek, Jeremiah","contributorId":197081,"corporation":false,"usgs":false,"family":"Marsicek","given":"Jeremiah","email":"","affiliations":[],"preferred":false,"id":712504,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"McLachlan, Jason S.","contributorId":167179,"corporation":false,"usgs":false,"family":"McLachlan","given":"Jason","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":712505,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Mock, Cary J.","contributorId":87323,"corporation":false,"usgs":true,"family":"Mock","given":"Cary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":712506,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Moore, David J. P.","contributorId":169810,"corporation":false,"usgs":false,"family":"Moore","given":"David","email":"","middleInitial":"J. P.","affiliations":[],"preferred":false,"id":712507,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Nichols, Jonathan M.","contributorId":45945,"corporation":false,"usgs":true,"family":"Nichols","given":"Jonathan M.","affiliations":[],"preferred":false,"id":712508,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Peteet, Dorothy M. 0000-0003-3029-7506","orcid":"https://orcid.org/0000-0003-3029-7506","contributorId":147523,"corporation":false,"usgs":false,"family":"Peteet","given":"Dorothy","email":"","middleInitial":"M.","affiliations":[{"id":16858,"text":"Goddard Institute","active":true,"usgs":false}],"preferred":false,"id":712509,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Schaefer, Kevin","contributorId":63323,"corporation":false,"usgs":true,"family":"Schaefer","given":"Kevin","affiliations":[],"preferred":false,"id":712510,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Trouet, Valerie","contributorId":197082,"corporation":false,"usgs":false,"family":"Trouet","given":"Valerie","email":"","affiliations":[],"preferred":false,"id":712511,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Umbanhowar, Charles","contributorId":197083,"corporation":false,"usgs":false,"family":"Umbanhowar","given":"Charles","affiliations":[],"preferred":false,"id":712512,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Williams, John W.","contributorId":16761,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":712513,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Yu, Zicheng 0000-0003-2358-2712","orcid":"https://orcid.org/0000-0003-2358-2712","contributorId":147521,"corporation":false,"usgs":false,"family":"Yu","given":"Zicheng","email":"","affiliations":[{"id":16857,"text":"Lehigh Univ.","active":true,"usgs":false}],"preferred":false,"id":712514,"contributorType":{"id":1,"text":"Authors"},"rank":27}]}}
,{"id":70191489,"text":"70191489 - 2017 - Revision of the jawfish genus Lonchopisthus with description of a new Atlantic species (Teleostei: Opistognathidae)","interactions":[],"lastModifiedDate":"2017-10-13T15:48:27","indexId":"70191489","displayToPublicDate":"2017-10-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5514,"text":"Journal of the Ocean Science Foundation","active":true,"publicationSubtype":{"id":10}},"title":"Revision of the jawfish genus Lonchopisthus with description of a new Atlantic species (Teleostei: Opistognathidae)","docAbstract":"<p><span>Synonymies, diagnoses, descriptions, illustrations, an identification key, and meristic frequency tables are provided for all species of Lonchopisthus. Most of the skeletal anatomy of L. higmani is also illustrated. A new jawfish, Lonchopisthus ancistrus n. sp., is described from the Gulf of Mexico and off Honduras based on 21 specimens 41–89 mm SL. The new species differs from other congeners by the following combination of characters: the posterior end of the maxilla strongly hooked; the membrane connecting the maxilla and premaxilla and the inner membrane covering the posterior part of the dentary pale; segmented dorsal-fin rays 11–13, with unbranched rays 2–5; longitudinal body-scale rows 33–39; and very long pelvic fins, 39.4–75.3% SL. Lonchopisthus lemur (and its synonym L. meadi) shares most characters with L. ancistrus, but differs in having shorter pelvic fins, 19.2–29.9% SL; fewer longitudinal body-scale rows, 26–33; and 5 infraorbitals (vs. 4). Both are relatively deep-water species, occurring from 100 m to at least 375 m (vs. 3–139 m in the other species). Lonchopisthus micrognathus is unique in having no branched caudal-fin rays at any size and the middle caudal-fin rays with free tips that may be used to maintain tactile contact with the substrate while hovering over its burrow. The western Atlantic Lonchopisthus higmani and eastern Pacific L. sinuscalifornicus are sister species that differ from the other Atlantic species in having the posterior end of the maxilla with a notch instead of a strong hook, the opercle with a large dark blotch, and one supraneural (vs. no supraneural).</span></p>","language":"English","publisher":"Ocean Science Foundation","doi":"10.5281/zenodo.1001056","usgsCitation":"Smith-Vaniz, W.F., and Walsh, S.J., 2017, Revision of the jawfish genus Lonchopisthus with description of a new Atlantic species (Teleostei: Opistognathidae): Journal of the Ocean Science Foundation, v. 28, p. 52-89, https://doi.org/10.5281/zenodo.1001056.","productDescription":"38 p.","startPage":"52","endPage":"89","ipdsId":"IP-090314","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":346603,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e1d095e4b05fe04cd11796","contributors":{"authors":[{"text":"Smith-Vaniz, William F.","contributorId":152526,"corporation":false,"usgs":false,"family":"Smith-Vaniz","given":"William","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":712422,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, Stephen J. 0000-0002-1009-8537 swalsh@usgs.gov","orcid":"https://orcid.org/0000-0002-1009-8537","contributorId":1456,"corporation":false,"usgs":true,"family":"Walsh","given":"Stephen","email":"swalsh@usgs.gov","middleInitial":"J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":712421,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70189709,"text":"sir20175074 - 2017 - Estimation of the groundwater resources of the bedrock aquifers at the Kettle Moraine Springs State Fish Hatchery, Sheboygan County, Wisconsin","interactions":[],"lastModifiedDate":"2017-10-12T11:27:22","indexId":"sir20175074","displayToPublicDate":"2017-10-12T11:00:00","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":"2017-5074","title":"Estimation of the groundwater resources of the bedrock aquifers at the Kettle Moraine Springs State Fish Hatchery, Sheboygan County, Wisconsin","docAbstract":"<p>Groundwater resources information was needed to understand regional aquifer systems and water available to wells and springs for rearing important Lake Michigan fish species at the Kettle Moraine Springs State Fish Hatchery in Sheboygan County, Wisconsin. As a basis for estimating the groundwater resources available, an existing groundwater-flow model was refined, and new groundwater-flow models were developed for the Kettle Moraine Springs State Fish Hatchery area using the U.S. Geological Survey (USGS) finite-difference code MODFLOW. This report describes the origin and construction of these groundwater-flow models and their use in testing conceptual models and simulating the hydrogeologic system.</p><p>The study area is in the Eastern Ridges and Lowlands geographical province of Wisconsin, and the hatchery property is situated on the southeastern edge of the Kettle Moraine, a north-south trending topographic high of glacial origin. The bedrock units underlying the study area consist of Cambrian, Ordovician, and Silurian units of carbonate and siliciclastic lithology. In the Sheboygan County area, the sedimentary bedrock sequence reaches a thickness of as much as about 1,600 feet (ft).</p><p>Two aquifer systems are present at the Kettle Moraine Springs State Fish Hatchery. A shallow system is made up of Silurian bedrock, consisting chiefly of dolomite, overlain by unconsolidated Quaternary-age glacial deposits. The glacial deposits of this aquifer system are the typical source of water to local springs, including the springs that have historically supplied the hatchery. The shallow aquifer system, therefore, consists of the unconsolidated glacial aquifer and the underlying bedrock Silurian aquifer. Most residential wells in the area draw from the Silurian aquifer. A deeper confined aquifer system is made up of Cambrian- and Ordovician-age bedrock units including sandstone formations. Because of its depth, very few wells are completed in the Cambrian-Ordovician aquifer system (COAS) near the Kettle Moraine Springs State Fish Hatchery.</p><p>Three groundwater-flow models were used to estimate the water resources available to the hatchery from bedrock aquifers under selected scenarios of well placement and seasonal water requirements and subject to constraints on the effects of pumping on neighboring wells, local springs, and creeks. Model input data (recharge, water withdrawal, and boundary conditions) for these models were compiled from a number of data and information sources.</p><p>The first model, named the “KMS model,” (KMS stands for Kettle Moraine Springs) is an inset model derived from a published USGS regional Lake Michigan Basin model and was constructed to simulate groundwater pumping from the semiconfined Silurian aquifer. The second model, named the “Pumping Test model,” was constructed to evaluate an aquifer pumping test conducted in the COAS as part of this project. The Pumping Test model was also used to simulate the local effects of 20 years of groundwater pumping from this deep bedrock aquifer for future hatchery operations. The third model, named the “LMB modified model,” is a version of the published Lake Michigan Basin (LMB) model that was modified with aquifer parameters refined in an area around the hatchery (approximately a 5-mile radius circle, corresponding to the area stressed by the aquifer pumping test). This LMB modified model was applied to evaluate regional effects of pumping from the confined COAS.</p><p>The available Silurian aquifer groundwater resource was estimated using the KMS model with three scenarios—named “AllConstraints,” “Constraints2,” and “Constraints3”—that specified local water-level and flow constraints such as drawdown at nearby household wells, water levels inside pumping well boreholes, and flow in local streams and springs. Each scenario utilized the MODFLOW Groundwater Management Process (GWM) to select three locations from six candidate locations that provided the greatest combined flow while satisfying the constraints. The three constraint scenarios provided estimates of 430 gallons per minute (gal/min), 480 gal/min, and 520 gal/min pumping from three wells—AllConstraints, Constraints2, and Constraints3, respectively. The same three wells were selected for the scenarios that estimated 480 gal/min and 520 gal/min; the scenario that estimated 430 gal/min shared two of these same wells, but the third selected well was different.</p><p>The available COAS groundwater resource was estimated by two scenarios with each conducted over a period of 20 years with the Pumping Test model and the LMB modified model<i>. </i>The Pumping Test model was used to simulate local effects of pumping, and the LMB modified model was used to simulate regional effects of pumping. The scenarios simulate a range of total and seasonal pumping rates potentially linked to site activities. Scenario 1 simulates two wells completed in the Cambrian-Ordovician aquifer system, each pumping for 8 months at 300 gal/min, followed by pumping for 4 months at 600 gal/min. The average yearly pumping rate of Scenario 1 is 800 gal/min. Scenario 2 simulates three wells completed in the Cambrian-Ordovician aquifer system pumping for 8 months at 200 gal/min, followed by pumping for 4 months at 500 gal/min. The average yearly pumping rate of Scenario 2 is 900 gal/min. The Pumping Test model simulations confirmed that drawdown in the boreholes of the pumping wells at the selected 2-well or 3-well rates will meet the desired condition that the pumping water level remains at least 100 ft above the highest Cambrian-Ordovician unit open to the well.</p><p>The LMB modified model was used to evaluate the regional drawdown of the pumping from the confined COAS under the same 2-well and 3-well scenarios. At the nearest known existing COAS well, Campbellsport production well #4, the simulated drawdown for Scenario 1 after 20 years of cyclical pumping with two pumping wells averaging a total of 800 gal/min is 16.9 ft, whereas the simulated drawdown for Scenario 2 after 20 years of pumping with three pumping wells averaging a total of 900 gal/min is 19.0 ft. The total deep aquifer thickness at the Campbellsport location is on the order of 620 ft, meaning that the simulated drawdown for either scenario is about 3 percent of the confined aquifer thickness.</p><p>The models developed as part of this project are archived in the project data release. The archive includes the model input and output files as well as MODFLOW source code and executables. (<a href=\"https://doi.org/10.5066/F77S7KW2\" data-mce-href=\"https://doi.org/10.5066/F77S7KW2\">Haserodt and others, 2017</a>).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175074","collaboration":"Prepared in cooperation with the Fisheries Management Program of the Wisconsin Department of Natural Resources","usgsCitation":"Dunning, C.P., Feinstein, D.T., Buchwald, C.A., Hunt, R.J., and Haserodt, M.J., 2017, Estimation of the groundwater resources of the bedrock aquifers at the Kettle Moraine Springs State Fish Hatchery, Sheboygan County, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2017–5074, 104 p., https://doi.org/10.3133/sir20175074.","productDescription":"Report: ix, 104 p.; Data Release","numberOfPages":"118","onlineOnly":"Y","ipdsId":"IP-079387","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":346498,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5074/sir20175074.pdf","text":"Report","size":"21.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5074"},{"id":346497,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5074/coverthb.jpg"},{"id":346499,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77S7KW2","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"GWM-2005, MODFLOW-2005, MODFLOW-NWT, and SEAWAT-2000 groundwater flow models of the Bedrock Aquifers at the Kettle Moraine Springs State Fish Hatchery, Sheboygan County, Wisconsin"}],"country":"United States","state":"Wisconsin","county":"Sheboygan County","otherGeospatial":"Kettle Moraine Springs State Fish Hatchery","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.0778,\n              43.5944\n            ],\n            [\n              -88.0889,\n              43.5944\n            ],\n            [\n              -88.0889,\n              43.6167\n            ],\n            [\n              -88.0778,\n              43.6167\n            ],\n            [\n              -88.0778,\n              43.5944\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:jfwalker@usgs.gov\" target=\"_blank\" data-mce-href=\"mailto:jfwalker@usgs.gov\">Director</a>,&nbsp;<a href=\"http://wi.water.usgs.gov/\" target=\"_blank\" data-mce-href=\"http://wi.water.usgs.gov/\">Wisconsin Water Science Center</a><br> U.S. Geological Survey<br> 8505 Research Way<br> Middleton, WI 53562</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Approach</li><li>Data Collection</li><li>Description of the Groundwater-Flow Models</li><li>Estimation of Water Supply from the Silurian Aquifer</li><li>Estimation of Water Supply from the Cambrian-Ordovician Aquifer System</li><li>Limitations of Analysis</li><li>Possible Future Work</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendix 1. Construction of a Test Production Well and a Monitoring Well in the Cambrian-Ordovician Aquifer System</li><li>Appendix 2. Design and Performance of Aquifer Pumping Test in the Cambrian-Ordovician Aquifer System</li><li>Appendix 3 .Development of the Pumping Test Model and Interpretation of the Cambrian- Ordovician Aquifer System Pumping Test</li><li>Appendix 4.Development of the Kettle Moraine Springs (KMS) Model to Support Analysis of Silurian Aquifer Water Supply</li><li>Appendix 5.Application of the Pumping Test (PT) Model and the Lake Michigan Basin (LMB) Modified Model to Cambrian-Ordovician Aquifer System Water Supply Scenarios</li><li>Appendix 6.Application of Kettle Moraine Springs (KMS) Model to Silurian Aquifer Water Supply Scenarios</li></ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2017-10-12","noUsgsAuthors":false,"publicationDate":"2017-10-12","publicationStatus":"PW","scienceBaseUri":"59e07f2de4b05fe04ccfccf7","contributors":{"authors":[{"text":"Dunning, Charles 0000-0002-0597-2058 cdunning@usgs.gov","orcid":"https://orcid.org/0000-0002-0597-2058","contributorId":174864,"corporation":false,"usgs":true,"family":"Dunning","given":"Charles","email":"cdunning@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feinstein, Daniel T. 0000-0003-1151-2530 dtfeinst@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-2530","contributorId":1907,"corporation":false,"usgs":true,"family":"Feinstein","given":"Daniel","email":"dtfeinst@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buchwald, Cheryl A. 0000-0001-8968-5023 cabuchwa@usgs.gov","orcid":"https://orcid.org/0000-0001-8968-5023","contributorId":1943,"corporation":false,"usgs":true,"family":"Buchwald","given":"Cheryl","email":"cabuchwa@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705886,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haserodt, Megan J. 0000-0002-8304-090X mhaserodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8304-090X","contributorId":174791,"corporation":false,"usgs":true,"family":"Haserodt","given":"Megan","email":"mhaserodt@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705887,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70189991,"text":"ofr20171099 - 2017 - Watershed Data Management (WDM) database for West Branch DuPage River streamflow simulation, DuPage County, Illinois, January 1, 2007, through September 30, 2013","interactions":[],"lastModifiedDate":"2017-10-16T13:43:05","indexId":"ofr20171099","displayToPublicDate":"2017-10-12T03:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1099","title":"Watershed Data Management (WDM) database for West Branch DuPage River streamflow simulation, DuPage County, Illinois, January 1, 2007, through September 30, 2013","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the DuPage County Stormwater Management Department, maintains a database of hourly meteorological and hydrologic data for use in a near real-time streamflow simulation system. This system is used in the management and operation of reservoirs and other flood-control structures in the West Branch DuPage River watershed in DuPage County, Illinois. The majority of the precipitation data are collected from a tipping-bucket rain-gage network located in and near DuPage County. The other meteorological data (air temperature, dewpoint temperature, wind speed, and solar radiation) are collected at Argonne National Laboratory in Argonne, Ill. Potential evapotranspiration is computed from the meteorological data using the computer program LXPET (Lamoreux Potential Evapotranspiration). The hydrologic data (water-surface elevation [stage] and discharge) are collected at U.S.Geological Survey streamflow-gaging stations in and around DuPage County. These data are stored in a Watershed Data Management (WDM) database.</p><p>This report describes a version of the WDM database that is quality-assured and quality-controlled annually to ensure datasets are complete and accurate. This database is named WBDR13.WDM. It contains data from January 1, 2007, through September 30, 2013. Each precipitation dataset may have time periods of inaccurate data. This report describes the methods used to estimate the data for the periods of missing, erroneous, or snowfall-affected data and thereby improve the accuracy of these data. The other meteorological datasets are described in detail in Over and others (2010), and the hydrologic datasets in the database are fully described in the online USGS annual water data reports for Illinois (U.S. Geological Survey, 2016) and, therefore, are described in less detail than the precipitation datasets in this report.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171099","collaboration":"Prepared in cooperation with DuPage County Stormwater Management Department","usgsCitation":"Bera, Maitreyee, 2017, Watershed Data Management (WDM) database for West Branch DuPage River streamflow simulation, DuPage County, Illinois, January 1, 2007, through September 30, 2013: U.S. Geological Survey Open-File Report 2017–1099, 39 p., https://doi.org/10.3133/ofr20171099.","productDescription":"Report: v, 39 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-078980","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":346557,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1099/ofr20171099.pdf","text":"Report","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1099"},{"id":346556,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1099/coverthb.jpg"},{"id":346558,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71Z42M0","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Watershed Data Management (WDM) Database (WBDR13.WDM) for West Branch DuPage River Streamflow Simulation, DuPage County, Illinois, January 1, 2007, through September 30, 2013"}],"country":"United States","state":"Illinois","county":"DuPage County","otherGeospatial":"West Branch DuPage River Watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.28338623046875,\n              41.70214000452559\n            ],\n            [\n              -87.99087524414062,\n              41.70214000452559\n            ],\n            [\n              -87.99087524414062,\n              41.99726342796974\n            ],\n            [\n              -88.28338623046875,\n              41.99726342796974\n            ],\n            [\n              -88.28338623046875,\n              41.70214000452559\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:krichards@usgs.gov\" data-mce-href=\"mailto:krichards@usgs.gov\">Director</a>, <a href=\"https://il.water.usgs.gov/\" data-mce-href=\"https://il.water.usgs.gov/\">Illinois Water Science Center</a><br> U.S. Geological Survey<br> 405 North Goodwin Avenue<br> Urbana, IL 61801-2347</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Watershed Data Management (WDM) Database</li><li>Precipitation Data</li><li>Other Meteorological Data</li><li>Hydrologic Data</li><li>Appendix 1. Dataset Attributes for the WBDR13.WDM Watershed Data Management Database</li><li>Appendix 2. Descriptions of Missing Data Periods and Estimated Days in the Precipitation, Stage, and Discharge Data in the WBDR13.WDM Watershed Data Management Database</li></ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2017-10-16","noUsgsAuthors":false,"publicationDate":"2017-10-16","publicationStatus":"PW","scienceBaseUri":"59e5c51be4b05fe04cd1c9d0","contributors":{"authors":[{"text":"Bera, Maitreyee 0000-0002-3968-1961 mbera@usgs.gov","orcid":"https://orcid.org/0000-0002-3968-1961","contributorId":5450,"corporation":false,"usgs":true,"family":"Bera","given":"Maitreyee","email":"mbera@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":707018,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70191435,"text":"70191435 - 2017 - Building capacity in biodiversity monitoring at the global scale","interactions":[],"lastModifiedDate":"2017-10-12T09:52:12","indexId":"70191435","displayToPublicDate":"2017-10-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1006,"text":"Biodiversity and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Building capacity in biodiversity monitoring at the global scale","docAbstract":"<p><span>Human-driven global change is causing ongoing declines in biodiversity worldwide. In order to address these declines, decision-makers need accurate assessments of the status of and pressures on biodiversity. However, these are heavily constrained by incomplete and uneven spatial, temporal and taxonomic coverage. For instance, data from regions such as Europe and North America are currently used overwhelmingly for large-scale biodiversity assessments due to lesser availability of suitable data from other, more biodiversity-rich, regions. These data-poor regions are often those experiencing the strongest threats to biodiversity, however. There is therefore an urgent need to fill the existing gaps in global biodiversity monitoring. Here, we review current knowledge on best practice in capacity building for biodiversity monitoring and provide an overview of existing means to improve biodiversity data collection considering the different types of biodiversity monitoring data. Our review comprises insights from work in Africa, South America, Polar Regions and Europe; in government-funded, volunteer and citizen-based monitoring in terrestrial, freshwater and marine ecosystems. The key steps to effectively building capacity in biodiversity monitoring are: identifying monitoring questions and aims; identifying the key components, functions, and processes to monitor; identifying the most suitable monitoring methods for these elements, carrying out monitoring activities; managing the resultant data; and interpreting monitoring data. Additionally, biodiversity monitoring should use multiple approaches including extensive and intensive monitoring through volunteers and professional scientists but also harnessing new technologies. Finally, we call on the scientific community to share biodiversity monitoring data, knowledge and tools to ensure the accessibility, interoperability, and reporting of biodiversity data at a global scale.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10531-017-1388-7","usgsCitation":"Schmeller, D.S., Böhm, M., Arvanitidis, C., Barber-Meyer, S., Brummitt, N., Chandler, M., Chatzinikolaou, E., Costello, M.J., Ding, H., Garcia-Moreno, J., Gill, M.J., Haase, P., Jones, M., Juillard, R., Magnusson, W.E., Martin, C.S., McGeoch, M.A., Mihoub, J., Pettorelli, N., Proença, V., Peng, C., Regan, E., Schmiedel, U., Simsika, J.P., Weatherdon, L., Waterman, C., Xu, H., and Belnap, J., 2017, Building capacity in biodiversity monitoring at the global scale: Biodiversity and Conservation, v. 26, no. 12, p. 2765-2790, https://doi.org/10.1007/s10531-017-1388-7.","productDescription":"26 p.","startPage":"2765","endPage":"2790","ipdsId":"IP-058340","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469447,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://discovery.ucl.ac.uk/id/eprint/1558305","text":"External Repository"},{"id":346547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-20","publicationStatus":"PW","scienceBaseUri":"59e07f2fe4b05fe04ccfcd09","contributors":{"authors":[{"text":"Schmeller, Dirk S.","contributorId":147645,"corporation":false,"usgs":false,"family":"Schmeller","given":"Dirk","email":"","middleInitial":"S.","affiliations":[{"id":16875,"text":"(1)Dept of Conservation Biology, Helmholtz Centre for Environmental Research – UFZ, Permoserstrasse 15, 04318 Leipzig, Germany;","active":true,"usgs":false}],"preferred":false,"id":712226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Böhm, Monika","contributorId":196999,"corporation":false,"usgs":false,"family":"Böhm","given":"Monika","affiliations":[],"preferred":false,"id":712228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arvanitidis, Christos","contributorId":196998,"corporation":false,"usgs":false,"family":"Arvanitidis","given":"Christos","email":"","affiliations":[],"preferred":false,"id":712227,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barber-Meyer, Shannon 0000-0002-3048-2616 sbarber-meyer@usgs.gov","orcid":"https://orcid.org/0000-0002-3048-2616","contributorId":191875,"corporation":false,"usgs":true,"family":"Barber-Meyer","given":"Shannon","email":"sbarber-meyer@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":712244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brummitt, Neil","contributorId":147648,"corporation":false,"usgs":false,"family":"Brummitt","given":"Neil","email":"","affiliations":[{"id":16878,"text":"Department of Life Sciences, The Natural History Museum, Cromwell Road, South Kensington, London SW7 5BD, UK","active":true,"usgs":false}],"preferred":false,"id":712229,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chandler, Mark","contributorId":197010,"corporation":false,"usgs":false,"family":"Chandler","given":"Mark","affiliations":[],"preferred":false,"id":712245,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chatzinikolaou, Eva","contributorId":197000,"corporation":false,"usgs":false,"family":"Chatzinikolaou","given":"Eva","email":"","affiliations":[],"preferred":false,"id":712230,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Costello, Mark John","contributorId":146661,"corporation":false,"usgs":false,"family":"Costello","given":"Mark","email":"","middleInitial":"John","affiliations":[{"id":13376,"text":"The University of Auckland","active":true,"usgs":false}],"preferred":false,"id":712232,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ding, Hui","contributorId":197002,"corporation":false,"usgs":false,"family":"Ding","given":"Hui","email":"","affiliations":[],"preferred":false,"id":712233,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Garcia-Moreno, Jaime","contributorId":197003,"corporation":false,"usgs":false,"family":"Garcia-Moreno","given":"Jaime","email":"","affiliations":[],"preferred":false,"id":712234,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gill, Michael J.","contributorId":131121,"corporation":false,"usgs":false,"family":"Gill","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":712235,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Haase, Peter","contributorId":197004,"corporation":false,"usgs":false,"family":"Haase","given":"Peter","email":"","affiliations":[],"preferred":false,"id":712236,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Jones, Miranda","contributorId":197016,"corporation":false,"usgs":false,"family":"Jones","given":"Miranda","email":"","affiliations":[],"preferred":false,"id":712272,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Juillard, Romain","contributorId":197005,"corporation":false,"usgs":false,"family":"Juillard","given":"Romain","email":"","affiliations":[],"preferred":false,"id":712237,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Magnusson, William E.","contributorId":147653,"corporation":false,"usgs":false,"family":"Magnusson","given":"William","email":"","middleInitial":"E.","affiliations":[{"id":16882,"text":"Instituto Nacional de Pesquisas da Amazônia, Caixa Postal 2223, 69080-971 Manaus AM, Brazil","active":true,"usgs":false}],"preferred":false,"id":712273,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Martin, Corinne S.","contributorId":197017,"corporation":false,"usgs":false,"family":"Martin","given":"Corinne","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":712274,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"McGeoch, Melodie A.","contributorId":85047,"corporation":false,"usgs":true,"family":"McGeoch","given":"Melodie","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712275,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Mihoub, Jean-Baptiste","contributorId":197018,"corporation":false,"usgs":false,"family":"Mihoub","given":"Jean-Baptiste","email":"","affiliations":[],"preferred":false,"id":712276,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Pettorelli, Nathalie","contributorId":197006,"corporation":false,"usgs":false,"family":"Pettorelli","given":"Nathalie","email":"","affiliations":[],"preferred":false,"id":712238,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Proença, Vânia","contributorId":147656,"corporation":false,"usgs":false,"family":"Proença","given":"Vânia","affiliations":[{"id":16885,"text":"Center for Innovation, Technology and Policy Research, ACAE-DEM, Instituto Superior Técnico, University of Lisbon, Avenida Rovisco Pais, 1, 1049-001 Lisboa, Portugal","active":true,"usgs":false}],"preferred":false,"id":712277,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Peng, 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China","active":true,"usgs":false}],"preferred":false,"id":712239,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Regan, Eugenie","contributorId":197019,"corporation":false,"usgs":false,"family":"Regan","given":"Eugenie","email":"","affiliations":[],"preferred":false,"id":712278,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Schmiedel, Ute","contributorId":197007,"corporation":false,"usgs":false,"family":"Schmiedel","given":"Ute","email":"","affiliations":[],"preferred":false,"id":712240,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Simsika, John P.","contributorId":197008,"corporation":false,"usgs":false,"family":"Simsika","given":"John","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":712241,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Weatherdon, Lauren","contributorId":197020,"corporation":false,"usgs":false,"family":"Weatherdon","given":"Lauren","affiliations":[],"preferred":false,"id":712279,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Waterman, Carly","contributorId":197021,"corporation":false,"usgs":false,"family":"Waterman","given":"Carly","email":"","affiliations":[],"preferred":false,"id":712280,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Xu, Haigen","contributorId":197009,"corporation":false,"usgs":false,"family":"Xu","given":"Haigen","email":"","affiliations":[],"preferred":false,"id":712243,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":712225,"contributorType":{"id":1,"text":"Authors"},"rank":28}]}}
,{"id":70191364,"text":"ofr20171090 - 2017 - Description of chronostratigraphic units preserved as channel deposits and geomorphic processes following a basin-scale disturbance by a wildfire in Colorado","interactions":[],"lastModifiedDate":"2017-10-12T10:18:15","indexId":"ofr20171090","displayToPublicDate":"2017-10-11T19:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1090","title":"Description of chronostratigraphic units preserved as channel deposits and geomorphic processes following a basin-scale disturbance by a wildfire in Colorado","docAbstract":"<p>The consequence of a 1996 wildfire disturbance and a subsequent high-intensity summer convective rain storm (about 110 millimeters per hour) was the deposition of a sediment superslug in the Spring Creek basin (26.8 square kilometers) of the Front Range Mountains in Colorado. Spring Creek is a tributary to the South Platte River upstream from Strontia Springs Reservoir, which supplies domestic water for the cities of Denver and Aurora. Changes in a superslug were monitored over the course of 18 years (1996–2014) by repeat surveys at 18 channel cross sections spaced at nearly equal intervals along a 1,500-meter study reach and by a time series of photographs of each cross section. Surveys were not repeated at regular time intervals but after major changes caused by different geomorphic processes. The focus of this long-term study was to understand the evolution and internal alluvial architecture of chronostratigraphic units (defined as the volume of sediment deposited between two successive surveys), and the preservation or storage of these units in the superslug. The data are presented as a series of 18 narratives (one for each cross section) that summarize the changes, illustrate these changes with photographs, and provide a preservation plot showing the amount of each chronostratigraphic unit still remaining in June 2014.</p><p>The most significant hydrologic change after the wildfire was an exponential decrease in peak discharge of flash floods caused by summer convective rain storms. In response to these hydrologic changes, all 18 locations went through an aggradation phase, an incision phase, and finally a stabilization phase. However, the architecture of the chronostratigraphic units differs from cross section to cross section, and units are characterized by either a laminar, fragmented, or hybrid alluvial architecture. In response to the decrease in peak-flood discharge and the increase in hillslope and riparian vegetation, Spring Creek abandoned many of the nearly horizontal erosional and depositional surfaces and left a landscape consisting of a series of cut-and-fill terraces as a legacy of this wildfire disturbance.&nbsp;</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171090","usgsCitation":"Moody, J.A., and Martin, D.A., 2017, Description of chronostratigraphic units preserved as channel deposits and geomorphic processes following a basin-scale disturbance by a wildfire in Colorado: U.S. Geological Survey Open-File Report 2017–1090, 73 p., https://doi.org/10.3133/ofr20171090.","productDescription":"vi, 73 p.","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-081971","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":346458,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1090/coverthb.jpg"},{"id":346459,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1090/ofr20171090.pdf","text":"Report","size":"43.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1090"}],"country":"United States","state":"Colorado","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.0455322265625,\n              38.89958342598271\n            ],\n            [\n              -104.600830078125,\n              38.89958342598271\n            ],\n            [\n              -104.600830078125,\n              39.50827899034114\n            ],\n            [\n              -106.0455322265625,\n              39.50827899034114\n            ],\n            [\n              -106.0455322265625,\n              38.89958342598271\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Branch Chief, Hydrodynamics Branch <br>Earth System Processes Division<br>U.S. Geological Survey<br>1400 Independence Road<br>Rolla, MO 65401</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Description of Chronostratigraphic Units and Geomorphic Processes</li><li>Acknowledgments</li><li>References Cited</li><li>Appendix 1. Universal Transverse Mercator (UTM) Coordinates for Cross Sections in Spring Creek</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2017-10-11","noUsgsAuthors":false,"publicationDate":"2017-10-11","publicationStatus":"PW","scienceBaseUri":"59defbafe4b05fe04ccd3d37","contributors":{"authors":[{"text":"Moody, John A. 0000-0003-2609-364X jamoody@usgs.gov","orcid":"https://orcid.org/0000-0003-2609-364X","contributorId":771,"corporation":false,"usgs":true,"family":"Moody","given":"John","email":"jamoody@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":712095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":1900,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":712096,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70190213,"text":"ofr20171108 - 2017 - Compilation of streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages","interactions":[],"lastModifiedDate":"2017-10-16T13:37:19","indexId":"ofr20171108","displayToPublicDate":"2017-10-10T03:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1108","title":"Compilation of streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages","docAbstract":"<p>Streamflow statistics are needed by decision makers for many planning, management, and design activities. The U.S. Geological Survey (USGS) StreamStats Web application provides convenient access to streamflow statistics for many streamgages by accessing the underlying StreamStatsDB database. In 2016, non-interpretive streamflow statistics were compiled for streamgages located throughout the Nation and stored in StreamStatsDB for use with StreamStats and other applications. Two previously published USGS computer programs that were designed to help calculate streamflow statistics were updated to better support StreamStats as part of this effort. These programs are named “GNWISQ” (Get National Water Information System Streamflow (Q) files), updated to version 1.1.1, and “QSTATS” (Streamflow (Q) Statistics), updated to version 1.1.2.</p><p>Statistics for 20,438 streamgages that had 1 or more complete years of record during water years 1901 through 2015 were calculated from daily mean streamflow data; 19,415 of these streamgages were within the conterminous United States. About 89 percent of the 20,438 streamgages had 3 or more years of record, and about 65 percent had 10 or more years of record. Drainage areas of the 20,438 streamgages ranged from 0.01 to 1,144,500 square miles. The magnitude of annual average streamflow yields (streamflow per square mile) for these streamgages varied by almost six orders of magnitude, from 0.000029 to 34 cubic feet per second per square mile. About 64 percent of these streamgages did not have any zero-flow days during their available period of record. The 18,122 streamgages with 3 or more years of record were included in the StreamStatsDB compilation so they would be available via the StreamStats interface for user-selected streamgages. All the statistics are available in a USGS ScienceBase data release.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171108","collaboration":"Prepared in cooperation with the Federal Highway Administration Office of Project Development and Environmental Review","usgsCitation":"Granato G.E., Ries, K.G., III, and Steeves, P.A., 2017, Compilation of streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages: U.S. Geological Survey Open-File Report 2017–1108, 17 p., https://doi.org/10.3133/ofr20171108.","productDescription":"Report: vi, 17 p.; 4 Figures; Data Release","onlineOnly":"Y","ipdsId":"IP-077435","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":346453,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71V5CFT","text":"USGS Data 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Explorer]"},{"id":346449,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2017/1108/ofr20171108_fig3b_interactive.pdf","text":"Figure 3B","size":"4.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1108 - Figure 3B","linkHelpText":"—Streamgages by drainage area [layered pdf; view in Adobe Reader or Microsoft Internet Explorer]"},{"id":346450,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2017/1108/ofr20171108_fig3c_interactive.pdf","text":"Figure 3C","size":"4.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1108 - Figure 3C","linkHelpText":"—Streamgages by percentage of zero-flow days [layered pdf; view in Adobe Reader or Microsoft Internet Explorer]"},{"id":346451,"rank":6,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2017/1108/ofr20171108_fig3d_interactive.pdf","text":"Figure 3D","size":"4.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1108 - Figure 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 \"}}]}\n","publicComments":"Groundwater and Streamflow Information Program","contact":"<p><a href=\"https://water.usgs.gov/osw/\" data-mce-href=\"https://water.usgs.gov/osw/\">Office of Surface Water</a><br> U.S. Geological Survey<br> 415 National Center<br> 12201 Sunrise Valley Drive<br> Reston, VA 20192</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Computer-Program Updates</li><li>Station Selection and Attributes</li><li>Updating StreamStatsDB and Display of Statistics in StreamStats</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2017-10-16","noUsgsAuthors":false,"publicationDate":"2017-10-16","publicationStatus":"PW","scienceBaseUri":"59e5c51be4b05fe04cd1c9d2","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":147346,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory","email":"ggranato@usgs.gov","middleInitial":"E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":false,"id":708011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ries, Kernell G. III 0000-0003-1690-5499 kries@usgs.gov","orcid":"https://orcid.org/0000-0003-1690-5499","contributorId":192960,"corporation":false,"usgs":true,"family":"Ries","given":"Kernell G.","suffix":"III","email":"kries@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":708012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steeves, Peter A. 0000-0001-7558-9719 psteeves@usgs.gov","orcid":"https://orcid.org/0000-0001-7558-9719","contributorId":1873,"corporation":false,"usgs":true,"family":"Steeves","given":"Peter","email":"psteeves@usgs.gov","middleInitial":"A.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":708013,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191374,"text":"70191374 - 2017 - Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions","interactions":[],"lastModifiedDate":"2017-10-10T16:00:45","indexId":"70191374","displayToPublicDate":"2017-10-10T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions","docAbstract":"<p><span>Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5-11&nbsp;months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One&nbsp;</span><i>ad hoc</i><span><span>&nbsp;</span>test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best-performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid-Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12562","usgsCitation":"Austin, S.H., and Nelms, D.L., 2017, Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions: Journal of the American Water Resources Association, v. 53, no. 5, p. 1133-1146, https://doi.org/10.1111/1752-1688.12562.","productDescription":"14 p.","startPage":"1133","endPage":"1146","ipdsId":"IP-069502","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":469450,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12562","text":"Publisher Index 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