{"pageNumber":"1373","pageRowStart":"34300","pageSize":"25","recordCount":184743,"records":[{"id":70113254,"text":"70113254 - 2014 - Gully annealing by aeolian sediment: field and remote-sensing investigation of aeolian-hillslope-fluvial interactions, Colorado River corridor, Arizona, USA","interactions":[],"lastModifiedDate":"2014-06-19T11:32:32","indexId":"70113254","displayToPublicDate":"2014-06-19T11:25:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Gully annealing by aeolian sediment: field and remote-sensing investigation of aeolian-hillslope-fluvial interactions, Colorado River corridor, Arizona, USA","docAbstract":"Processes contributing to development of ephemeral gully channels are of great importance to landscapes worldwide, and particularly in dryland regions where soil loss and land degradation from gully erosion pose long-term land-management problems. Whereas gully formation has been relatively well studied, much less is known of the processes that anneal gullies and impede their growth. This study of gully annealing by aeolian sediment, spanning 95 km along the Colorado River corridor in Glen, Marble, and Grand Canyon, Arizona, USA, employed field and remote sensing observations, including digital topographic modelling. Results indicate that aeolian sediment activity can be locally effective at counteracting gully erosion. Gullies are less prevalent in areas where surficial sediment undergoes active aeolian transport, and have a greater tendency to terminate in active aeolian sand. Although not common, examples exist in the record of historical imagery of gullies that underwent infilling by aeolian sediment in past decades and evidently were effectively annealed. We thus provide new evidence for a potentially important interaction of aeolian–hillslope–fluvial processes, which could affect dryland regions substantially in ways not widely recognized. Moreover, because the biologic soil crust plays an important role in determining aeolian sand activity, and so in turn the extent of gully development, this study highlights a critical role of geomorphic–ecologic interactions in determining arid-landscape evolution.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geomorphology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2014.05.028","usgsCitation":"Sankey, J.B., and Draut, A.E., 2014, Gully annealing by aeolian sediment: field and remote-sensing investigation of aeolian-hillslope-fluvial interactions, Colorado River corridor, Arizona, USA: Geomorphology, v. 220, p. 68-80, https://doi.org/10.1016/j.geomorph.2014.05.028.","productDescription":"13 p.","startPage":"68","endPage":"80","numberOfPages":"13","ipdsId":"IP-052875","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":288905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288903,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.geomorph.2014.05.028"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River;Glen Canyon;Grand Canyon;Marble Canyon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118.43,30.69 ], [ -118.43,44.01 ], [ -104.06,44.01 ], [ -104.06,30.69 ], [ -118.43,30.69 ] ] ] } } ] }","volume":"220","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7732e4b0abf75cf2c0a1","contributors":{"authors":[{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":495025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Draut, Amy E.","contributorId":92215,"corporation":false,"usgs":true,"family":"Draut","given":"Amy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":495026,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70111838,"text":"fs20143053 - 2014 - The 3D Elevation Program: summary for Oklahoma","interactions":[],"lastModifiedDate":"2016-08-17T15:39:45","indexId":"fs20143053","displayToPublicDate":"2014-06-19T11:18:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3053","title":"The 3D Elevation Program: summary for Oklahoma","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Oklahoma, elevation data are critical for flood risk management, infrastructure and construction management, agriculture and precision farming, natural resources conservation, wildlife and habitat management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of local, State, and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment (NEEA; Dewberry, 2011) evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143053","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for Oklahoma: U.S. Geological Survey Fact Sheet 2014-3053, 2 p., https://doi.org/10.3133/fs20143053.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056012","costCenters":[{"id":423,"text":"National Geospatial 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":494479,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70104185,"text":"sir20145078 - 2014 - Estimation of flood discharges at selected annual exceedance probabilities for unregulated, rural streams in Vermont, <i>with a section on</i> Vermont regional skew regression","interactions":[],"lastModifiedDate":"2014-06-19T11:15:42","indexId":"sir20145078","displayToPublicDate":"2014-06-19T11:06:00","publicationYear":"2014","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":"2014-5078","title":"Estimation of flood discharges at selected annual exceedance probabilities for unregulated, rural streams in Vermont, <i>with a section on</i> Vermont regional skew regression","docAbstract":"<p>This report provides estimates of flood discharges at selected annual exceedance probabilities (AEPs) for streamgages in and adjacent to Vermont and equations for estimating flood discharges at AEPs of 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent (recurrence intervals of 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-years, respectively) for ungaged, unregulated, rural streams in Vermont. The equations were developed using generalized least-squares regression. Flood-frequency and drainage-basin characteristics from 145 streamgages were used in developing the equations. The drainage-basin characteristics used as explanatory variables in the regression equations include drainage area, percentage of wetland area, and the basin-wide mean of the average annual precipitation. The average standard errors of prediction for estimating the flood discharges at the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEP with these equations are 34.9, 36.0, 38.7, 42.4, 44.9, 47.3, 50.7, and 55.1 percent, respectively.</p>\n<br/>\n<p>Flood discharges at selected AEPs for streamgages were computed by using the Expected Moments Algorithm. To improve estimates of the flood discharges for given exceedance probabilities at streamgages in Vermont, a new generalized skew coefficient was developed. The new generalized skew for the region is a constant, 0.44. The mean square error of the generalized skew coefficient is 0.078. This report describes a technique for using results from the regression equations to adjust an AEP discharge computed from a streamgage record. This report also describes a technique for using a drainage-area adjustment to estimate flood discharge at a selected AEP for an ungaged site upstream or downstream from a streamgage.</p>\n<br/>\n<p>The final regression equations and the flood-discharge frequency data used in this study will be available in StreamStats. StreamStats is a World Wide Web application providing automated regression-equation solutions for user-selected sites on streams.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145078","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Olson, S.A., and with a section by Veilleux, A.G., 2014, Estimation of flood discharges at selected annual exceedance probabilities for unregulated, rural streams in Vermont, <i>with a section on</i> Vermont regional skew regression: U.S. Geological Survey Scientific Investigations Report 2014-5078, Report: vi, 27 p.; Appendixes 1-8, 7, 9, https://doi.org/10.3133/sir20145078.","productDescription":"Report: vi, 27 p.; Appendixes 1-8, 7, 9","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052679","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":288898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145078.jpg"},{"id":288893,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5078/"},{"id":288894,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5078/pdf/sir2014-5078.pdf"},{"id":288895,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5078/appendix/sir2014-5078_olson_apend01-08.xlsx"},{"id":288897,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5078/appendix/sir2014-5078_olson_apend09.xlsx"},{"id":288896,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5078/appendix/sir2014-5078_olson_apend07.pdf"}],"country":"United States","state":"Vermont","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.7537,42.1919 ], [ -74.7537,45.5564 ], [ -70.5267,45.5564 ], [ -70.5267,42.1919 ], [ -74.7537,42.1919 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae76aae4b0abf75cf2bfd6","contributors":{"authors":[{"text":"Olson, Scott A. 0000-0002-1064-2125 solson@usgs.gov","orcid":"https://orcid.org/0000-0002-1064-2125","contributorId":2059,"corporation":false,"usgs":true,"family":"Olson","given":"Scott","email":"solson@usgs.gov","middleInitial":"A.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"with a section by Veilleux, Andrea G.","contributorId":74302,"corporation":false,"usgs":true,"family":"with a section by Veilleux","given":"Andrea","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":493626,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70113245,"text":"70113245 - 2014 - Effects of recruitment, growth, and exploitation on walleye population size structure in northern Wisconsin lakes","interactions":[],"lastModifiedDate":"2014-06-19T10:57:57","indexId":"70113245","displayToPublicDate":"2014-06-19T10:52:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Effects of recruitment, growth, and exploitation on walleye population size structure in northern Wisconsin lakes","docAbstract":"We evaluated the dynamics of walleye <i>Sander vitreus</i> population size structure, as indexed by the proportional size distribution (PSD) of quality-length fish, in Escanaba Lake during 1967–2003 and in 204 other lakes in northern Wisconsin during 1990–2011. We estimated PSD from angler-caught walleyes in Escanaba Lake and from spring electrofishing in 204 other lakes, and then related PSD to annual estimates of recruitment to age-3, length at age 3, and annual angling exploitation rate. In Escanaba Lake during 1967–2003, annual estimates of PSD were highly dynamic, growth (positively) explained 35% of PSD variation, recruitment explained only 3% of PSD variation, and exploitation explained only 7% of PSD variation. In 204 other northern Wisconsin lakes during 1990–2011, PSD varied widely among lakes, recruitment (negatively) explained 29% of PSD variation, growth (positively) explained 21% of PSD variation, and exploitation explained only 4% of PSD variation. We conclude that population size structure was most strongly driven by recruitment and growth, rather than exploitation, in northern Wisconsin walleye populations. Studies of other species over wide spatial and temporal ranges of recruitment, growth, and mortality are needed to determine which dynamic rate most strongly influences population size structure of other species. Our findings indicate a need to be cautious about assuming exploitation is a strong driver of walleye population size structure.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Fish and Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/092013-JFWM-065","usgsCitation":"Hansen, M.J., and Nate, N.A., 2014, Effects of recruitment, growth, and exploitation on walleye population size structure in northern Wisconsin lakes: Journal of Fish and Wildlife Management, v. 5, no. 1, p. 99-108, https://doi.org/10.3996/092013-JFWM-065.","productDescription":"10 p.","startPage":"99","endPage":"108","numberOfPages":"10","ipdsId":"IP-055653","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":472931,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/092013-jfwm-065","text":"Publisher Index Page"},{"id":288891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288888,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3996/092013-JFWM-065"}],"country":"United States","state":"Wisconsin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.89,42.49 ], [ -92.89,47.08 ], [ -86.76,47.08 ], [ -86.76,42.49 ], [ -92.89,42.49 ] ] ] } } ] }","volume":"5","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-03-01","publicationStatus":"PW","scienceBaseUri":"53ae769ae4b0abf75cf2bfc1","contributors":{"authors":[{"text":"Hansen, Michael J. 0000-0001-8522-3876 michaelhansen@usgs.gov","orcid":"https://orcid.org/0000-0001-8522-3876","contributorId":5006,"corporation":false,"usgs":true,"family":"Hansen","given":"Michael","email":"michaelhansen@usgs.gov","middleInitial":"J.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":495016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nate, Nancy A.","contributorId":26626,"corporation":false,"usgs":true,"family":"Nate","given":"Nancy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":495017,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70189943,"text":"70189943 - 2014 - Modeling low-temperature geochemical processes:","interactions":[],"lastModifiedDate":"2022-12-09T16:44:03.209979","indexId":"70189943","displayToPublicDate":"2014-06-19T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7.2","title":"Modeling low-temperature geochemical processes:","docAbstract":"<p><span>This chapter provides an overview of geochemical modeling that applies to water–rock interactions under ambient conditions of temperature and pressure. Topics include modeling definitions, historical background, issues of activity coefficients, popular codes and databases, examples of modeling common types of water–rock interactions, and issues of model reliability. Examples include speciation, microbial redox kinetics and ferrous iron oxidation, calcite dissolution, pyrite oxidation, combined pyrite and calcite dissolution, dedolomitization, seawater–carbonate groundwater mixing, reactive-transport modeling in streams, modeling catchments, and evaporation of seawater. The chapter emphasizes limitations to geochemical modeling: that a proper understanding and ability to communicate model results well are as important as completing a set of useful modeling computations and that greater sophistication in model and code development is not necessarily an advancement. If the goal is to understand how a particular geochemical system behaves, it is better to collect more field data than rely on computer codes.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference module in earth systems and environmental sciences: Treatise on geochemistry","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/B978-0-08-095975-7.00502-7","usgsCitation":"Nordstrom, D.K., and Campbell, K.M., 2014, Modeling low-temperature geochemical processes:, chap. 7.2 <i>of</i> Reference module in earth systems and environmental sciences: Treatise on geochemistry, v. 7, p. 27-68, https://doi.org/10.1016/B978-0-08-095975-7.00502-7.","productDescription":"42 p.","startPage":"27","endPage":"68","ipdsId":"IP-038052","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":345118,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","edition":"2nd Edition","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"599fe5bce4b038630d022110","contributors":{"authors":[{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":706839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":706840,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70187705,"text":"70187705 - 2014 - A mapping and monitoring assessment of the Philippines' mangrove forests from 1990 to 2010","interactions":[],"lastModifiedDate":"2017-05-15T14:44:11","indexId":"70187705","displayToPublicDate":"2014-06-19T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"A mapping and monitoring assessment of the Philippines' mangrove forests from 1990 to 2010","docAbstract":"<p><span>Information on the present condition and spatiotemporal dynamics of mangrove forests is needed for land-change studies and integrated natural resources planning and management. Although several national mangrove estimates for the Philippines exist, information is unavailable at sufficient spatial and thematic detail for change analysis. Historical and contemporary mangrove distribution maps of the Philippines for 1990 and 2010 were prepared at nominal 30-m spatial resolution using Landsat satellite data. Image classification was performed using a supervised decision tree classification approach. Additionally, decadal land-cover change maps from 1990 to 2010 were prepared to depict changes in mangrove area. Total mangrove area decreased 10.5% from 1990 to 2010. Comparison of estimates produced from this study with selected historical mangrove area estimates revealed that total mangrove area decreased by approximately half (51.8%) from 1918 to 2010. This study provides the most current and reliable data regarding the Philippines mangrove area and spatial distribution and delineates where and when mangrove change has occurred in recent decades. The results from this study are useful for developing conservation strategies, biodiversity loss mitigation efforts, and future monitoring and analysis.</span></p>","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/JCOASTRES-D-13-00057.1","usgsCitation":"Long, J., Napton, D., Giri, C., and Graesser, J., 2014, A mapping and monitoring assessment of the Philippines' mangrove forests from 1990 to 2010: Journal of Coastal Research, v. 30, no. 2, p. 260-271, https://doi.org/10.2112/JCOASTRES-D-13-00057.1.","productDescription":"12 p.","startPage":"260","endPage":"271","ipdsId":"IP-046144","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341308,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Phillippines","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[126.37681,8.41471],[126.47851,7.75035],[126.53742,7.18938],[126.19677,6.27429],[125.83142,7.29372],[125.36385,6.78649],[125.68316,6.04966],[125.39651,5.581],[124.21979,6.16136],[123.93872,6.88514],[124.24366,7.36061],[123.61021,7.83353],[123.29607,7.41888],[122.82551,7.45737],[122.0855,6.89942],[121.91993,7.19212],[122.31236,8.03496],[122.9424,8.31624],[123.48769,8.69301],[123.84115,8.24032],[124.60147,8.51416],[124.76461,8.96041],[125.47139,8.987],[125.41212,9.76033],[126.22271,9.28607],[126.30664,8.78249],[126.37681,8.41471]]],[[[123.98244,10.27878],[123.62318,9.95009],[123.30992,9.31827],[122.99588,9.02219],[122.38005,9.71336],[122.58609,9.98104],[122.83708,10.26116],[122.94741,10.88187],[123.49885,10.94062],[123.33777,10.26738],[124.07794,11.23273],[123.98244,10.27878]]],[[[118.50458,9.31638],[117.17427,8.3675],[117.66448,9.06689],[118.38691,9.6845],[118.98734,10.37629],[119.5115,11.36967],[119.68968,10.55429],[119.02946,10.00365],[118.50458,9.31638]]],[[[121.88355,11.89176],[122.48382,11.58219],[123.12022,11.58366],[123.10084,11.16593],[122.63771,10.74131],[122.00261,10.44102],[121.96737,10.90569],[122.03837,11.41584],[121.88355,11.89176]]],[[[125.50255,12.16269],[125.78346,11.04612],[125.01188,11.31145],[125.03276,10.97582],[125.27745,10.35872],[124.80182,10.13468],[124.76017,10.838],[124.4591,10.88993],[124.30252,11.49537],[124.89101,11.41558],[124.87799,11.79419],[124.26676,12.55776],[125.22712,12.53572],[125.50255,12.16269]]],[[[121.52739,13.06959],[121.26219,12.20556],[120.8339,12.7045],[120.32344,13.46641],[121.18013,13.4297],[121.52739,13.06959]]],[[[121.32131,18.50406],[121.9376,18.21855],[122.24601,18.47895],[122.33696,18.22488],[122.17428,17.81028],[122.51565,17.0935],[122.25231,16.26244],[121.66279,15.93102],[121.50507,15.12481],[121.72883,14.32838],[122.25893,14.2182],[122.70128,14.33654],[123.9503,13.78213],[123.85511,13.23777],[124.18129,12.99753],[124.07742,12.53668],[123.29804,13.02753],[122.92865,13.55292],[122.67136,13.18584],[122.03465,13.78448],[121.12638,13.63669],[120.62864,13.85766],[120.67938,14.27102],[120.99182,14.52539],[120.69334,14.75667],[120.56415,14.39628],[120.07043,14.97087],[119.92093,15.40635],[119.88377,16.3637],[120.28649,16.03463],[120.39005,17.59908],[120.71587,18.50523],[121.32131,18.50406]]]]},\"properties\":{\"name\":\"Philippines\"}}]}","volume":"30","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591abe38e4b0a7fdb43c8bfb","contributors":{"authors":[{"text":"Long, Jordan 0000-0002-4814-464X jlong@usgs.gov","orcid":"https://orcid.org/0000-0002-4814-464X","contributorId":3609,"corporation":false,"usgs":true,"family":"Long","given":"Jordan","email":"jlong@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Napton, Darrell","contributorId":176288,"corporation":false,"usgs":false,"family":"Napton","given":"Darrell","affiliations":[],"preferred":false,"id":695186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giri, Chandra cgiri@usgs.gov","contributorId":189128,"corporation":false,"usgs":true,"family":"Giri","given":"Chandra","email":"cgiri@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695184,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graesser, Jordan","contributorId":192030,"corporation":false,"usgs":false,"family":"Graesser","given":"Jordan","email":"","affiliations":[],"preferred":false,"id":695189,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70112913,"text":"sir20145073 - 2014 - Streamflow, water quality, and aquatic macroinvertebrates of selected streams in Fairfax County, Virginia, 2007-12","interactions":[],"lastModifiedDate":"2014-06-18T15:06:54","indexId":"sir20145073","displayToPublicDate":"2014-06-18T15:01:00","publicationYear":"2014","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":"2014-5073","title":"Streamflow, water quality, and aquatic macroinvertebrates of selected streams in Fairfax County, Virginia, 2007-12","docAbstract":"<p>Efforts to mitigate the effects of urbanization on streams rely on best management practices (BMPs) that are implemented with the intent of reducing and retaining stormwater runoff. A cooperative monitoring effort between the U.S. Geological Survey and Fairfax County, Virginia, was initiated in 2007 to assess the condition of county streams and document watershed-scale responses to the implementation of BMPs. Assessment of the data collected during the first 5 years of this monitoring program focused on characterizing the hydrologic and ecological condition of 14 monitored streams.</p>\n<br>\n<p>Hydrologic, chemical, and macroinvertebrate community conditions in the streams monitored were found to be consistent, overall, with conditions commonly observed in urban streams. Hydrologically, the monitored streams were found to be flashy, with flashiness positively related to road cover in the watershed. Typical pH values of streams throughout the network centered around neutrality (pH = 7) with strong daily fluctuations apparent in the continuous data. Patterns in specific conductance were largely representative of anthropogenic disturbances—watersheds having the greatest percentage of open space and estate residential land-use had the lowest typical specific conductance values, and specific conductance variability was less than what is observed in watersheds that are more intensively developed. In watersheds having greater road coverage, and more development in general, increases in specific conductance over several orders of magnitude were observed during winter months as a result of the application of de-icing salts on impervious surfaces. Dissolved oxygen conditions were typically within the range required to support healthy biological communities, although occasional departures during summer months at some sites fell below the impairment threshold for streams in Virginia.</p>\n<br>\n<p>Nitrogen (N) and phosphorus (P), concentration patterns were largely consistent across the network, with few exceptions. Nitrogen concentrations in monthly samples were generally low and dominated by nitrate. Exceptions to the generally low N concentrations occurred at Captain Hickory Run, which had a median total N concentration of approximately 4.9 milligrams per liter (mg/L), compared to the network-wide median of approximately 1.7 mg/L, and at Popes Head Creek Tributary, where total N concentrations spiked to 6–8 mg/L during low-flow periods in August or September of each year. Phosphorus concentrations in monthly samples were generally low and dominated by the dissolved fraction. Two monitoring stations in the network, Flatlick Branch and Frog Branch, are notable for having median total P concentrations that were, on average, approximately three times greater than the median total P concentration of 0.02 mg/L observed at the other 12 stations in the network.</p>\n<br>\n<p>Suspended-sediment and nutrient loads and yields were similar to those of urbanized watersheds in other studies, although the yields from these urbanized basins were greater than, or within, the upper quartile of yields observed throughout the Chesapeake Bay watershed. Annual suspended-sediment loads ranged from 289–10,275 tons, with a median of 1,311 tons, and corresponding yields ranged from 107–2,827 tons per square mile (ton/mi<sup>2</sup>), with a median of 277 ton/mi<sup>2</sup>. Annual total N loads ranged from 8,014–36,413 pounds, with a median of 21,314 pounds, and corresponding yields ranged from 3,361–8,360 pounds per square mile (lb/mi<sup>2</sup>), with a median of 6,200 lb/mi<sup>2</sup>. Annual total P loads ranged from 380–6,558 pounds, with a median of 1,874 pounds, and corresponding yields ranged from 140–1,562 lb/mi<sup>2</sup>, with a median of 543 lb/mi<sup>2</sup>.</p>\n<br>\n<p>Benthic macroinvertebrate community metrics indicated that streams throughout Fairfax County are generally of poor health. One station, Castle Creek, was an exception with results indicating relatively high quality aquatic health.</p>\n<br>\n<p>Six additional monitoring stations were added to the network in 2012 to improve spatial coverage throughout Fairfax County. Monitoring activities are expected to continue at all 20 stations for the foreseeable future as BMP implementation is conducted.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145073","issn":"2328-0328","isbn":"978-1-4113-3788-6","collaboration":"Prepared in cooperation with Fairfax County, Virginia","usgsCitation":"Jastram, J.D., 2014, Streamflow, water quality, and aquatic macroinvertebrates of selected streams in Fairfax County, Virginia, 2007-12: U.S. Geological Survey Scientific Investigations Report 2014-5073, x, 68 p., https://doi.org/10.3133/sir20145073.","productDescription":"x, 68 p.","numberOfPages":"82","onlineOnly":"N","temporalStart":"2007-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-051336","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":288839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145073.jpg"},{"id":288837,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5073/"},{"id":288838,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5073/pdf/sir2014-5073.pdf"}],"scale":"2000000","country":"United States","state":"Virginia","county":"Fairfax County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.5,38.666667 ], [ -77.5,39.0 ], [ -77.0,39.0 ], [ -77.0,38.666667 ], [ -77.5,38.666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7843e4b0abf75cf2cf70","contributors":{"authors":[{"text":"Jastram, John D. 0000-0002-9416-3358 jdjastra@usgs.gov","orcid":"https://orcid.org/0000-0002-9416-3358","contributorId":3531,"corporation":false,"usgs":true,"family":"Jastram","given":"John","email":"jdjastra@usgs.gov","middleInitial":"D.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494913,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70048478,"text":"70048478 - 2014 - Population dynamics of bowfin in a south Georgia reservoir: latitudinal comparisons of population structure, growth, and mortality","interactions":[],"lastModifiedDate":"2015-11-13T13:40:30","indexId":"70048478","displayToPublicDate":"2014-06-18T14:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3909,"text":"Journal of the Southeastern Association of Fish and Wildlife Agencies","active":true,"publicationSubtype":{"id":10}},"title":"Population dynamics of bowfin in a south Georgia reservoir: latitudinal comparisons of population structure, growth, and mortality","docAbstract":"<p>The objectives of this study were to evaluate the population dynamics of bowfin (Amia calva) in Lake Lindsay Grace, Georgia, and to compare those dynamics to other bowfin populations. Relative abundance of bowfin sampled in 2010 in Lake Lindsay Grace was low and variable (mean&plusmn;SD; 2.7&plusmn;4.7 fish per hour of electrofishing). Total length (TL) of bowfin collected in Lake Lindsay Grace varied from 233&ndash;683 mm. Age of bowfin in Lake Lindsay Grace varied from 0&ndash;5 yr. Total annual mortality (A) was estimated at 68%. Both sexes appeared to be fully mature by age 2 with gonadosomatic index values above 8 for females and close to 1 for males. The majority of females were older, longer, and heavier than males. Bowfin in Lake Lindsay Grace had fast growth up to age 4 and higher total annual mortality than the other populations examined in this study. A chi-square test indicated that size structure of bowfin from Lake Lindsay Grace was different than those of a Louisiana population and two bowfin populations from the upper Mississippi River. To further assess bowfin size structure, we proposed standard length (i.e., TL) categories: stock (200 mm, 8 inches), quality (350 mm, 14 inches), preferred (460 mm, 18 inches), memorable (560 mm, 22, inches), and trophy (710 mm, 28 inches). Because our knowledge of bowfin ecology is limited, additional understanding of bowfin population dynamics provides important insight that can be used in management of bowfin across their distribution.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Proceedings of the Southeastern Association of Fish and Wildlife Agencies","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Southeastern Association of Fish and Wildlife Agencies","publisherLocation":"Maggie Valley, NC","usgsCitation":"Porter, N.J., Bonvechio, T., McCormick, J.L., and Quist, M., 2014, Population dynamics of bowfin in a south Georgia reservoir: latitudinal comparisons of population structure, growth, and mortality: Journal of the Southeastern Association of Fish and Wildlife Agencies, p. 103-109.","productDescription":"7 p.","startPage":"103","endPage":"109","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045974","costCenters":[{"id":342,"text":"Idaho Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":311311,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311310,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.bowfinanglers.com/JSEAFWA_2014_Porter_bowfin_Georgia.pdf"}],"country":"United States","state":"Georgia","otherGeospatial":"Lake Lindsay Grace","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.05611228942871,\n              31.59250052022682\n            ],\n            [\n              -82.05319404602051,\n              31.589283616099355\n     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]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564717d1e4b0e2669b313123","contributors":{"authors":[{"text":"Porter, Nicholas J.","contributorId":149848,"corporation":false,"usgs":false,"family":"Porter","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":579801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonvechio, Timothy F.","contributorId":149849,"corporation":false,"usgs":false,"family":"Bonvechio","given":"Timothy F.","affiliations":[],"preferred":false,"id":579802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, Joshua L.","contributorId":105193,"corporation":false,"usgs":true,"family":"McCormick","given":"Joshua","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":579803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quist, Michael","contributorId":119346,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","affiliations":[],"preferred":false,"id":518209,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70095721,"text":"ds829 - 2014 - Archive of digital chirp subbottom profile data collected during USGS Cruise 13GFP01, Brownlee Dam and Hells Canyon Reservoir, Idaho and Oregon, 2013","interactions":[],"lastModifiedDate":"2014-06-18T14:43:21","indexId":"ds829","displayToPublicDate":"2014-06-18T14:37:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"829","title":"Archive of digital chirp subbottom profile data collected during USGS Cruise 13GFP01, Brownlee Dam and Hells Canyon Reservoir, Idaho and Oregon, 2013","docAbstract":"From March 16 - 31, 2013, the U.S. Geological Survey in cooperation with the Idaho Power Company conducted a geophysical survey to investigate sediment deposits and long-term sediment transport within the Snake River from Brownlee Dam to Hells Canyon Reservoir, along the Idaho and Oregon border; this effort will help the USGS to better understand geologic processes. This report serves as an archive of unprocessed digital chirp subbottom data, trackline maps, navigation files, Geographic Information System (GIS) files, Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FGDC) metadata. Gained (showing a relative increase in signal amplitude) digital images of the seismic profiles are also provided. Refer to the <a href=\"http://pubs.usgs.gov/ds/0829/html/acronyms.html\">Acronyms</a> page for expansions of acronyms and abbreviations used in this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds829","issn":"2327-638X","collaboration":"Idaho Power Company, Boise, ID","usgsCitation":"Forde, A.S., Dadisman, S.V., Flocks, J.G., Fosness, R.L., Welcker, C., and Kelso, K.W., 2014, Archive of digital chirp subbottom profile data collected during USGS Cruise 13GFP01, Brownlee Dam and Hells Canyon Reservoir, Idaho and Oregon, 2013: U.S. Geological Survey Data Series 829, Report: HTML document; Downloads directory, https://doi.org/10.3133/ds829.","productDescription":"Report: HTML document; Downloads directory","onlineOnly":"N","temporalStart":"2013-03-16","temporalEnd":"2013-03-31","ipdsId":"IP-053170","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds829.jpg"},{"id":288833,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0829/downloads"},{"id":288831,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0829/"},{"id":288832,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0829/title.html"}],"country":"United States","state":"Idaho;Oregon","otherGeospatial":"Brownlee Dam;Hells Canyon Reservoir","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.0,43.5 ], [ -119.0,45.0 ], [ -117.5,45.0 ], [ -117.5,43.5 ], [ -119.0,43.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7630e4b0abf75cf2bebf","contributors":{"authors":[{"text":"Forde, Arnell S. 0000-0002-5581-2255 aforde@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-2255","contributorId":376,"corporation":false,"usgs":true,"family":"Forde","given":"Arnell","email":"aforde@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":491382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dadisman, Shawn V. sdadisman@usgs.gov","contributorId":2207,"corporation":false,"usgs":true,"family":"Dadisman","given":"Shawn","email":"sdadisman@usgs.gov","middleInitial":"V.","affiliations":[],"preferred":true,"id":491384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flocks, James G. 0000-0002-6177-7433 jflocks@usgs.gov","orcid":"https://orcid.org/0000-0002-6177-7433","contributorId":816,"corporation":false,"usgs":true,"family":"Flocks","given":"James","email":"jflocks@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":491383,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491385,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welcker, Chris","contributorId":63314,"corporation":false,"usgs":true,"family":"Welcker","given":"Chris","email":"","affiliations":[],"preferred":false,"id":491387,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelso, Kyle W. 0000-0003-0615-242X kkelso@usgs.gov","orcid":"https://orcid.org/0000-0003-0615-242X","contributorId":4307,"corporation":false,"usgs":true,"family":"Kelso","given":"Kyle","email":"kkelso@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":491386,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70112928,"text":"70112928 - 2014 - Performance of a surface bypass structure to enhance juvenile steelhead passage and survival at Lower Granite Dam, Washington","interactions":[],"lastModifiedDate":"2016-04-26T09:36:35","indexId":"70112928","displayToPublicDate":"2014-06-18T13:57:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Performance of a surface bypass structure to enhance juvenile steelhead passage and survival at Lower Granite Dam, Washington","docAbstract":"<p><span>An integral part of efforts to recover stocks of Pacific salmon&nbsp;</span><i>Oncorhynchus</i><span>&nbsp;spp. and steelhead&nbsp;</span><i>O. mykiss</i><span>&nbsp;in Pacific Northwest rivers is to increase passage efficacy and survival of juveniles past hydroelectric dams. As part of this effort, we evaluated the efficacy of a prototype surface bypass structure, the removable spillway weir (RSW), installed in a spillbay at Lower Granite Dam, Washington, on the Snake River during 2002, 2003, 2005, and 2006. Radio-tagged juvenile steelhead were released upstream from the dam and their route of passage through the turbines, juvenile bypass, spillway, or RSW was recorded. The RSW was operated in an on-or-off condition and passed 3&ndash;13% of the total discharge at the dam when it was on. Poisson rate models were fit to the passage counts of hatchery- and natural-origin juvenile steelhead to predict the probability of fish passing the dam. Main-effect predictor variables were RSW operation, diel period, day of the year, proportion of flow passed by the spillway, and total discharge at the dam. The combined fish passage through the RSW and spillway was 55&ndash;85% during the day and 37&ndash;61% during the night. The proportion of steelhead passing through nonturbine routes was &lt;88% when the RSW was off during the day and increased to &gt;95% when the RSW was on during the day. The ratio of the proportion of steelhead passed to the proportion of water passing the RSW was from 6.3:1 to 10.0:1 during the day and from 2.7:1 to 5.2:1 during the night. Steelhead passing through the RSW exited the tailrace about 15&nbsp;min faster than fish passing through the spillway. Mark&ndash;recapture single-release survival estimates for steelhead passing the RSW ranged from 0.95 to 1.00. The RSW appeared to be an effective bypass structure compared with other routes of fish passage at the dam.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1080/02755947.2014.901256","usgsCitation":"Adams, N.S., Plumb, J.M., Perry, R.W., and Rondorf, D.W., 2014, Performance of a surface bypass structure to enhance juvenile steelhead passage and survival at Lower Granite Dam, Washington: North American Journal of Fisheries Management, v. 34, no. 3, p. 576-594, https://doi.org/10.1080/02755947.2014.901256.","productDescription":"19 p.","startPage":"576","endPage":"594","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-046409","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":288826,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon, Washington","otherGeospatial":"Lower Granite Dam, Snake River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.56,45.15 ], [ -119.56,47.04 ], [ -114.51,47.04 ], [ -114.51,45.15 ], [ -119.56,45.15 ] ] ] } } ] }","volume":"34","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-05-22","publicationStatus":"PW","scienceBaseUri":"53ae77a4e4b0abf75cf2c196","contributors":{"authors":[{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":494948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John M. 0000-0003-4255-1612 jplumb@usgs.gov","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":3569,"corporation":false,"usgs":true,"family":"Plumb","given":"John","email":"jplumb@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":494949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":494946,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rondorf, Dennis W. drondorf@usgs.gov","contributorId":2970,"corporation":false,"usgs":true,"family":"Rondorf","given":"Dennis","email":"drondorf@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":494947,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70112920,"text":"70112920 - 2014 - The response of stream periphyton to Pacific salmon: using a model to understand the role of environmental context","interactions":[],"lastModifiedDate":"2014-06-18T13:43:10","indexId":"70112920","displayToPublicDate":"2014-06-18T13:39:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"The response of stream periphyton to Pacific salmon: using a model to understand the role of environmental context","docAbstract":"<p>1. In stream ecosystems, Pacific salmon deliver subsidies of marine-derived nutrients and disturb the stream bed during spawning. The net effect of this nutrient subsidy and physical disturbance on biological communities can be hard to predict and is likely to be mediated by environmental conditions. For periphyton, empirical studies have revealed that the magnitude and direction of the response to salmon varies from one location to the next. Salmon appear to increase periphyton biomass and/or production in some contexts (a positive response), but decrease them in others (a negative response).</p>\n<br>\n<p>2. To reconcile these seemingly conflicting results, we constructed a system dynamics model that links periphyton biomass and production to salmon spawning. We used this model to explore how environmental conditions influence the periphyton response to salmon.</p>\n<br>\n<p>3. Our simulations suggest that the periphyton response to salmon is strongly mediated by both background nutrient concentrations and the proportion of the stream bed suitable for spawning. Positive periphyton responses occurred when both background nutrient concentrations were low (nutrient limiting conditions) and when little of the stream bed was suitable for spawning (because the substratum is too coarse). In contrast, negative responses occurred when nutrient concentrations were higher or a larger proportion of the bed was suitable for spawning.</p>\n<br>\n<p>4. Although periphyton biomass generally remained above or below background conditions for several months following spawning, periphyton production returned quickly to background values shortly afterwards. As a result, based upon our simulations, salmon did not greatly increase or decrease overall annual periphyton production. This suggests that any increase in production by fish or invertebrates in response to returning salmon is more likely to occur via direct consumption of salmon carcasses and/or eggs, rather than the indirect effects of greater periphyton production.</p>\n<br>\n<p>5. Overall, our simulations suggest that environmental factors need to be taken into account when considering the effects of spawning salmon on aquatic ecosystems. Our model offers researchers a framework for testing periphyton response to salmon across a range of conditions, which can be used to generate hypotheses, plan field experiments and guide data collection.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/fwb.12356","usgsCitation":"Bellmore, J.R., Fremier, A., Mejia, F., and Newsom, M., 2014, The response of stream periphyton to Pacific salmon: using a model to understand the role of environmental context: Freshwater Biology, v. 59, no. 7, p. 1437-1451, https://doi.org/10.1111/fwb.12356.","productDescription":"15 p.","startPage":"1437","endPage":"1451","numberOfPages":"15","ipdsId":"IP-051251","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":288822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288801,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/fwb.12356"}],"volume":"59","issue":"7","noUsgsAuthors":false,"publicationDate":"2014-03-17","publicationStatus":"PW","scienceBaseUri":"53ae7870e4b0abf75cf2d4e3","contributors":{"authors":[{"text":"Bellmore, J. Ryan","contributorId":104790,"corporation":false,"usgs":true,"family":"Bellmore","given":"J.","email":"","middleInitial":"Ryan","affiliations":[],"preferred":false,"id":494932,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fremier, Alexander K.","contributorId":104403,"corporation":false,"usgs":true,"family":"Fremier","given":"Alexander K.","affiliations":[],"preferred":false,"id":494931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mejia, Francine","contributorId":106804,"corporation":false,"usgs":true,"family":"Mejia","given":"Francine","affiliations":[],"preferred":false,"id":494933,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Newsom, Michael","contributorId":16753,"corporation":false,"usgs":true,"family":"Newsom","given":"Michael","affiliations":[],"preferred":false,"id":494930,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70112906,"text":"70112906 - 2014 - Mapping mountain pine beetle mortality through growth trend analysis of time-series landsat data","interactions":[],"lastModifiedDate":"2014-06-18T13:37:34","indexId":"70112906","displayToPublicDate":"2014-06-18T13:28:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Mapping mountain pine beetle mortality through growth trend analysis of time-series landsat data","docAbstract":"Disturbances are key processes in the carbon cycle of forests and other ecosystems. In recent decades, mountain pine beetle (MPB; Dendroctonus ponderosae) outbreaks have become more frequent and extensive in western North America. Remote sensing has the ability to fill the data gaps of long-term infestation monitoring, but the elimination of observational noise and attributing changes quantitatively are two main challenges in its effective application. Here, we present a forest growth trend analysis method that integrates Landsat temporal trajectories and decision tree techniques to derive annual forest disturbance maps over an 11-year period. The temporal trajectory component successfully captures the disturbance events as represented by spectral segments, whereas decision tree modeling efficiently recognizes and attributes events based upon the characteristics of the segments. Validated against a point set sampled across a gradient of MPB mortality, 86.74% to 94.00% overall accuracy was achieved with small variability in accuracy among years. In contrast, the overall accuracies of single-date classifications ranged from 37.20% to 75.20% and only become comparable with our approach when the training sample size was increased at least four-fold. This demonstrates that the advantages of this time series work flow exist in its small training sample size requirement. The easily understandable, interpretable and modifiable characteristics of our approach suggest that it could be applicable to other ecoregions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"MDPI","doi":"10.3390/rs6065696","usgsCitation":"Liang, L., Chen, Y., Hawbaker, T., Zhu, Z., and Gong, P., 2014, Mapping mountain pine beetle mortality through growth trend analysis of time-series landsat data: Remote Sensing, v. 6, no. 6, p. 5696-5716, https://doi.org/10.3390/rs6065696.","productDescription":"21 p.","startPage":"5696","endPage":"5716","numberOfPages":"21","ipdsId":"IP-053363","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":472932,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs6065696","text":"Publisher Index Page"},{"id":288821,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288757,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3390/rs6065696"}],"country":"United States","state":"Colorado","county":"Grand County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.666667,39.666667 ], [ -106.666667,40.333333 ], [ -105.666667,40.333333 ], [ -105.666667,39.666667 ], [ -106.666667,39.666667 ] ] ] } } ] }","volume":"6","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-06-18","publicationStatus":"PW","scienceBaseUri":"53ae7773e4b0abf75cf2c133","contributors":{"authors":[{"text":"Liang, Lu","contributorId":72714,"corporation":false,"usgs":true,"family":"Liang","given":"Lu","affiliations":[],"preferred":false,"id":494906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Yanlei","contributorId":18276,"corporation":false,"usgs":true,"family":"Chen","given":"Yanlei","email":"","affiliations":[],"preferred":false,"id":494904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":494903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhi-Liang","contributorId":70726,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhi-Liang","affiliations":[],"preferred":false,"id":494905,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gong, Peng","contributorId":102393,"corporation":false,"usgs":true,"family":"Gong","given":"Peng","affiliations":[],"preferred":false,"id":494907,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70112760,"text":"70112760 - 2014 - Methylmercury production in sediment from agricultural and non-agricultural wetlands in the Yolo Bypass, California, USA","interactions":[],"lastModifiedDate":"2018-09-25T09:25:04","indexId":"70112760","displayToPublicDate":"2014-06-18T12:59:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Methylmercury production in sediment from agricultural and non-agricultural wetlands in the Yolo Bypass, California, USA","docAbstract":"As part of a larger study of mercury (Hg) biogeochemistry and bioaccumulation in agricultural (rice growing) and non-agricultural wetlands in California's Central Valley, USA, seasonal and spatial controls on methylmercury (MeHg) production were examined in surface sediment. Three types of shallowly-flooded agricultural wetlands (white rice, wild rice, and fallow fields) and two types of managed (non-agricultural) wetlands (permanently and seasonally flooded) were sampled monthly-to-seasonally. Dynamic seasonal changes in readily reducible ‘reactive’ mercury (Hg(II)<sub>R</sub>), Hg(II)-methylation rate constants (k<sub>meth</sub>), and concentrations of electron acceptors (sulfate and ferric iron) and donors (acetate), were all observed in response to field management hydrology, whereas seasonal changes in these parameters were more muted in non-agricultural managed wetlands. Agricultural wetlands exhibited higher sediment MeHg concentrations than did non-agricultural wetlands, particularly during the fall through late-winter (post-harvest) period. Both sulfate- and iron-reducing bacteria have been implicated in MeHg production, and both were demonstrably active in all wetlands studied. Stoichiometric calculations suggest that iron-reducing bacteria dominated carbon flow in agricultural wetlands during the growing season. Sulfate-reducing bacteria were not stimulated by the addition of sulfate-based fertilizer to agricultural wetlands during the growing season, suggesting that labile organic matter, rather than sulfate, limited their activity in these wetlands. Along the continuum of sediment geochemical conditions observed, values of k<sub>meth</sub> increased approximately 10,000-fold, whereas Hg(II)<sub>R</sub> decreased 100-fold. This suggests that, with respect to the often opposing trends of Hg(II)-methylating microbial activity and Hg(II) availability for methylation, microbial activity dominated the Hg(II)-methylation process, and that along this biogeochemical continuum, conditions that favored microbial sulfate reduction resulted in the highest calculated MeHg production potential rates. Rice straw management options aimed at limiting labile carbon supplies to surface sediment during the post-harvest fall–winter period may be effective in limiting MeHg production within agricultural wetlands.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2013.09.098","usgsCitation":"Marvin-DiPasquale, M., Windham-Myers, L., Agee, J.L., Kakouros, E., Kieu, L.H., Fleck, J., Alpers, C.N., and Stricker, C.A., 2014, Methylmercury production in sediment from agricultural and non-agricultural wetlands in the Yolo Bypass, California, USA: Science of the Total Environment, v. 484, p. 288-299, https://doi.org/10.1016/j.scitotenv.2013.09.098.","productDescription":"12 p.","startPage":"288","endPage":"299","numberOfPages":"12","ipdsId":"IP-046333","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":288819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288818,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.scitotenv.2013.09.098"}],"country":"United States","state":"California","otherGeospatial":"Yolo Bypass","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.8128,38.2329 ], [ -121.8128,38.5804 ], [ -121.5097,38.5804 ], [ -121.5097,38.2329 ], [ -121.8128,38.2329 ] ] ] } } ] }","volume":"484","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7779e4b0abf75cf2c13f","contributors":{"authors":[{"text":"Marvin-DiPasquale, Mark","contributorId":57423,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","affiliations":[],"preferred":false,"id":494872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":494868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Agee, Jennifer L. 0000-0002-5964-5079 jlagee@usgs.gov","orcid":"https://orcid.org/0000-0002-5964-5079","contributorId":2586,"corporation":false,"usgs":true,"family":"Agee","given":"Jennifer","email":"jlagee@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":494869,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kakouros, Evangelos 0000-0002-4778-4039 kakouros@usgs.gov","orcid":"https://orcid.org/0000-0002-4778-4039","contributorId":2587,"corporation":false,"usgs":true,"family":"Kakouros","given":"Evangelos","email":"kakouros@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":494870,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kieu, Le H. lkieu@usgs.gov","contributorId":25115,"corporation":false,"usgs":true,"family":"Kieu","given":"Le","email":"lkieu@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":false,"id":494871,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fleck, Jacob A. 0000-0002-3217-3972 jafleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-3972","contributorId":1498,"corporation":false,"usgs":true,"family":"Fleck","given":"Jacob A.","email":"jafleck@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":494867,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494865,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":494866,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70095563,"text":"sir20145032 - 2014 - Simulation of the effects of rainfall and groundwater use on historical lake water levels, groundwater levels, and spring flows in central Florida","interactions":[],"lastModifiedDate":"2014-06-18T12:47:57","indexId":"sir20145032","displayToPublicDate":"2014-06-18T12:42:00","publicationYear":"2014","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":"2014-5032","title":"Simulation of the effects of rainfall and groundwater use on historical lake water levels, groundwater levels, and spring flows in central Florida","docAbstract":"<p>The urbanization of central Florida has progressed substantially in recent decades, and the total population in Lake, Orange, Osceola, Polk, and Seminole Counties more than quadrupled from 1960 to 2010. The Floridan aquifer system is the primary source of water for potable, industrial, and agricultural purposes in central Florida. Despite increases in groundwater withdrawals to meet the demand of population growth, recharge derived by infiltration of rainfall in the well-drained karst terrain of central Florida is the largest component of the long-term water balance of the Floridan aquifer system. To complement existing physics-based groundwater flow models, artificial neural networks and other data-mining techniques were used to simulate historical lake water level, groundwater level, and spring flow at sites throughout the area.</p>\n<br>\n<p>Historical data were examined using descriptive statistics, cluster analysis, and other exploratory analysis techniques to assess their suitability for more intensive data-mining analysis. Linear trend analyses of meteorological data collected by the National Oceanic and Atmospheric Administration at 21 sites indicate 67 percent of sites exhibited upward trends in air temperature over at least a 45-year period of record, whereas 76 percent exhibited downward trends in rainfall over at least a 95-year period of record. Likewise, linear trend analyses of hydrologic response data, which have varied periods of record ranging in length from 10 to 79 years, indicate that water levels in lakes (307 sites) were about evenly split between upward and downward trends, whereas water levels in 69 percent of wells (out of 455 sites) and flows in 68 percent of springs (out of 19 sites) exhibited downward trends. Total groundwater use in the study area increased from about 250 million gallons per day (Mgal/d) in 1958 to about 590 Mgal/d in 1980 and remained relatively stable from 1981 to 2008, with a minimum of 559 Mgal/d in 1994 and a maximum of 773 Mgal/d in 2000. The change in groundwater-use trend in the early 1980s and the following period of relatively slight trend is attributable to the concomitant effects of increasing public-supply withdrawals and decreasing use of water by the phosphate industry and agriculture.</p>\n<br>\n<p>On the basis of available historical data and exploratory analyses, empirical lake water-level, groundwater-level, and spring-flow models were developed for 22 lakes, 23 wells, and 6 springs. Input time series consisting of various frequencies and frequency-band components of daily rainfall (1942 to 2008) and monthly total groundwater use (1957 to 2008) resulted in hybrid signal-decomposition artificial neural network models. The final models explained much of the variability in observed hydrologic data, with 43 of the 51 sites having coefficients of determination exceeding 0.6, and the models matched the magnitude of the observed data reasonably well, such that models for 32 of the 51 sites had root-mean-square errors less than 10 percent of the measured range of the data. The Central Florida Artificial Neural Network Decision Support System was developed to integrate historical databases and the 102 site-specific artificial neural network models, model controls, and model output into a spreadsheet application with a graphical user interface that allows the user to simulate scenarios of interest.</p>\n<br>\n<p>Overall, the data-mining analyses indicate that the Floridan aquifer system in central Florida is a highly conductive, dynamic, open system that is strongly influenced by external forcing. The most important external forcing appears to be rainfall, which explains much of the multiyear cyclic variability and long-term downward trends observed in lake water levels, groundwater levels, and spring flows. For most sites, groundwater use explains less of the observed variability in water levels and flows than rainfall. Relative groundwater-use impacts are greater during droughts, however, and long-term trends in water levels and flows were identified that are consistent with historical groundwater-use patterns. The sensitivity of the hydrologic system to rainfall is expected, owing to the well-drained karst terrain and relatively thin confinement of the Floridan aquifer system in much of central Florida. These characteristics facilitate the relatively rapid transmission of infiltrating water from rainfall to the water table and contribute to downward leakage of water to the Floridan aquifer system. The areally distributed nature of rainfall, as opposed to the site-specific nature of groundwater use, and the generally high transmissivity and low storativity properties of the semiconfined Floridan aquifer system contribute to the prevalence of water-level and flow patterns that mimic rainfall patterns. In general, the data-mining analyses demonstrate that the hydrologic system in central Florida is affected by groundwater use differently during wet periods, when little or no system storage is available (high water levels), compared to dry periods, when there is excess system storage (low water levels). Thus, by driving the overall behavior of the system, rainfall indirectly influences the degree to which groundwater use will effect persistent trends in water levels and flows, with groundwater-use impacts more prevalent during periods of low water levels and spring flows caused by low rainfall and less prevalent during periods of high water levels and spring flows caused by high rainfall. Differences in the magnitudes of rainfall and groundwater use during wet and dry periods also are important determinants of hydrologic response.</p>\n<br>\n<p>An important implication of the data-mining analyses is that rainfall variability at subannual to multidecadal timescales must be considered in combination with groundwater use to provide robust system-response predictions that enhance sustainable resource management in an open karst aquifer system. The data-driven approach was limited, however, by the confounding effects of correlation between rainfall and groundwater use, the quality and completeness of the historical databases, and the spatial variations in groundwater use. The data-mining analyses indicate that available historical data when used alone do not contain sufficient information to definitively quantify the related individual effects of rainfall and groundwater use on hydrologic response. The knowledge gained from data-driven modeling and the results from physics-based modeling, when compared and used in combination, can yield a more comprehensive assessment and a more robust understanding of the hydrologic system than either of the approaches used separately.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145032","issn":"2328-0328","collaboration":"Prepared in cooperation with the St. Johns River Water Management District, Southwest Florida Water Management District, and South Florida Water Management District","usgsCitation":"O’Reilly, A.M., Roehl, E.A., Conrads, P., Daamen, R.C., and Petkewich, M.D., 2014, Simulation of the effects of rainfall and groundwater use on historical lake water levels, groundwater levels, and spring flows in central Florida: U.S. Geological Survey Scientific Investigations Report 2014-5032, Report: xi, 153 p.; Appendix 1: ZIP; Appendix 2: XLSX; Appendix 3: PDF; Appendix 6: ZIP; Appendix 7: XLSX, https://doi.org/10.3133/sir20145032.","productDescription":"Report: xi, 153 p.; Appendix 1: ZIP; Appendix 2: XLSX; Appendix 3: PDF; Appendix 6: ZIP; Appendix 7: XLSX","numberOfPages":"169","onlineOnly":"Y","ipdsId":"IP-049051","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":288816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145032.jpg"},{"id":288811,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5032/appendix/sir2014-5032_appendix1-v2.5.zip"},{"id":288812,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5032/appendix/sir2014-5032_appendix2-gudv.xlsx"},{"id":288809,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5032/"},{"id":288810,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5032/pdf/sir2014-5032.pdf"},{"id":288813,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5032/appendix/sir2014-5032_appendix3_tableA3-1.pdf"},{"id":288814,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5032/appendix/sir2014-5032_appendix6-cfann-dss20120924.zip"},{"id":288815,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5032/appendix/sir2014-5032_appendix7-mdv.xlsx"}],"projection":"Universal Transverse Mercator projection","country":"United States","state":"Florida","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82.0,28.0 ], [ -82.0,29.0 ], [ -81.0,29.0 ], [ -81.0,28.0 ], [ -82.0,28.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae782ce4b0abf75cf2ccb3","contributors":{"authors":[{"text":"O’Reilly, Andrew M. 0000-0003-3220-1248 aoreilly@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-1248","contributorId":2184,"corporation":false,"usgs":true,"family":"O’Reilly","given":"Andrew","email":"aoreilly@usgs.gov","middleInitial":"M.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":491298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roehl, Edwin A. Jr.","contributorId":108083,"corporation":false,"usgs":false,"family":"Roehl","given":"Edwin","suffix":"Jr.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":491300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":491296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daamen, Ruby C.","contributorId":105391,"corporation":false,"usgs":true,"family":"Daamen","given":"Ruby","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":491299,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491297,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70127576,"text":"70127576 - 2014 - PAH concentrations in lake sediment decline following ban on coal-tar-based pavement sealants in Austin, Texas","interactions":[],"lastModifiedDate":"2023-03-22T16:09:58.492334","indexId":"70127576","displayToPublicDate":"2014-06-18T12:32:29","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"PAH concentrations in lake sediment decline following ban on coal-tar-based pavement sealants in Austin, Texas","docAbstract":"Recent studies have concluded that coal-tar-based pavement sealants are a major source of polycyclic aromatic hydrocarbons (PAHs) in urban settings in large parts of the United States. In 2006, Austin, TX, became the first jurisdiction in the U.S. to ban the use of coal-tar sealants. We evaluated the effect of Austin’s ban by analyzing PAHs in sediment cores and bottom-sediment samples collected in 1998, 2000, 2001, 2012, and 2014 from Lady Bird Lake, the principal receiving water body for Austin urban runoff. The sum concentration of the 16 EPA Priority Pollutant PAHs (∑PAH<sub>16</sub>) in dated core intervals and surficial bottom-sediment samples collected from sites in the lower lake declined about 44% from 1998–2005 to 2006–2014 (means of 7980 and 4500 μg kg<sup>–1</sup>, respectively), and by 2012–2014, the decline was about 58% (mean of 3320 μg kg<sup>–1</sup>). Concentrations of ∑PAH<sub>16</sub> in bottom sediment from two of three mid-lake sites decreased by about 71 and 35% from 2001 to 2014. Concentrations at a third site increased by about 14% from 2001 to 2014. The decreases since 2006 reverse a 40-year (1959–1998) upward trend. Despite declines in PAH concentrations, PAH profiles and source-receptor modeling results indicate that coal-tar sealants remain the largest PAH source to the lake, implying that PAH concentrations likely will continue to decline as stocks of previously applied sealant gradually become depleted.","language":"English","publisher":"American Chemical Society","publisherLocation":"Easton, PA","doi":"10.1021/es405691q","usgsCitation":"Van Metre, P., and Mahler, B., 2014, PAH concentrations in lake sediment decline following ban on coal-tar-based pavement sealants in Austin, Texas: Environmental Science & Technology, v. 48, no. 13, p. 7222-7228, https://doi.org/10.1021/es405691q.","productDescription":"7 p.","startPage":"7222","endPage":"7228","numberOfPages":"7","ipdsId":"IP-052479","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":294646,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","city":"Austin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.938383,30.098659 ], [ -97.938383,30.516863 ], [ -97.56842,30.516863 ], [ -97.56842,30.098659 ], [ -97.938383,30.098659 ] ] ] } } ] }","volume":"48","issue":"13","noUsgsAuthors":false,"publicationDate":"2014-06-16","publicationStatus":"PW","scienceBaseUri":"542bc644e4b0abfb4c809879","contributors":{"authors":[{"text":"Van Metre, Peter C.","contributorId":34104,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","affiliations":[],"preferred":false,"id":502442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahler, Barbara 0000-0002-9150-9552 bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":502441,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70110857,"text":"ds855 - 2014 - Mobile terrestrial light detection and ranging (T-LiDAR) survey of areas on Dauphin Island, Alabama, in the aftermath of Hurricane Isaac, 2012","interactions":[],"lastModifiedDate":"2014-06-18T09:32:54","indexId":"ds855","displayToPublicDate":"2014-06-18T09:16:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"855","title":"Mobile terrestrial light detection and ranging (T-LiDAR) survey of areas on Dauphin Island, Alabama, in the aftermath of Hurricane Isaac, 2012","docAbstract":"Topographic survey data of areas on Dauphin Island on the Alabama coast were collected using a truck-mounted mobile terrestrial light detection and ranging system. This system is composed of a high frequency laser scanner in conjunction with an inertial measurement unit and a position and orientation computer to produce highly accurate topographic datasets. A global positioning system base station was set up on a nearby benchmark and logged vertical and horizontal position information during the survey for post-processing. Survey control points were also collected throughout the study area to determine residual errors. Data were collected 5 days after Hurricane Isaac made landfall in early September 2012 to document sediment deposits prior to clean-up efforts. Three data files in ASCII text format with the extension .xyz are included in this report, and each file is named according to both the acquisition date and the relative geographic location on Dauphin Island (for example, 20120903_Central.xyz). Metadata are also included for each of the files in both Extensible Markup Language with the extension .xml and ASCII text formats. These topographic data can be used to analyze the effects of storm surge on barrier island environments and also serve as a baseline dataset for future change detection analyses.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds855","issn":"2327-638X","usgsCitation":"Kimbrow, D.R., 2014, Mobile terrestrial light detection and ranging (T-LiDAR) survey of areas on Dauphin Island, Alabama, in the aftermath of Hurricane Isaac, 2012: U.S. Geological Survey Data Series 855, Report: HTML document; Downloads directory, https://doi.org/10.3133/ds855.","productDescription":"Report: HTML document; Downloads directory","onlineOnly":"Y","ipdsId":"IP-055484","costCenters":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"links":[{"id":288755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds855.gif"},{"id":288749,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0855/"},{"id":288753,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0855/title_page.html"},{"id":288754,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0855/Downloads"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.233333,30.216667 ], [ -88.233333,30.3 ], [ -88.083333,30.3 ], [ -88.083333,30.216667 ], [ -88.233333,30.216667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae777be4b0abf75cf2c147","contributors":{"authors":[{"text":"Kimbrow, Dustin R. dkimbrow@usgs.gov","contributorId":3915,"corporation":false,"usgs":true,"family":"Kimbrow","given":"Dustin","email":"dkimbrow@usgs.gov","middleInitial":"R.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494173,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70098143,"text":"ofr20141057 - 2014 - Histograms showing variations in oil yield, water yield, and specific gravity of oil from Fischer assay analyses of oil-shale drill cores and cuttings from the Piceance Basin, northwestern Colorado","interactions":[],"lastModifiedDate":"2014-06-18T09:03:04","indexId":"ofr20141057","displayToPublicDate":"2014-06-18T08:53:00","publicationYear":"2014","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":"2014-1057","title":"Histograms showing variations in oil yield, water yield, and specific gravity of oil from Fischer assay analyses of oil-shale drill cores and cuttings from the Piceance Basin, northwestern Colorado","docAbstract":"Recent studies indicate that the Piceance Basin in northwestern Colorado contains over 1.5 trillion barrels of oil in place, making the basin the largest known oil-shale deposit in the world. Previously published histograms display oil-yield variations with depth and widely correlate rich and lean oil-shale beds and zones throughout the basin. Histograms in this report display oil-yield data plotted alongside either water-yield or oil specific-gravity data. Fischer assay analyses of core and cutting samples collected from exploration drill holes penetrating the Eocene Green River Formation in the Piceance Basin can aid in determining the origins of those deposits, as well as estimating the amount of organic matter, halite, nahcolite, and water-bearing minerals. This report focuses only on the oil yield plotted against water yield and oil specific gravity.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141057","usgsCitation":"Dietrich, J.D., Brownfield, M.E., Johnson, R.C., and Mercier, T.J., 2014, Histograms showing variations in oil yield, water yield, and specific gravity of oil from Fischer assay analyses of oil-shale drill cores and cuttings from the Piceance Basin, northwestern Colorado: U.S. Geological Survey Open-File Report 2014-1057, Report: iii, 12p.; Downloads Directory, https://doi.org/10.3133/ofr20141057.","productDescription":"Report: iii, 12p.; Downloads Directory","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-041055","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":288746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141057.jpg"},{"id":288705,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1057/"},{"id":288742,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1057/pdf/ofr2014-1057.pdf"},{"id":288743,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1057/downloads/"}],"country":"United States","state":"Colorado","otherGeospatial":"Piceance Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.0,39.0 ], [ -112.0,43.0 ], [ -107.0,43.0 ], [ -107.0,39.0 ], [ -112.0,39.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7738e4b0abf75cf2c0ad","contributors":{"authors":[{"text":"Dietrich, John D.","contributorId":53841,"corporation":false,"usgs":true,"family":"Dietrich","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":491636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":491633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Ronald C. 0000-0002-6197-5165 rcjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-6197-5165","contributorId":1550,"corporation":false,"usgs":true,"family":"Johnson","given":"Ronald","email":"rcjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":491634,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mercier, Tracey J. 0000-0002-8232-525X tmercier@usgs.gov","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":2847,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey","email":"tmercier@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":491635,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70154769,"text":"70154769 - 2014 - Reproductive ecology of lampreys","interactions":[],"lastModifiedDate":"2017-05-08T15:28:44","indexId":"70154769","displayToPublicDate":"2014-06-18T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Reproductive ecology of lampreys","docAbstract":"<p><span>Lampreys typically spawn in riffle habitats during the spring. Spawning activity and diel (i.e., during daylight and at night) behavioral patterns are initiated when spring water temperatures increase to levels that coincide with optimal embryologic development. Nests are constructed in gravel substrate using the oral disc to move stones and the tail to fan sediment out of the nest. Spawning habitat used by individual species is generally a function of adult size, where small-bodied species construct nests in shallower water with slower flow and smaller gravel than large-bodied species. The mating system of lampreys is primarily polygynandrous (i.e., where multiple males mate with multiple females). Lamprey species with adult total length less than 30&nbsp;cm generally spawn communally, where a nest may contain 20 or more individuals of both sexes. Lamprey species with adult sizes greater than 35&nbsp;cm generally spawn in groups of two to four. Operational sex ratios of lampreys are highly variable across species, populations, and time, but are generally male biased. The act of spawning typically starts with the male attaching with his oral disc to the back of the female’s head; the male and female then entwine and simultaneously release gametes. However, alternative mating behaviors (e.g., release of gametes without paired courtship and sneaker males) have been observed. Future research should determine how multiple modalities of communication among lampreys (including mating pheromones) are integrated to inform species recognition and mate choice. Such research could inform both sea lamprey control strategies and provide insight into possible evolution of reproductive isolation mechanisms between paired lamprey species in sympatry.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Lampreys: Biology, Conservation and Control","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"Dordrecht","doi":"10.1007/978-94-017-9306-3_6","isbn":"978-94-017-9306-3","usgsCitation":"Johnson, N., Buchinger, T.J., and Li, W., 2014, Reproductive ecology of lampreys, chap. <i>of</i> Lampreys: Biology, Conservation and Control, p. 265-303, https://doi.org/10.1007/978-94-017-9306-3_6.","productDescription":"39 p.","startPage":"265","endPage":"303","ipdsId":"IP-028159","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":340956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-25","publicationStatus":"PW","scienceBaseUri":"591183b7e4b0e541a03c1a74","contributors":{"authors":[{"text":"Johnson, Nicholas S. njohnson@usgs.gov","contributorId":145449,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":564068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buchinger, Tyler J.","contributorId":40508,"corporation":false,"usgs":true,"family":"Buchinger","given":"Tyler","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":564069,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Li, Weiming","contributorId":65440,"corporation":false,"usgs":true,"family":"Li","given":"Weiming","affiliations":[],"preferred":false,"id":564070,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70155214,"text":"70155214 - 2014 - Aftershock risks such as those demonstrated by the recent events in New Zealand and Japan","interactions":[],"lastModifiedDate":"2017-05-30T11:21:41","indexId":"70155214","displayToPublicDate":"2014-06-18T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Aftershock risks such as those demonstrated by the recent events in New Zealand and Japan","docAbstract":"<p>Recent earthquakes in New Zealand and Japan show that it is important to consider the spatial and temporal distribution of aftershocks following large magnitude events since the probability of high intensity ground motions from aftershocks, which are capable of causing significant societal impact, can be considerable. This is due to the fact that a mainshock will have many aftershocks, some of which may occur closer to populated areas and may be large enough to cause damage. When a large magnitude event strikes a region, the chance that aftershocks will cause damage can be significant as was observed after the 2011 Tohoku and 2010 Canterbury earthquakes (e.g., damage caused by M<sub>w</sub>6.6 April 11, 2011 Fukushima-Hamadori earthquake following Tohoku earthquake or by M<sub>w</sub>6.3 February 22, 2011 Christchurch earthquake following Canterbury earthquake). Aftershock events may further damage already damaged buildings, thereby further complicating assessments of risk to the built environment. In this paper, the issue of aftershock risk is addressed by summarizing current research regarding: (1) aftershock hazard, (2) structural fragility/vulnerability before and after the mainshock, and (3) change in risk due to aftershocks.</p>","conferenceTitle":"Tenth U.S. National Conference on Earthquake Engineering","conferenceDate":"July 21-25, 2014","conferenceLocation":"Anchorage, Alaska","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Shome, N., Luco, N., Gerstenberger, M., Boyd, O.S., Field, E., Liel, A., and van de Lindt, J.W., 2014, Aftershock risks such as those demonstrated by the recent events in New Zealand and Japan, Tenth U.S. National Conference on Earthquake Engineering, Anchorage, Alaska, July 21-25, 2014, 11 p.","productDescription":"11 p.","ipdsId":"IP-055598","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":341832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592e84c3e4b092b266f10d86","contributors":{"authors":[{"text":"Shome, Nilesh","contributorId":145729,"corporation":false,"usgs":false,"family":"Shome","given":"Nilesh","email":"","affiliations":[{"id":16212,"text":"Model Development, Risk Management Solutions","active":true,"usgs":false}],"preferred":false,"id":565110,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":565111,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerstenberger, Matt","contributorId":22431,"corporation":false,"usgs":true,"family":"Gerstenberger","given":"Matt","email":"","affiliations":[],"preferred":false,"id":565112,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":565113,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":1165,"corporation":false,"usgs":true,"family":"Field","given":"Edward H.","email":"field@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":565114,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liel, Abbie","contributorId":145731,"corporation":false,"usgs":false,"family":"Liel","given":"Abbie","affiliations":[{"id":16213,"text":"Dept. of Civil, Environ. and Architectural  Engineering, University of Colorado","active":true,"usgs":false}],"preferred":false,"id":565115,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"van de Lindt, John W.","contributorId":42133,"corporation":false,"usgs":true,"family":"van de Lindt","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":565116,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70189901,"text":"70189901 - 2014 - Variability common to global sea surface temperatures and runoff in the conterminous United States","interactions":[],"lastModifiedDate":"2017-08-04T10:26:20","indexId":"70189901","displayToPublicDate":"2014-06-18T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Variability common to global sea surface temperatures and runoff in the conterminous United States","docAbstract":"<p><span>Singular value decomposition (SVD) is used to identify the variability common to global sea surface temperatures (SSTs) and water-balance-modeled water-year (WY) runoff in the conterminous United States (CONUS) for the 1900–2012 period. Two modes were identified from the SVD analysis; the two modes explain 25% of the variability in WY runoff and 33% of the variability in WY SSTs. The first SVD mode reflects the variability of the El Niño–Southern Oscillation (ENSO) in the SST data and the hydroclimatic effects of ENSO on WY runoff in the CONUS. The second SVD mode is related to variability of the Atlantic multidecadal oscillation (AMO). An interesting aspect of these results is that both ENSO and AMO appear to have nearly equivalent effects on runoff variability in the CONUS. However, the relatively small amount of variance explained by the SVD analysis indicates that there is little covariation between runoff and SSTs, suggesting that SSTs may not be a viable predictor of runoff variability for most of the conterminous United States.</span></p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-13-097.1","usgsCitation":"McCabe, G., and Wolock, D.M., 2014, Variability common to global sea surface temperatures and runoff in the conterminous United States: Journal of Hydrometeorology, v. 15, p. 714-725, https://doi.org/10.1175/JHM-D-13-097.1.","productDescription":"12 p.","startPage":"714","endPage":"725","ipdsId":"IP-051813","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":472934,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-13-097.1","text":"Publisher Index 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dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":706689,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70189761,"text":"70189761 - 2014 - The earthquake cycle in the San Francisco Bay region: A.D. 1600–2012","interactions":[],"lastModifiedDate":"2021-05-21T17:11:31.821686","indexId":"70189761","displayToPublicDate":"2014-06-18T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"The earthquake cycle in the San Francisco Bay region: A.D. 1600–2012","docAbstract":"<p><span>Stress changes produced by the 1906 San Francisco earthquake had a profound effect on the seismicity of the San Francisco Bay region (SFBR), dramatically reducing it in the twentieth century. Whether the SFBR is still within or has emerged from this seismic quiescence is an issue of debate with implications for earthquake mechanics and seismic hazards. Historically, the SFBR has not experienced one complete earthquake cycle (i.e., the accumulation of stress, its release primarily as coseismic slip during surface‐faulting earthquakes, its re‐accumulation in the interval following, and its subsequent rerelease). The historical record of earthquake occurrence in the SFBR appears to be complete at about&nbsp;</span><strong>M</strong><span>&nbsp;5.5 back to 1850 (</span><span id=\"xref-ref-2-1\" class=\"xref-bibr\">Bakun, 1999</span><span>). For large events, the record may be complete back to 1776, which represents about half a cycle. Paleoseismic data provide a more complete view of the most recent pre‐1906 SFBR earthquake cycle, extending it back to about 1600. Using these, we have developed estimates of magnitude and seismic moment for alternative sequences of surface‐faulting paleoearthquakes occurring between 1600 and 1776 on the region’s major faults. From these we calculate seismic moment and moment release rates for different time intervals between 1600 and 2012. These show the variability in moment release and suggest that, in the SFBR regional plate boundary, stress can be released on a single fault in great earthquakes such as that in 1906 and in multiple ruptures distributed on the regional plate boundary fault system on a decadal time scale.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120120322","usgsCitation":"Schwartz, D.P., Lienkaemper, J.J., Hecker, S., Kelson, K.I., Fumal, T.E., Baldwin, J.N., Seitz, G.G., and Niemi, T., 2014, The earthquake cycle in the San Francisco Bay region: A.D. 1600–2012: Bulletin of the Seismological Society of America, https://doi.org/10.1785/0120120322.","ipdsId":"IP-053346","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":344265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122,\n              39\n            ],\n            [\n              -120.5,\n              37.2\n            ],\n            [\n              -122.1,\n              36.4\n            ],\n            [\n              -123.5,\n              38.3\n            ],\n            [\n              -122,\n              39\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-05-20","publicationStatus":"PW","scienceBaseUri":"59770753e4b0ec1a48889fa4","contributors":{"authors":[{"text":"Schwartz, David P. 0000-0001-5193-9200 dschwartz@usgs.gov","orcid":"https://orcid.org/0000-0001-5193-9200","contributorId":1940,"corporation":false,"usgs":true,"family":"Schwartz","given":"David","email":"dschwartz@usgs.gov","middleInitial":"P.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lienkaemper, James J. 0000-0002-7578-7042 jlienk@usgs.gov","orcid":"https://orcid.org/0000-0002-7578-7042","contributorId":1941,"corporation":false,"usgs":true,"family":"Lienkaemper","given":"James","email":"jlienk@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706234,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hecker, Suzanne 0000-0002-5054-372X shecker@usgs.gov","orcid":"https://orcid.org/0000-0002-5054-372X","contributorId":3553,"corporation":false,"usgs":true,"family":"Hecker","given":"Suzanne","email":"shecker@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706235,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelson, Keith I.","contributorId":192585,"corporation":false,"usgs":false,"family":"Kelson","given":"Keith","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":706236,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fumal, Thomas E.","contributorId":195091,"corporation":false,"usgs":false,"family":"Fumal","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":706237,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baldwin, John N.","contributorId":195092,"corporation":false,"usgs":false,"family":"Baldwin","given":"John","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":706238,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Seitz, Gordon G.","contributorId":139062,"corporation":false,"usgs":false,"family":"Seitz","given":"Gordon","email":"","middleInitial":"G.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":706239,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Niemi, Tina","contributorId":195093,"corporation":false,"usgs":false,"family":"Niemi","given":"Tina","email":"","affiliations":[],"preferred":false,"id":706240,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70189903,"text":"70189903 - 2014 - Spatial and temporal patterns in conterminous United States streamflow characteristics","interactions":[],"lastModifiedDate":"2017-08-04T10:16:59","indexId":"70189903","displayToPublicDate":"2014-06-18T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal patterns in conterminous United States streamflow characteristics","docAbstract":"<p><span>Spatial and temporal patterns in annual and seasonal minimum, mean, and maximum daily streamflow values were examined for a set of 516 reference stream gauges located throughout the conterminous United States for the period 1951–2009. Cluster analysis was used to classify the stream gauges into 14 groups based on similarity in their temporal patterns of streamflow. The results indicated that the temporal patterns in flow metrics (1) have strong spatial coherence within each region, (2) are similar among the three annual flow metrics and the four seasonal flow metrics within each region, (3) indicate some small magnitude trends over time, and (4) are only weakly associated with well-known climate indices. We conclude that most of the temporal variability in flow is unpredictable in terms of relations to climate indices and infer that, for the most part, future changes in flow characteristics cannot be predicted by these indices.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014GL061980","usgsCitation":"McCabe, G., and Wolock, D.M., 2014, Spatial and temporal patterns in conterminous United States streamflow characteristics: Geophysical Research Letters, v. 41, no. 19, p. 6889-6897, https://doi.org/10.1002/2014GL061980.","productDescription":"9 p.","startPage":"6889","endPage":"6897","ipdsId":"IP-058033","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":706717,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70189606,"text":"70189606 - 2014 - Analysis of induced seismicity in geothermal reservoirs – An overview","interactions":[],"lastModifiedDate":"2017-07-19T10:03:10","indexId":"70189606","displayToPublicDate":"2014-06-18T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of induced seismicity in geothermal reservoirs – An overview","docAbstract":"<p><span>In this overview we report results of analysing induced seismicity in geothermal reservoirs in various tectonic settings within the framework of the European&nbsp;</span><i>G</i><span>eothermal<span>&nbsp;</span></span><i>E</i><span>ngineering<span>&nbsp;</span></span><i>I</i><span>ntegrating Mitigation of Induced<span>&nbsp;</span></span><i>Se</i><span>ismicity in<span>&nbsp;</span></span><i>R</i><span>eservoirs (GEISER) project. In the reconnaissance phase of a field, the subsurface fault mapping, in situ stress and the seismic network are of primary interest in order to help assess the geothermal resource. The hypocentres of the observed seismic events (seismic cloud) are dependent on the design of the installed network, the used velocity model and the applied location technique. During the stimulation phase, the attention is turned to reservoir hydraulics (e.g., fluid pressure, injection volume) and its relation to larger magnitude seismic events, their source characteristics and occurrence in space and time. A change in isotropic components of the full waveform moment tensor is observed for events close to the injection well (tensile character) as compared to events further away from the injection well (shear character). Tensile events coincide with high Gutenberg-Richter<span>&nbsp;</span></span><i>b</i><span>-values and low Brune stress drop values. The stress regime in the reservoir controls the direction of the fracture growth at depth, as indicated by the extent of the seismic cloud detected. Stress magnitudes are important in multiple stimulation of wells, where little or no seismicity is observed until the previous maximum stress level is exceeded (Kaiser Effect). Prior to drilling, obtaining a 3D<span>&nbsp;</span></span><i>P</i><span>-wave (</span><i>Vp</i><span>) and<span>&nbsp;</span></span><i>S</i><span>-wave velocity (</span><i>Vs</i><span>) model down to reservoir depth is recommended. In the stimulation phase, we recommend to monitor and to locate seismicity with high precision (decametre) in real-time and to perform local 4D tomography for velocity ratio (</span><i>Vp</i><span>/</span><i>Vs</i><span>). During exploitation, one should use observed and model induced seismicity to forward estimate seismic hazard so that field operators are in a position to adjust well hydraulics (rate and volume of the fluid injected) when induced events start to occur far away from the boundary of the seismic cloud.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2014.06.005","usgsCitation":"Zang, A., Oye, V., Jousset, P., Deichmann, N., Gritto, R., McGarr, A.F., Majer, E., and Bruhn, D., 2014, Analysis of induced seismicity in geothermal reservoirs – An overview: Geothermics, v. 52, p. 6-21, https://doi.org/10.1016/j.geothermics.2014.06.005.","productDescription":"16 p.","startPage":"6","endPage":"21","ipdsId":"IP-057945","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":472933,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://gfzpublic.gfz-potsdam.de/pubman/item/item_455903","text":"External Repository"},{"id":344025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59706fbce4b0d1f9f065a8f8","contributors":{"authors":[{"text":"Zang, Arno","contributorId":194794,"corporation":false,"usgs":false,"family":"Zang","given":"Arno","email":"","affiliations":[],"preferred":false,"id":705389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oye, Volker","contributorId":194795,"corporation":false,"usgs":false,"family":"Oye","given":"Volker","email":"","affiliations":[],"preferred":false,"id":705390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jousset, Philippe","contributorId":194796,"corporation":false,"usgs":false,"family":"Jousset","given":"Philippe","email":"","affiliations":[],"preferred":false,"id":705391,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deichmann, Nicholas","contributorId":194797,"corporation":false,"usgs":false,"family":"Deichmann","given":"Nicholas","email":"","affiliations":[],"preferred":false,"id":705392,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gritto, Roland","contributorId":194798,"corporation":false,"usgs":false,"family":"Gritto","given":"Roland","email":"","affiliations":[],"preferred":false,"id":705393,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McGarr, Arthur F. 0000-0001-9769-4093 mcgarr@usgs.gov","orcid":"https://orcid.org/0000-0001-9769-4093","contributorId":3178,"corporation":false,"usgs":true,"family":"McGarr","given":"Arthur","email":"mcgarr@usgs.gov","middleInitial":"F.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705388,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Majer, Ernest","contributorId":139408,"corporation":false,"usgs":false,"family":"Majer","given":"Ernest","affiliations":[{"id":6670,"text":"Lawrence Berkeley National Laboratory, Berkeley, CA","active":true,"usgs":false}],"preferred":false,"id":705394,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bruhn, David","contributorId":194799,"corporation":false,"usgs":false,"family":"Bruhn","given":"David","email":"","affiliations":[],"preferred":false,"id":705395,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70186901,"text":"70186901 - 2014 - Climate change and the Rocky Mountains","interactions":[],"lastModifiedDate":"2022-12-09T16:50:35.285225","indexId":"70186901","displayToPublicDate":"2014-06-18T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"20","title":"Climate change and the Rocky Mountains","docAbstract":"<p>Rural landscapes in the Andes are characterized by an impressive diversity of natural environments and by multiple resource assets. This is particularly the case in the tropical realm where the ecological altitudinal zones of the tierra caliente, the tierra templada, the tierra fria and the tierra helada</p><p>offer a remarkable range of agricultural potential. This is complemented by a multitude of topographic, hydrographic and climatic niches. The landscape is further overlaid by a cultural mosaic and by the recent impact of political ecology parameters. These agricultural ‘archipelagos’ and ‘overlapping patchworks’ (Zimmerer 1999) of human utilization also represent fragile and potentially vulnerable regions exposed to environmental risks and to socioeconomic or political threats. The external natural and human stimulators or stressors affecting the environment and people are complemented by new challenges and changes within the rural societies. Thus, farming and human settlement in the Andes have millennia tradition of an ‘open’ rural system, constantly adapting to an array of changing environmental, political, cultural, social and economic conditions (Stadel 2003b, Stadel 2008).</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Impact of global changes on mountains: Responses and adaptation","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","publisherLocation":"Boca Raton","usgsCitation":"Byrne, J.M., Fagre, D.B., and MacDonald, R., 2014, Climate change and the Rocky Mountains, chap. 20 <i>of</i> Impact of global changes on mountains: Responses and adaptation, p. 432-463.","productDescription":"32 p.","startPage":"432","endPage":"463","ipdsId":"IP-052658","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":339798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":339797,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.taylorfrancis.com/chapters/edit/10.1201/b17963-27/climate-change-rocky-mountains-james-byrne-daniel-fagre-ryan-macdonald?context=ubx&refId=81b9aeda-c946-4d44-a95a-4d647fd3f56c"}],"country":"Canada, United States","otherGeospatial":"Rocky Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -104.80281896878353,\n              35.61845241839859\n            ],\n            [\n              -103.95994773927038,\n              38.40516082657268\n            ],\n            [\n              -105.04737997456178,\n              42.80370874698866\n            ],\n            [\n              -109.38299642597238,\n              46.04935539414794\n            ],\n            [\n              -114.71114853091092,\n              50.45227486777216\n            ],\n            [\n              -124.6918171718354,\n              58.253966502202786\n            ],\n            [\n              -128.0537838658589,\n              59.37042496540823\n            ],\n            [\n              -128.9267207309033,\n              57.914437059438285\n            ],\n            [\n              -124.64320616598633,\n              53.79709661930235\n            ],\n            [\n              -119.5758714684903,\n              49.31776327850176\n            ],\n            [\n              -117.72607658192615,\n              44.15671034247009\n            ],\n            [\n              -113.9848561301589,\n              41.16547033261847\n            ],\n            [\n              -107.79034670316258,\n              37.61007651833016\n            ],\n            [\n              -105.2635964197159,\n              35.166549792981385\n            ],\n            [\n              -104.80281896878353,\n              35.61845241839859\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f5d444e4b0f2e20545e429","contributors":{"authors":[{"text":"Byrne, James M.","contributorId":190864,"corporation":false,"usgs":false,"family":"Byrne","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":690935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":690934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"MacDonald, Ryan","contributorId":190865,"corporation":false,"usgs":false,"family":"MacDonald","given":"Ryan","email":"","affiliations":[],"preferred":false,"id":690936,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70112724,"text":"ofr20141026 - 2014 - A field trip guidebook to the type localities of Marland Billings' 1935 Paleozoic bedrock stratigraphy near Littleton, New Hampshire","interactions":[],"lastModifiedDate":"2014-06-17T15:25:06","indexId":"ofr20141026","displayToPublicDate":"2014-06-17T15:18:00","publicationYear":"2014","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":"2014-1026","title":"A field trip guidebook to the type localities of Marland Billings' 1935 Paleozoic bedrock stratigraphy near Littleton, New Hampshire","docAbstract":"Marland Billings' classic paper published in 1937 in the Geological Society of America Bulletin established a succession of six stratigraphic units in rocks of low metamorphic grade near Littleton, New Hampshire. The two youngest units are fossiliferous in the area, with ages established at the time as “middle” Silurian and Early Devonian. Billings and students mapped the same stratigraphic section in adjacent areas of progressively higher regional metamorphic grade. This work laid the foundation upon which a major part of subsequent work in New England has been directly or indirectly built. This guidebook was written for a field trip held in March 2013 to visit roadcuts that are as close as possible in March to the type localities or areas of Billings’ six-fold stratigraphic succession. Ten stops are in rocks of chlorite grade of Acadian(?) metamorphism; the final stop visits amphibolite of the Ammonoosuc Volcanics. Fieldwork by the authors over the past 20 years confirms Billings’ broad conclusions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141026","usgsCitation":"Rankin, D., and Rankin, M.B., 2014, A field trip guidebook to the type localities of Marland Billings' 1935 Paleozoic bedrock stratigraphy near Littleton, New Hampshire: U.S. Geological Survey Open-File Report 2014-1026, iv, 21 p., https://doi.org/10.3133/ofr20141026.","productDescription":"iv, 21 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-044548","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":288704,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141026.jpg"},{"id":288703,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1026/pdf/ofr2014-1026.pdf"},{"id":288702,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1026/"}],"country":"United States","state":"New Hampshire","city":"Littleton","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.99938,44.239281 ], [ -71.99938,44.386765 ], [ -71.771166,44.386765 ], [ -71.771166,44.239281 ], [ -71.99938,44.239281 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7611e4b0abf75cf2be71","contributors":{"authors":[{"text":"Rankin, Douglas W. dwrankin@usgs.gov","contributorId":1770,"corporation":false,"usgs":true,"family":"Rankin","given":"Douglas W.","email":"dwrankin@usgs.gov","affiliations":[],"preferred":true,"id":494858,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rankin, Mary B.","contributorId":13151,"corporation":false,"usgs":true,"family":"Rankin","given":"Mary","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":494859,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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