{"pageNumber":"468","pageRowStart":"11675","pageSize":"25","recordCount":40783,"records":[{"id":70176306,"text":"sir20165124 - 2016 - FishVis, A regional decision support tool for identifying vulnerabilities of riverine habitat and fishes to climate change in the Great Lakes Region","interactions":[],"lastModifiedDate":"2019-12-30T14:43:18","indexId":"sir20165124","displayToPublicDate":"2016-10-13T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5124","title":"FishVis, A regional decision support tool for identifying vulnerabilities of riverine habitat and fishes to climate change in the Great Lakes Region","docAbstract":"<p>Climate change is expected to alter the distributions and community composition of stream fishes in the Great Lakes region in the 21st century, in part as a result of altered hydrological systems (stream temperature, streamflow, and habitat). Resource managers need information and tools to understand where fish species and stream habitats are expected to change under future conditions. Fish sample collections and environmental variables from multiple sources across the United States Great Lakes Basin were integrated and used to develop empirical models to predict fish species occurrence under present-day climate conditions. Random Forests models were used to predict the probability of occurrence of 13 lotic fish species within each stream reach in the study area. Downscaled climate data from general circulation models were integrated with the fish species occurrence models to project fish species occurrence under future climate conditions. The 13 fish species represented three ecological guilds associated with water temperature (cold, cool, and warm), and the species were distributed in streams across the Great Lakes region. Vulnerability (loss of species) and opportunity (gain of species) scores were calculated for all stream reaches by evaluating changes in fish species occurrence from present-day to future climate conditions. The 13 fish species included 4 cold-water species, 5 cool-water species, and 4 warm-water species. Presently, the 4 cold-water species occupy from 15 percent (55,000 kilometers [km]) to 35 percent (130,000 km) of the total stream length (369,215 km) across the study area; the 5 cool-water species, from 9 percent (33,000 km) to 58 percent (215,000 km); and the 4 warm-water species, from 9 percent (33,000 km) to 38 percent (141,000 km).</p><p>Fish models linked to projections from 13 downscaled climate models projected that in the mid to late 21st century (2046–65 and 2081–2100, respectively) habitats suitable for all 4 cold-water species and 4 of 5 cool-water species under present-day conditions will decline as much as 86 percent and as little as 33 percent, and habitats suitable for all 4 warm-water species will increase as much as 33 percent and as little as 7 percent. This report documents the approach and data used to predict and project fish species occurrence under present-day and future climate conditions for 13 lotic fish species in the United States Great Lakes Basin. A Web-based decision support mapping application termed “FishVis” was developed to provide a means to integrate, visualize, query, and download the results of these projected climate-driven responses and help inform conservation planning efforts within the region.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165124","collaboration":"Prepared in cooperation with Michigan State University, Michigan Department of Natural Resources Institute of Fisheries Research, and the Wisconsin Department of Natural Resources","usgsCitation":"Stewart, J.S., Covert, S.A., Estes, N.J., Westenbroek, S.M., Krueger, Damon, Wieferich, D.J., Slattery, M.T., Lyons, J.D., McKenna, J.E., Jr., Infante, D.M., and Bruce, J.L., 2016, FishVis, A regional decision support tool for identifying vulnerabilities of riverine habitat and fishes to climate change in the Great Lakes Region: U.S. Geological Survey Scientific Investigations Report 2016–5124, 15 p., with appendixes, https://dx.doi.org/10.3133/sir20165124.","productDescription":"Report: viii, 15 p.; Appendixes 1-4","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071837","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":438537,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74T6GGG","text":"USGS data release","linkHelpText":"FishVis, predicted occurrence and vulnerability for 13 fish species for current (1961 - 1990) and future (2046 - 2100) climate conditions in Great Lakes streams."},{"id":329488,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5124/coverthb.jpg"},{"id":329489,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5124/sir20165124.pdf","text":"Report","size":"2.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5124"},{"id":329490,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5124/sir20165124_appendixes1to4.xlsx","text":"Appendixes 1–4","size":"34.4 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5124 Appendixes"}],"country":"United States","otherGeospatial":"Great Lakes Region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.94433593749999,\n              46.5286346952717\n            ],\n            [\n              -86.66015624999999,\n              46.164614496897094\n            ],\n            [\n              -88.24218749999999,\n              44.715513732021336\n            ],\n            [\n              -87.978515625,\n              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          ],\n            [\n              -87.8466796875,\n              49.26780455063753\n            ],\n            [\n              -89.912109375,\n              48.42920055556841\n            ],\n            [\n              -92.021484375,\n              47.15984001304432\n            ],\n            [\n              -92.94433593749999,\n              46.5286346952717\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, Wisconsin Water Science Center<br>U.S. Geological Survey<br>8505 Research Way &nbsp;<br>Middleton, WI 53562</p><p><a href=\"http://wi.water.usgs.gov\" data-mce-href=\"http://wi.water.usgs.gov\">http://wi.water.usgs.gov</a></p>","tableOfContents":"<ul><li>Acknowledgments<br></li><li>Abstract<br></li><li>Introduction<br></li><li>Methods<br></li><li>Fish Species Occurrence Under Current and Future Climate Conditions<br></li><li>FishVis, A Web-Based Decision Support Mapping Application<br></li><li>Summary<br></li><li>References Cited<br></li><li>Appendixes 1–4<br></li></ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-10-13","noUsgsAuthors":false,"publicationDate":"2016-10-13","publicationStatus":"PW","scienceBaseUri":"57ffdefee4b0824b2d179cf0","contributors":{"authors":[{"text":"Stewart, Jana S. 0000-0002-8121-1373 jsstewar@usgs.gov","orcid":"https://orcid.org/0000-0002-8121-1373","contributorId":539,"corporation":false,"usgs":true,"family":"Stewart","given":"Jana","email":"jsstewar@usgs.gov","middleInitial":"S.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":648279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Covert, S. Alex sacovert@usgs.gov","contributorId":4941,"corporation":false,"usgs":true,"family":"Covert","given":"S.","email":"sacovert@usgs.gov","middleInitial":"Alex","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":648280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Estes, Nick J. njestes@usgs.gov","contributorId":5287,"corporation":false,"usgs":true,"family":"Estes","given":"Nick","email":"njestes@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":648281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Westenbroek, Stephen M. 0000-0002-6284-8643 smwesten@usgs.gov","orcid":"https://orcid.org/0000-0002-6284-8643","contributorId":2210,"corporation":false,"usgs":true,"family":"Westenbroek","given":"Stephen","email":"smwesten@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":648282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krueger, Damon","contributorId":174440,"corporation":false,"usgs":false,"family":"Krueger","given":"Damon","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":648284,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wieferich, Daniel J. 0000-0003-1554-7992 dwieferich@usgs.gov","orcid":"https://orcid.org/0000-0003-1554-7992","contributorId":5781,"corporation":false,"usgs":true,"family":"Wieferich","given":"Daniel","email":"dwieferich@usgs.gov","middleInitial":"J.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":648283,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Slattery, Michael T. mslattery@usgs.gov","contributorId":5470,"corporation":false,"usgs":true,"family":"Slattery","given":"Michael","email":"mslattery@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":648285,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lyons, John D.","contributorId":150808,"corporation":false,"usgs":false,"family":"Lyons","given":"John D.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":648286,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McKenna, James E. Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":627,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","suffix":"Jr.","email":"jemckenna@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":650851,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Infante, Dana M. 0000-0003-1385-1587","orcid":"https://orcid.org/0000-0003-1385-1587","contributorId":150821,"corporation":false,"usgs":false,"family":"Infante","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":18112,"text":"Dept. of Fisheries and Wildlife,","active":true,"usgs":false}],"preferred":false,"id":648288,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bruce, Jennifer L. 0000-0003-4915-5567 jlbruce@usgs.gov","orcid":"https://orcid.org/0000-0003-4915-5567","contributorId":132,"corporation":false,"usgs":true,"family":"Bruce","given":"Jennifer","email":"jlbruce@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":648289,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70176889,"text":"70176889 - 2016 - Thermal regimes, nonnative trout, and their influences on native Bull Trout in the Upper Klamath River Basin, Oregon","interactions":[],"lastModifiedDate":"2017-11-22T17:26:15","indexId":"70176889","displayToPublicDate":"2016-10-12T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Thermal regimes, nonnative trout, and their influences on native Bull Trout in the Upper Klamath River Basin, Oregon","docAbstract":"<p><span>The occurrence of fish species may be strongly influenced by a stream’s thermal regime (magnitude, frequency, variation, and timing). For instance, magnitude and frequency provide information about sublethal temperatures, variability in temperature can affect behavioral thermoregulation and bioenergetics, and timing of thermal events may cue life history events, such as spawning and migration. We explored the relationship between thermal regimes and the occurrences of native Bull Trout </span><i>Salvelinus confluentus</i><span> and nonnative Brook Trout </span><i>Salvelinus fontinalis</i><span> and Brown Trout </span><i>Salmo trutta</i><span> across 87 sites in the upper Klamath River basin, Oregon. Our objectives were to associate descriptors of the thermal regime with trout occurrence, predict the probability of Bull Trout occurrence, and estimate upper thermal tolerances of the trout species. We found that each species was associated with a different suite of thermal regime descriptors. Bull Trout were present at sites that were cooler, had fewer high-temperature events, had less variability, and took longer to warm. Brook Trout were also observed at cooler sites with fewer high-temperature events, but the sites were more variable and Brook Trout occurrence was not associated with a timing descriptor. In contrast, Brown Trout were present at sites that were warmer and reached higher temperatures faster, but they were not associated with frequency or variability descriptors. Among the descriptors considered, magnitude (specifically June degree-days) was the most important in predicting the probability of Bull Trout occurrence, and model predictions were strengthened by including Brook Trout occurrence. Last, all three trout species exhibited contrasting patterns of tolerating longer exposures to lower temperatures. Tolerance limits for Bull Trout were lower than those for Brook Trout and Brown Trout, with contrasts especially evident for thermal maxima. Our results confirm the value of exploring a suite of thermal regime descriptors for understanding the distribution and occurrence of fishes. Moreover, these descriptors and their relationships to fish should be considered with future changes in land use, water use, or climate.</span></p>","language":"English","publisher":"Taylor and Francis","doi":"10.1080/00028487.2016.1219677","usgsCitation":"Benjamin, J.R., Heltzel, J., Dunham, J.B., Heck, M., and Banish, N.P., 2016, Thermal regimes, nonnative trout, and their influences on native Bull Trout in the Upper Klamath River Basin, Oregon: Transactions of the American Fisheries Society, v. 145, no. 6, p. 1318-1330, https://doi.org/10.1080/00028487.2016.1219677.","productDescription":"13 p.","startPage":"1318","endPage":"1330","ipdsId":"IP-073755","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":470507,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Thermal_Regimes_Nonnative_Trout_and_Their_Influences_on_Native_Bull_Trout_in_the_Upper_Klamath_River_Basin_Oregon/4007463","text":"External Repository"},{"id":329486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.2283935546875,\n              42.0125705565935\n            ],\n            [\n              -122.2283935546875,\n              42.91620643817353\n            ],\n            [\n              -120.970458984375,\n              42.91620643817353\n            ],\n            [\n              -120.970458984375,\n              42.0125705565935\n            ],\n            [\n              -122.2283935546875,\n              42.0125705565935\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"145","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-11","publicationStatus":"PW","scienceBaseUri":"57ff4bf5e4b0824b2d159761","contributors":{"authors":[{"text":"Benjamin, Joseph R. 0000-0003-3733-6838 jbenjamin@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-6838","contributorId":3999,"corporation":false,"usgs":true,"family":"Benjamin","given":"Joseph","email":"jbenjamin@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":650613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heltzel, Jeannie","contributorId":175260,"corporation":false,"usgs":false,"family":"Heltzel","given":"Jeannie","email":"","affiliations":[{"id":27548,"text":"D.J. Warren & Associates Inc.","active":true,"usgs":false}],"preferred":false,"id":650614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":650612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heck, Michael 0000-0001-8858-7325 mheck@usgs.gov","orcid":"https://orcid.org/0000-0001-8858-7325","contributorId":4796,"corporation":false,"usgs":true,"family":"Heck","given":"Michael","email":"mheck@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":650615,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Banish, Nolan P.","contributorId":168511,"corporation":false,"usgs":false,"family":"Banish","given":"Nolan","email":"","middleInitial":"P.","affiliations":[{"id":25313,"text":"U.S. Fish and Wildlife Service, Klamath Falls Fish and Wildlife Office, 1936 California Avenue, Klamath Falls, Oregon, 97601, USA","active":true,"usgs":false}],"preferred":false,"id":650616,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70175527,"text":"sir20165119 - 2016 - Flood inundation maps for the Wabash River at New Harmony, Indiana","interactions":[],"lastModifiedDate":"2016-10-11T15:52:58","indexId":"sir20165119","displayToPublicDate":"2016-10-11T15:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5119","title":"Flood inundation maps for the Wabash River at New Harmony, Indiana","docAbstract":"<p>Digital flood-inundation maps for a 3.68-mile reach of the Wabash River extending 1.77 miles upstream and 1.91 miles downstream from streamgage 03378500 at New Harmony, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at <a href=\"http://water.usgs.gov/osw/flood_inundation/\" data-mce-href=\"http://water.usgs.gov/osw/flood_inundation/\">http://water.usgs.gov/osw/flood_inundation/</a>, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Wabash River at New Harmony, Ind. (station 03378500). Near-real-time stages at this streamgage may be obtained from the USGS National Water Information System at <a href=\"http://waterdata.usgs.gov\" data-mce-href=\"http://waterdata.usgs.gov\">http://waterdata.usgs.gov/</a> or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at <a href=\"http://water.weather.gov/ahps/\" data-mce-href=\"http://water.weather.gov/ahps/\"> http://water.weather.gov/ahps/</a>, which also forecasts flood hydrographs at this site (NHRI3).</p><p>Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at the Wabash River at New Harmony, Ind., streamgage and the documented high-water marks from the flood of April 27–28, 2013. The calibrated hydraulic model was then used to compute 17 water-surface profiles for flood stages at approximately 1-foot intervals referenced to the streamgage datum and ranging from 10.0 feet, or near bankfull, to 25.4 feet, the highest stage of the stage-discharge rating curve used in the model. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging (lidar) data having a 0.98-ft vertical accuracy and 4.9-ft horizontal resolution) to delineate the area flooded at each water level.</p><p>The availability of these maps along with Internet information regarding current stage from the USGS streamgage at Wabash River at New Harmony, Ind., and forecasted stream stages from the NWS will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165119","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Fowler, K.K., 2016, Flood-inundation maps for the Wabash River at New Harmony, Indiana: U.S. Geological Survey Scientific Investigations Report 2016–5119, 14 p., https://dx.doi.org/10.3133/sir20165119.","productDescription":"Report: vii, 14 p.; Metadata; Read Me; Spatial Data","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066894","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":329430,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2016/5119/downloads/metadata_depth_grids.pdf","text":"Metadata Depth Grids","size":"94.3 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5119"},{"id":329431,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2016/5119/downloads/metadata_shapefile.pdf","text":"Metadata Shapefiles","size":"94.9 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5119"},{"id":329432,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2016/5119/downloads/00Readme.pdf","text":"Readme","size":"82.6 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5119"},{"id":329433,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2016/5119/downloads/depth_grids.zip","text":"Depth Grids","size":"144 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5119"},{"id":329434,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2016/5119/downloads/shapefiles.zip","text":"Shape File","size":"2.40 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5119"},{"id":329410,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5119/coverthb.jpg"},{"id":329411,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5119/sir20165119.pdf","text":"Report","size":"14.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5119"}],"country":"United States","state":"Indiana","city":"New Harmony","otherGeospatial":"Wabash River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.03173065185545,\n              38.10700680156137\n            ],\n            [\n              -88.03173065185545,\n              38.171003529816126\n            ],\n            [\n              -87.8580093383789,\n              38.171003529816126\n            ],\n            [\n              -87.8580093383789,\n              38.10700680156137\n            ],\n            [\n              -88.03173065185545,\n              38.10700680156137\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_in@usgs.gov\" data-mce-href=\"mailto:dc_in@usgs.gov\">Director</a>, Indiana-Kentucky Water Science Center <br> U.S. Geological Survey<br> 5957 Lakeside Boulevard<br> Indianapolis, IN 46278<br> <a href=\"http://in.water.usgs.gov/\" data-mce-href=\"http://in.water.usgs.gov/\">http://in.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract&nbsp;</li><li>Introduction</li><li>Creation of Flood-Inundation Map Library</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-10-11","noUsgsAuthors":false,"publicationDate":"2016-10-11","publicationStatus":"PW","scienceBaseUri":"57fe6799e4b0824b2d1436eb","contributors":{"authors":[{"text":"Fowler, Kathleen K. 0000-0002-0107-3848 kkfowler@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3848","contributorId":2439,"corporation":false,"usgs":true,"family":"Fowler","given":"Kathleen","email":"kkfowler@usgs.gov","middleInitial":"K.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":645565,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70174941,"text":"ofr20161062 - 2016 - Evaluating models of population process in a threatened population of Steller’s eiders: A retrospective approach","interactions":[],"lastModifiedDate":"2016-10-12T08:39:36","indexId":"ofr20161062","displayToPublicDate":"2016-10-11T15:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1062","title":"Evaluating models of population process in a threatened population of Steller’s eiders: A retrospective approach","docAbstract":"<p>The Alaskan breeding population of Steller’s eiders (<i>Polysticta stelleri</i>) was listed as threatened under the Endangered Species Act in 1997 in response to perceived declines in abundance throughout their breeding and nesting range. Aerial surveys suggest the breeding population is small and highly variable in number, with zero birds counted in 5 of the last 25 years. Research was conducted to evaluate competing population process models of Alaskan-breeding Steller’s eiders through comparison of model projections to aerial survey data. To evaluate model efficacy and estimate demographic parameters, a Bayesian state-space modeling framework was used and each model was fit to counts from the annual aerial surveys, using sequential importance sampling and resampling. The results strongly support that the Alaskan breeding population experiences population level nonbreeding events and is open to exchange with the larger Russian-Pacific breeding population. Current recovery criteria for the Alaskan breeding population rely heavily on the ability to estimate population viability. The results of this investigation provide an informative model of the population process that can be used to examine future population states and assess the population in terms of the current recovery and reclassification criteria.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161062","usgsCitation":"Dunham, Kylee, and Grand, J.B., 2016, Evaluating models of population process in a threatened population of Steller’s eiders—A retrospective approach: U.S. Geological Survey Open-File Report 2016–1062, 14 p., https://dx.doi.org/10.3133/ofr20161062.","productDescription":"vi, 14 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074896","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":329250,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/preview/ofr20161084","text":"Open-File Report 2016–1084","description":"Open-File Report 2016–1084","linkHelpText":"- Viability of the Alaskan Breeding Population of Steller’s Eiders"},{"id":329247,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1062/ofr20161062.pdf","text":"Report","size":"355 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1062"},{"id":329246,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1062/coverthb.jpg"}],"contact":"<p>Chief, Cooperative Research Units<br> U.S. Geological Survey<br> 12201 Sunrise Valley Drive<br> Reston, VA 20192-0002<br> <a href=\"https://www.usgs.gov/science/mission-areas/ecosystems\" data-mce-href=\"https://www.usgs.gov/science/mission-areas/ecosystems\">https://www.usgs.gov/science/mission-areas/ecosystems </a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>1 Introduction</li><li>2 Methods</li><li>3 Results</li><li>4 Discussion</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-10-11","noUsgsAuthors":false,"publicationDate":"2016-10-11","publicationStatus":"PW","scienceBaseUri":"57fe679ae4b0824b2d1436ed","contributors":{"authors":[{"text":"Dunham, Kylee","contributorId":173081,"corporation":false,"usgs":false,"family":"Dunham","given":"Kylee","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":643254,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":643253,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70174940,"text":"ofr20161084 - 2016 - Viability of the Alaskan breeding population of Steller’s eiders","interactions":[],"lastModifiedDate":"2016-10-11T15:47:23","indexId":"ofr20161084","displayToPublicDate":"2016-10-11T15:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1084","title":"Viability of the Alaskan breeding population of Steller’s eiders","docAbstract":"<p>The U.S. Fish and Wildlife Service is tasked with setting objective and measurable criteria for delisting species or populations listed under the Endangered Species Act. Determining the acceptable threshold for extinction risk for any species or population is a challenging task, particularly when facing marked uncertainty. The Alaskan breeding population of Steller’s eiders (<i>Polysticta stelleri</i>) was listed as threatened under the Endangered Species Act in 1997 because of a perceived decline in abundance throughout their nesting range and geographic isolation from the Russian breeding population. Previous genetic studies and modeling efforts, however, suggest that there may be dispersal from the Russian breeding population. Additionally, evidence exists of population level nonbreeding events. Research was conducted to estimate population viability of the Alaskan breeding population of Steller’s eiders, using both an open and closed model of population process for this threatened population. Projections under a closed population model suggest this population has a 100 percent probability of extinction within 42 years. Projections under an open population model suggest that with immigration there is no probability of permanent extinction. Because of random immigration process and nonbreeding behavior, however, it is likely that this population will continue to be present in low and highly variable numbers on the breeding grounds in Alaska. Monitoring the winter population, which includes both Russian and Alaskan breeding birds, may offer a more comprehensive indication of population viability.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161084","usgsCitation":"Dunham, Kylee, and Grand, J.B., 2016, Viability of the Alaskan breeding population of Steller’s eiders: U.S. Geological Survey Open-File Report 2016–1084, 8 p., https://dx.doi.org/10.3133/ofr20161084.","productDescription":"v, 8 p.","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074532","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":329251,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/preview/ofr20161062","text":"Open-File Report 2016–1062","description":"Open-File Report 2016–1062","linkHelpText":"- Evaluating Models of Population Process in a Threatened Population of Steller’s Eiders: A Retrospective Approach"},{"id":329249,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1084/ofr20161084.pdf","text":"Report","size":"232 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1084"},{"id":329248,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1084/coverthb.jpg"}],"contact":"<p>Chief, Cooperative Research Units<br> U.S. Geological Survey<br> 12201 Sunrise Valley Drive<br> Reston, VA 20192-0002<br> <a href=\"https://www.usgs.gov/science/mission-areas/ecosystems\" data-mce-href=\"https://www.usgs.gov/science/mission-areas/ecosystems\">https://www.usgs.gov/science/mission-areas/ecosystems </a></p>","tableOfContents":"<ul><li>Ackknowledgments&nbsp;</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-10-11","noUsgsAuthors":false,"publicationDate":"2016-10-11","publicationStatus":"PW","scienceBaseUri":"57fe679ae4b0824b2d1436ef","contributors":{"authors":[{"text":"Dunham, Kylee","contributorId":173081,"corporation":false,"usgs":false,"family":"Dunham","given":"Kylee","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":643252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":643251,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70176844,"text":"70176844 - 2016 - Climate change is advancing spring onset across the U.S. national park system","interactions":[],"lastModifiedDate":"2016-10-13T15:40:08","indexId":"70176844","displayToPublicDate":"2016-10-11T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Climate change is advancing spring onset across the U.S. national park system","docAbstract":"<p><span>Many U.S. national parks are already at the extreme warm end of their historical temperature distributions. With rapidly warming conditions, park resource management will be enhanced by information on seasonality of climate that supports adjustments in the timing of activities such as treating invasive species, operating visitor facilities, and scheduling climate-related events (e.g., flower festivals and fall leaf-viewing). Seasonal changes in vegetation, such as pollen, seed, and fruit production, are important drivers of ecological processes in parks, and phenology has thus been identified as a key indicator for park monitoring. Phenology is also one of the most proximate biological responses to climate change. Here, we use estimates of start of spring based on climatically modeled dates of first leaf and first bloom derived from indicator plant species to evaluate the recent timing of spring onset (past 10–30&nbsp;yr) in each U.S. natural resource park relative to its historical range of variability across the past 112&nbsp;yr (1901–2012). Of the 276 high latitude to subtropical parks examined, spring is advancing in approximately three-quarters of parks (76%), and 53% of parks are experiencing “extreme” early springs that exceed 95% of historical conditions. Our results demonstrate how changes in climate seasonality are important for understanding ecological responses to climate change, and further how spatial variability in effects of climate change necessitates different approaches to management. We discuss how our results inform climate change adaptation challenges and opportunities facing parks, with implications for other protected areas, by exploring consequences for resource management and planning.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1465","usgsCitation":"Monahan, W.B., Rosemartin, A., Gerst, K.L., Fisichelli, N.A., Ault, T.R., Schwartz, M.D., Gross, J.E., and Weltzin, J., 2016, Climate change is advancing spring onset across the U.S. national park system: Ecosphere, v. 7, no. 10, p. 1-17, https://doi.org/10.1002/ecs2.1465.","productDescription":"e01465; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-072799","costCenters":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"links":[{"id":470511,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1465","text":"Publisher Index Page"},{"id":329420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-06","publicationStatus":"PW","scienceBaseUri":"57fe679be4b0824b2d1436ff","contributors":{"authors":[{"text":"Monahan, William B.","contributorId":175225,"corporation":false,"usgs":false,"family":"Monahan","given":"William","email":"","middleInitial":"B.","affiliations":[{"id":27542,"text":"NPS I&M","active":true,"usgs":false}],"preferred":false,"id":650493,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosemartin, Alyssa","contributorId":175226,"corporation":false,"usgs":false,"family":"Rosemartin","given":"Alyssa","affiliations":[],"preferred":false,"id":650494,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerst, Katharine L.","contributorId":175227,"corporation":false,"usgs":false,"family":"Gerst","given":"Katharine","email":"","middleInitial":"L.","affiliations":[{"id":27543,"text":"National Phenology Network, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":650495,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisichelli, Nicholas A.","contributorId":174508,"corporation":false,"usgs":false,"family":"Fisichelli","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[{"id":27461,"text":"NPS, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":650496,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ault, Toby R.","contributorId":146164,"corporation":false,"usgs":false,"family":"Ault","given":"Toby","email":"","middleInitial":"R.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":650498,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwartz, Mark D.","contributorId":175228,"corporation":false,"usgs":false,"family":"Schwartz","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":18038,"text":"University of Wisconsin, Milwaukee","active":true,"usgs":false}],"preferred":false,"id":650499,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gross, John E.","contributorId":106777,"corporation":false,"usgs":false,"family":"Gross","given":"John","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":650497,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weltzin, Jake F. jweltzin@usgs.gov","contributorId":296,"corporation":false,"usgs":true,"family":"Weltzin","given":"Jake F.","email":"jweltzin@usgs.gov","affiliations":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"preferred":false,"id":650492,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70176846,"text":"70176846 - 2016 - Atmospheric inputs of organic matter to a forested watershed: Variations from storm to storm over the seasons","interactions":[],"lastModifiedDate":"2016-10-21T13:07:56","indexId":"70176846","displayToPublicDate":"2016-10-11T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":924,"text":"Atmospheric Environment","active":true,"publicationSubtype":{"id":10}},"title":"Atmospheric inputs of organic matter to a forested watershed: Variations from storm to storm over the seasons","docAbstract":"<p><span>The objectives of this study were to determine the quantity and chemical composition of precipitation inputs of dissolved organic carbon (DOC) to a forested watershed; and to characterize the associated temporal variability. We sampled most precipitation that occurred from May 2012 through August 2013&nbsp;at the Susquehanna Shale Hills Critical Zone Observatory (Pennsylvania, USA). Sub-event precipitation samples (159) were collected sequentially during 90 events; covering various types of synoptic meteorological conditions in all climatic seasons. Precipitation DOC concentrations and rates of wet atmospheric DOC deposition were highly variable from storm to storm, ranging from 0.3 to 5.6&nbsp;mg&nbsp;C&nbsp;L</span><sup>−1</sup><span> and from 0.5 to 32.8&nbsp;mg&nbsp;C&nbsp;m</span><sup>−2</sup><span>&nbsp;h</span><sup>−1</sup><span>, respectively. Seasonally, storms in spring and summer had higher concentrations of DOC and more optically active organic matter than in winter. Higher DOC concentrations resulted from weather types that favor air advection, where cold frontal systems, on average, delivered more than warm/stationary fronts and northeasters. A mixed modeling statistical approach revealed that factors related to storm properties, emission sources, and to the chemical composition of the atmosphere could explain more than 60% of the storm to storm variability in DOC concentrations. This study provided observations on changes in dissolved organic matter that can be useful in modeling of atmospheric oxidative chemistry, exploring relationships between organics and other elements of precipitation chemistry, and in considering temporal changes in ecosystem nutrient balances and microbial activity.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.atmosenv.2016.10.002","usgsCitation":"Iavorivska, L., Boyer, E.W., Miller, M.P., Brown, M.G., Vasilopoulos, T., Fuentes, J.D., and Duffy, C.J., 2016, Atmospheric inputs of organic matter to a forested watershed: Variations from storm to storm over the seasons: Atmospheric Environment, v. 147, p. 284-295, https://doi.org/10.1016/j.atmosenv.2016.10.002.","productDescription":"12 p.","startPage":"284","endPage":"295","ipdsId":"IP-077852","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":470512,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.atmosenv.2016.10.002","text":"Publisher Index Page"},{"id":329417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57fe679be4b0824b2d1436fd","contributors":{"authors":[{"text":"Iavorivska, Lidiia","contributorId":175230,"corporation":false,"usgs":false,"family":"Iavorivska","given":"Lidiia","email":"","affiliations":[],"preferred":false,"id":650525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyer, Elizabeth W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":650526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Michael G.","contributorId":175231,"corporation":false,"usgs":false,"family":"Brown","given":"Michael","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":650527,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vasilopoulos, Terrie","contributorId":175245,"corporation":false,"usgs":false,"family":"Vasilopoulos","given":"Terrie","email":"","affiliations":[],"preferred":false,"id":650528,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fuentes, Jose D.","contributorId":97231,"corporation":false,"usgs":true,"family":"Fuentes","given":"Jose","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":650529,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Duffy, Christopher J.","contributorId":175246,"corporation":false,"usgs":false,"family":"Duffy","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":650530,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70176830,"text":"70176830 - 2016 - Potential effects of climate change on streamflow for seven watersheds in eastern and central Montana","interactions":[],"lastModifiedDate":"2017-03-10T11:22:18","indexId":"70176830","displayToPublicDate":"2016-10-11T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Potential effects of climate change on streamflow for seven watersheds in eastern and central Montana","docAbstract":"<h4 id=\"absSec_1\">Study region</h4><p id=\"spar0040\">Eastern and central Montana.</p><h4 id=\"absSec_2\">Study focus</h4><p id=\"spar0045\">Fish in Northern Great Plains streams tolerate extreme conditions including heat, cold, floods, and drought; however changes in streamflow associated with long-term climate change may render some prairie streams uninhabitable for current fish species. To better understand future hydrology of these prairie streams, the Precipitation-Runoff Modeling System model and output from the RegCM3 Regional Climate model were used to simulate streamflow for seven watersheds in eastern and central Montana, for a baseline period (water years 1982–1999) and three future periods: water years 2021–2038 (2030 period), 2046–2063 (2055 period), and 2071–2088 (2080 period).</p><h4 id=\"absSec_3\">New hydrological insights for the region</h4><p id=\"spar0050\">Projected changes in mean annual and mean monthly streamflow vary by the RegCM3 model selected, by watershed, and by future period. Mean annual streamflows for all future periods are projected to increase (11–21%) for two of the four central Montana watersheds: Middle Musselshell River and Cottonwood Creek. Mean annual streamflows for all future periods are projected to decrease (changes of −24 to −75%) for Redwater River watershed in eastern Montana. Mean annual streamflows are projected to increase slightly (2–15%) for the 2030 period and decrease (changes of −16 to −44%) for the 2080 period for the four remaining watersheds.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2016.06.001","usgsCitation":"Chase, K.J., Haj, A., Regan, R.S., and Viger, R., 2016, Potential effects of climate change on streamflow for seven watersheds in eastern and central Montana: Journal of Hydrology: Regional Studies, v. 7, p. 69-81, https://doi.org/10.1016/j.ejrh.2016.06.001.","productDescription":"13 p.","startPage":"69","endPage":"81","ipdsId":"IP-062632","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":470510,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2016.06.001","text":"Publisher Index Page"},{"id":438538,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P26W5S","text":"USGS data release","linkHelpText":"Documentation of the Precipitation-Runoff Modeling System and Output from the RegCM3 Regional Climate Model Used to Estimate Potential Effects of Climate Change on Streamflow for Seven Watersheds in Eastern and Central Montana (2013-2014 Analyses)"},{"id":329422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":337329,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/doi:10.5066/F7P26W5S","text":"Potential effects of climate change on streamflow in eastern and central Montana (2013-2014 analyses) - PRMS model input and output"}],"country":"United 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Steven 0000-0003-4803-8596","orcid":"https://orcid.org/0000-0003-4803-8596","contributorId":87237,"corporation":false,"usgs":true,"family":"Regan","given":"R.","email":"","middleInitial":"Steven","affiliations":[],"preferred":false,"id":650481,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":1204,"corporation":false,"usgs":true,"family":"Viger","given":"Roland J.","email":"rviger@usgs.gov","affiliations":[],"preferred":false,"id":650482,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70176859,"text":"70176859 - 2016 - Large-scale changes in bloater growth and condition in Lake Huron","interactions":[],"lastModifiedDate":"2016-10-11T15:14:08","indexId":"70176859","displayToPublicDate":"2016-10-11T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Large-scale changes in bloater growth and condition in Lake Huron","docAbstract":"<p>Native Bloaters <i>Coregonus hoyi</i> have exhibited multiple strong year-classes since 2005 and now are the most abundant benthopelagic offshore prey fish in Lake Huron, following the crash of nonnative Alewives<i>Alosa pseudoharengus</i> and substantial declines in nonnative Rainbow Smelt <i>Osmerus mordax</i>. Despite recent recoveries in Bloater abundance, marketable-size (&gt;229 mm) Bloaters remain scarce. We used annual survey data to assess temporal and spatial dynamics of Bloater body condition and lengths at age in the main basin of Lake Huron from 1973 to 2014. Basinwide lengths at age were modeled by cohort for the 1973–2003 year-classes using a von Bertalanffy growth model with time-varying Brody growth coefficient (<i>k</i>) and asymptotic length (<img src=\"http://www.tandfonline.com/na101/home/literatum/publisher/tandf/journals/content/utaf20/2016/utaf20.v145.i06/00028487.2016.1214176/20161007/images/utaf_a_1214176_ilm0001.gif\" alt=\"\" data-formula-source=\"{&quot;type&quot; : &quot;image&quot;, &quot;src&quot; : &quot;/na101/home/literatum/publisher/tandf/journals/content/utaf20/2016/utaf20.v145.i06/00028487.2016.1214176/20161007/images/utaf_a_1214176_ilm0001.gif&quot;}\" data-mce-src=\"http://www.tandfonline.com/na101/home/literatum/publisher/tandf/journals/content/utaf20/2016/utaf20.v145.i06/00028487.2016.1214176/20161007/images/utaf_a_1214176_ilm0001.gif\"><span>) parameters. Median Bloater weights at selected lengths were estimated to assess changes in condition by modeling weight–length relations with an allometric growth model that allowed growth parameters to vary spatially and temporally. Estimated Bloater lengths at age declined 14–24% among ages 4–8 for all year-classes between 1973 and 2004. Estimates of&nbsp;</span><img src=\"http://www.tandfonline.com/na101/home/literatum/publisher/tandf/journals/content/utaf20/2016/utaf20.v145.i06/00028487.2016.1214176/20161007/images/utaf_a_1214176_ilm0002.gif\" alt=\"\" data-formula-source=\"{&quot;type&quot; : &quot;image&quot;, &quot;src&quot; : &quot;/na101/home/literatum/publisher/tandf/journals/content/utaf20/2016/utaf20.v145.i06/00028487.2016.1214176/20161007/images/utaf_a_1214176_ilm0002.gif&quot;}\" data-mce-src=\"http://www.tandfonline.com/na101/home/literatum/publisher/tandf/journals/content/utaf20/2016/utaf20.v145.i06/00028487.2016.1214176/20161007/images/utaf_a_1214176_ilm0002.gif\"><span> declined from a peak of 394 mm (1973 year-class) to a minimum of 238 mm (1998 year-class). Observed mean lengths at age in 2014 were at all-time lows, suggesting that year-classes comprising the current Bloater population would have to follow growth trajectories unlike those characterizing the 1973–2003 year-classes to attain marketable size. Furthermore, estimated weights of 250-mm Bloaters (i.e., a large, commercially valuable size-class) declined 17% among all regions from 1976 to 2007. Decreases in body condition of large Bloaters are associated with lower lipid content and may be linked to marked declines in abundance of the amphipods</span><i>Diporeia</i><span> spp. in Lake Huron. We hypothesize that since at least 1976, large Bloaters have become more negatively buoyant and may have incurred an increasingly greater metabolic cost performing diel vertical migrations to prey upon the opossum shrimp </span><i>Mysis diluviana</i><span> and zooplankton.</span><br></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2016.1214176","usgsCitation":"Prichard, C.G., Roseman, E., Keeler, K.M., O’Brien, T.P., and Riley, S.C., 2016, Large-scale changes in bloater growth and condition in Lake Huron: Transactions of the American Fisheries Society, v. 145, no. 6, p. 1241-1251, https://doi.org/10.1080/00028487.2016.1214176.","productDescription":"11 p.","startPage":"1241","endPage":"1251","ipdsId":"IP-074730","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":329461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Huron","volume":"145","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-07","publicationStatus":"PW","scienceBaseUri":"57fe679ae4b0824b2d1436f7","contributors":{"authors":[{"text":"Prichard, Carson G. cprichard@usgs.gov","contributorId":168429,"corporation":false,"usgs":true,"family":"Prichard","given":"Carson","email":"cprichard@usgs.gov","middleInitial":"G.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":650542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roseman, Edward F. eroseman@usgs.gov","contributorId":534,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","email":"eroseman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":650541,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keeler, Kevin M. 0000-0002-8118-0060 kkeeler@usgs.gov","orcid":"https://orcid.org/0000-0002-8118-0060","contributorId":4377,"corporation":false,"usgs":true,"family":"Keeler","given":"Kevin","email":"kkeeler@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":650543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Brien, Timothy P. 0000-0003-4502-5204 tiobrien@usgs.gov","orcid":"https://orcid.org/0000-0003-4502-5204","contributorId":2662,"corporation":false,"usgs":true,"family":"O’Brien","given":"Timothy","email":"tiobrien@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":650544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riley, Stephen C. 0000-0002-8968-8416 sriley@usgs.gov","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":2661,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen","email":"sriley@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":650545,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70200351,"text":"70200351 - 2016 - Automatic delineation of seacliff limits using lidar-derived high-resolution DEMs in southern California","interactions":[],"lastModifiedDate":"2018-12-13T09:14:06","indexId":"70200351","displayToPublicDate":"2016-10-10T14:57:03","publicationYear":"2016","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":"Automatic delineation of seacliff limits using lidar-derived high-resolution DEMs in southern California","docAbstract":"<p><span>Seacliff erosion is a serious hazard with implications for coastal management and is often estimated using successive hand-digitized cliff tops or bases (toe) to assess cliff retreat. Even if efforts are made to standardize manual digitizing and eliminate subjectivity, the delineation of cliffs is time-consuming and depends on the analyst's interpretation. An automatic procedure is proposed to extract cliff edges from high-resolution lidar-derived bare-earth digital elevation models, generalized coastal shoreline vectors, and approximate measurements of distance between the shoreline and the cliff top. The method generates orthogonal transects and profiles with a minimum spacing equal to the digital elevation model resolution. The method also extracts the xyz coordinates for each profile for the cliff top and toe, as well as second major inflections along the profile. Over 75% of the automated cliff top points and 78% of the toe automated points are within 95% confidence interval of the hand-digitized top and toe lines, and over 79% of the digitized top points and 84% of the digitized toe points are within the 95% confidence interval of the automated top and toe lines along a stretch of coast in Del Mar, California. Outlier errors were caused by either the failure to remove all vegetation from the bare-earth digital elevation model or errors of interpretation. The automatic method was further applied between Point Conception and Los Angeles Harbor, California. This automatic method is repeatable, takes advantage of detailed topographic information within high-resolution digital elevation models, and is more efficient than hand-digitizing.</span></p>","language":"English","publisher":"Coastal Education & Research Foundation","doi":"10.2112/SI76-014","usgsCitation":"Palaseanu-Lovejoy, M., Danielson, J.J., Thatcher, C.A., Foxgrover, A.C., Barnard, P., Brock, J., and Young, A., 2016, Automatic delineation of seacliff limits using lidar-derived high-resolution DEMs in southern California: Journal of Coastal Research, no. Special Issue 76, p. 162-173, https://doi.org/10.2112/SI76-014.","productDescription":"12 p.","startPage":"162","endPage":"173","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"links":[{"id":462063,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.2112/SI76-014","text":"External Repository"},{"id":358353,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","issue":"Special Issue 76","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10ada1e4b034bf6a7e78e5","contributors":{"authors":[{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":748458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":748459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":748460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foxgrover, Amy C. 0000-0003-0638-5776 afoxgrover@usgs.gov","orcid":"https://orcid.org/0000-0003-0638-5776","contributorId":3261,"corporation":false,"usgs":true,"family":"Foxgrover","given":"Amy","email":"afoxgrover@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":748461,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":748462,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":748463,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Young, Adam","contributorId":177578,"corporation":false,"usgs":false,"family":"Young","given":"Adam","affiliations":[],"preferred":false,"id":748464,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70184237,"text":"70184237 - 2016 - Evaluating land cover influences on model uncertainties—A case study of cropland carbon dynamics in the Mid-Continent Intensive Campaign region","interactions":[],"lastModifiedDate":"2017-05-09T12:44:23","indexId":"70184237","displayToPublicDate":"2016-10-10T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating land cover influences on model uncertainties—A case study of cropland carbon dynamics in the Mid-Continent Intensive Campaign region","docAbstract":"<p><span>Quantifying spatial and temporal patterns of carbon sources and sinks and their uncertainties across agriculture-dominated areas remains challenging for understanding regional carbon cycles. Characteristics of local land cover inputs could impact the regional carbon estimates but the effect has not been fully evaluated in the past. Within the North American Carbon Program Mid-Continent Intensive (MCI) Campaign, three models were developed to estimate carbon fluxes on croplands: an inventory-based model, the Environmental Policy Integrated Climate (EPIC) model, and the General Ensemble biogeochemical Modeling System (GEMS) model. They all provided estimates of three major carbon fluxes on cropland: net primary production (NPP), net ecosystem production (NEP), and soil organic carbon (SOC) change. Using data mining and spatial statistics, we studied the spatial distribution of the carbon fluxes uncertainties and the relationships between the uncertainties and the land cover characteristics. Results indicated that uncertainties for all three carbon fluxes were not randomly distributed, but instead formed multiple clusters within the MCI region. We investigated the impacts of three land cover characteristics on the fluxes uncertainties: cropland percentage, cropland richness and cropland diversity. The results indicated that cropland percentage significantly influenced the uncertainties of NPP and NEP, but not on the uncertainties of SOC change. Greater uncertainties of NPP and NEP were found in counties with small cropland percentage than the counties with large cropland percentage. Cropland species richness and diversity also showed negative correlations with the model uncertainties. Our study demonstrated that the land cover characteristics contributed to the uncertainties of regional carbon fluxes estimates. The approaches we used in this study can be applied to other ecosystem models to identify the areas with high uncertainties and where models can be improved to reduce overall uncertainties for regional carbon flux estimates.</span></p>","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.ecolmodel.2016.07.002","usgsCitation":"Li, Z., Liu, S., Zhang, X., West, T.O., Ogle, S.M., and Zhou, N., 2016, Evaluating land cover influences on model uncertainties—A case study of cropland carbon dynamics in the Mid-Continent Intensive Campaign region: Ecological Modelling, v. 337, p. 176-187, https://doi.org/10.1016/j.ecolmodel.2016.07.002.","productDescription":"12 p.","startPage":"176","endPage":"187","ipdsId":"IP-076132","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470514,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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,{"id":70175959,"text":"sir20165123 - 2016 - Effects of water-supply reservoirs on streamflow in Massachusetts","interactions":[],"lastModifiedDate":"2021-02-09T18:07:43.492574","indexId":"sir20165123","displayToPublicDate":"2016-10-06T08:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5123","title":"Effects of water-supply reservoirs on streamflow in Massachusetts","docAbstract":"<p>State and local water-resource managers need modeling tools to help them manage and protect water-supply resources for both human consumption and ecological needs. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a decision-support tool to estimate the effects of reservoirs on natural streamflow. The Massachusetts Reservoir Simulation Tool is a model that simulates the daily water balance of a reservoir. The reservoir simulation tool provides estimates of daily outflows from reservoirs and compares the frequency, duration, and magnitude of the volume of outflows from reservoirs with estimates of the unaltered streamflow that would occur if no dam were present. This tool will help environmental managers understand the complex interactions and tradeoffs between water withdrawals, reservoir operational practices, and reservoir outflows needed for aquatic habitats.</p><p>A sensitivity analysis of the daily water balance equation was performed to identify physical and operational features of reservoirs that could have the greatest effect on reservoir outflows. For the purpose of this report, uncontrolled releases of water (spills or spillage) over the reservoir spillway were considered to be a proxy for reservoir outflows directly below the dam. The ratio of average withdrawals to the average inflows had the largest effect on spillage patterns, with the highest withdrawals leading to the lowest spillage. The size of the surface area relative to the drainage area of the reservoir also had an effect on spillage; reservoirs with large surface areas have high evaporation rates during the summer, which can contribute to frequent and long periods without spillage, even in the absence of water withdrawals. Other reservoir characteristics, such as variability of inflows, groundwater interactions, and seasonal demand patterns, had low to moderate effects on the frequency, duration, and magnitude of spillage. The reservoir simulation tool was used to simulate 35 single- and multiple-reservoir systems in Massachusetts over a 44-year period (water years 1961 to 2004) under two water-use scenarios. The no-pumping scenario assumes no water withdrawal pumping, and the pumping scenario incorporates average annual pumping rates from 2000 to 2004. By comparing the results of the two scenarios, the total streamflow alteration can be parsed into the portion of streamflow alteration caused by the presence of a reservoir and the additional streamflow alteration caused by the level of water use of the system.</p><p>For each reservoir system, the following metrics were computed to characterize the frequency, duration, and magnitude of reservoir outflow volumes compared with unaltered streamflow conditions: (1) the median number of days per year in which the reservoir did not spill, (2) the median duration of the longest consecutive period of no-spill days per year, and (3) the lowest annual flow duration exceedance probability at which the outflows are significantly different from estimated unaltered streamflow at the 95-percent confidence level. Most reservoirs in the study do not spill during the summer months even under no-pumping conditions. The median number of days during which there was no spillage was less than 365 for all reservoirs in the study, indicating that, even under reported pumping conditions, the reservoirs refill to full volume and spill at least once during nondrought years, typically in the spring.</p><p>Thirteen multiple-reservoir systems consisting of two or three hydrologically connected reservoirs were included in the study. Because operating rules used to manage multiple-reservoir systems are not available, these systems were simulated under two pumping scenarios, one in which water transfers between reservoirs are minimal and one in which reservoirs continually transferred water to intermediate or terminal reservoirs. These two scenarios provided upper and lower estimates of spillage under average pumping conditions from 2000 to 2004.</p><p>For sites with insufficient data to simulate daily water balances, a proxy method to estimate the three spillage metrics was developed. A series of 4,000 Monte Carlo simulations of the reservoir water balance were run. In each simulation, streamflow, physical reservoir characteristics, and daily climate inputs were randomly varied. Tobit regression equations that quantify the relation between streamflow alteration and physical and operational characteristics of reservoirs were developed from the results of the Monte Carlo simulations and can be used to estimate each of the three spillage metrics using only the withdrawal ratio and the ratio of the surface area to the drainage area, which are available statewide for all reservoirs.</p><p>A graphical user-interface for the Massachusetts Reservoir Simulation Tool was developed in a Microsoft Access environment. The simulation tool contains information for 70 reservoirs in Massachusetts and allows for simulation of additional scenarios than the ones considered in this report, including controlled releases, dam seepage and leakage, demand management plans, and alternative water withdrawal and transfer rules.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165123","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Levin, S.B., 2016, Effects of water-supply reservoirs on streamflow in Massachusetts: U.S. Geological Survey Scientific Investigations Report 2016–5123, 35 p., https://dx.doi.org/10.3133/sir20165123.","productDescription":"Report: vii, 35 p.; Software or Model Page","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-067115","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":329303,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20161136","text":"Open-File Report 2016–1136","description":"Open-File Report 2016-1136","linkHelpText":"- Massachusetts Reservoir Simulation Tool—User’s Manual"},{"id":383173,"rank":4,"type":{"id":4,"text":"Application Site"},"url":"https://www.sciencebase.gov/catalog/item/5eb4486082ce25b5135abfa0","text":"Software or Model Page","description":"Software or Model Page","linkHelpText":"– The Massachusetts Reservoir Simulation Tool"},{"id":329302,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5123/sir20165123.pdf","text":"Report","size":"3.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5123"},{"id":329301,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5123/coverthb.jpg"}],"country":"United 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 \"}}]}","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, New England Water Science Center<br> U.S. Geological Survey<br> 10 Bearfoot Road<br> Northborough, MA 01532</p><p>Or visit our Web site at:<br> <a href=\"http://newengland.water.usgs.gov\" data-mce-href=\"http://newengland.water.usgs.gov\">http://newengland.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Reservoir Simulation Tool</li><li>Spillage Metrics</li><li>Sensitivity of Spillage to Reservoir Characteristics</li><li>Application of the Reservoir Model for Selected Systems</li><li>Estimating Streamflow Alteration at Previously Unstudied Reservoirs</li><li>Limitations</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2016-10-06","noUsgsAuthors":false,"publicationDate":"2016-10-06","publicationStatus":"PW","scienceBaseUri":"57f7c089e4b0bc0bec09c7cf","contributors":{"authors":[{"text":"Levin, Sara B. 0000-0002-2448-3129 slevin@usgs.gov","orcid":"https://orcid.org/0000-0002-2448-3129","contributorId":1870,"corporation":false,"usgs":true,"family":"Levin","given":"Sara","email":"slevin@usgs.gov","middleInitial":"B.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":646705,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70176712,"text":"sir20165138 - 2016 - Delineation of areas contributing groundwater to selected receiving surface water bodies for long-term average hydrologic conditions from 1968 to 1983 for Long Island, New York","interactions":[],"lastModifiedDate":"2016-10-05T16:38:00","indexId":"sir20165138","displayToPublicDate":"2016-10-05T13:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5138","title":"Delineation of areas contributing groundwater to selected receiving surface water bodies for long-term average hydrologic conditions from 1968 to 1983 for Long Island, New York","docAbstract":"<p>To assist resource managers and planners in developing informed strategies to address nitrogen loading to coastal water bodies of Long Island, New York, the U.S. Geological Survey and the New York State Department of Environmental Conservation initiated a program to delineate a comprehensive dataset of groundwater recharge areas (or areas contributing groundwater), travel times, and outflows to streams and saline embayments on Long Island. A four-layer regional three-dimensional finite-difference groundwater-flow model of hydrologic conditions from 1968 to 1983 was used to provide delineations of 48 groundwater watersheds on Long Island. Sixteen particle starting points were evenly spaced within each of the 4,000- by 4,000-foot model cells that receive water-table recharge and tracked using forward particle-tracking analysis modeling software to outflow zones. For each particle, simulated travel times were grouped by age as follows: less than or equal to 10 years, greater than 10 years and less than or equal to 100 years, greater than 100 years and less than or equal to 1,000 years, and greater than 1,000 years; and simulated ending zones were grouped into 48 receiving water bodies, based on the New York State Department of Environmental Conservation Waterbody Inventory/Priority Waterbodies List. Areal delineation of travel time zones and groundwater contributing areas were generated and a table was prepared presenting the sum of groundwater outflow for each area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165138","collaboration":"Prepared in cooperation with the  New York State Department of Environmental Conservation","usgsCitation":"Misut, P.E., and Monti, Jack, Jr., 2016, Delineation of areas contributing groundwater to selected receiving surface water bodies for long-term average hydrologic conditions from 1968 to 1983 for Long Island, New York:U.S. Geological Survey Scientific Investigations Report 2016–5138, 22 p., https://dx.doi.org/10.3133/sir20165138.","productDescription":"Report: iv, 22 p.; Figures: 1-5; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[],"links":[{"id":329253,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5138/coverthb.jpg"},{"id":329257,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7TB151D ","text":"USGS data release","description":"USGS data release ","linkHelpText":"MODFLOW-2005 and MODPATH6 models "},{"id":329254,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5138/sir20165138.pdf","text":"Report","size":"5.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5138"},{"id":329255,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2016/5138/sir20165138_figs1-5.zip","text":"Figures 1-5 ","size":"10.2 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5138","linkHelpText":"- Large-format versions of figures in report"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.25,\n              40.5\n            ],\n            [\n              -73.25,\n              40.9\n            ],\n            [\n              -74.25,\n              40.9\n            ],\n            [\n              -74.25,\n              40.5\n            ],\n            [\n              -73.25,\n              40.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:: dc_ny@usgs.gov\" data-mce-href=\"mailto:: dc_ny@usgs.gov\">Director</a>, New York Water Science Center<br> U.S. Geological Survey<br> 425 Jordan Road<br> Troy, NY 12180<br> <a href=\"http://ny.water.usgs.gov\" data-mce-href=\"http://ny.water.usgs.gov\">http://ny.water.usgs.gov</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods of Analysis</li><li>Delineation of Areas Contributing Groundwater to Selected Receiving Surface Water Bodies</li><li>Limitations of Analysis</li><li>Summary and Conclusions</li><li>References Cited</li><li>Glossary</li></ul>","publishedDate":"2016-10-05","noUsgsAuthors":false,"publicationDate":"2016-10-05","publicationStatus":"PW","scienceBaseUri":"584e41fae4b0260a373816ec","contributors":{"authors":[{"text":"Misut, Paul E. 0000-0002-6502-5255 pemisut@usgs.gov","orcid":"https://orcid.org/0000-0002-6502-5255","contributorId":1073,"corporation":false,"usgs":true,"family":"Misut","given":"Paul","email":"pemisut@usgs.gov","middleInitial":"E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monti,, Jack Jr. jmonti@usgs.gov","contributorId":145900,"corporation":false,"usgs":true,"family":"Monti,","given":"Jack","suffix":"Jr.","email":"jmonti@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":650107,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70176703,"text":"70176703 - 2016 - Using an interlaboratory study to revise methods for conducting 10-d to 42-d water or sediment toxicity tests with <i>Hyalella azteca</i>","interactions":[],"lastModifiedDate":"2018-08-07T11:55:17","indexId":"70176703","displayToPublicDate":"2016-10-04T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Using an interlaboratory study to revise methods for conducting 10-d to 42-d water or sediment toxicity tests with <i>Hyalella azteca</i>","docAbstract":"<p><span>Studies have been conducted to refine US Environmental Protection Agency, ASTM International, and Environment Canada standard methods for conducting 42-d reproduction tests with </span><i>Hyalella azteca</i><span> in water or in sediment. Modifications to the </span><i>H. azteca</i><span> method include better-defined ionic composition requirements for exposure water (i.e., &gt;15 mg/L of chloride and &gt;0.02 mg/L of bromide) and improved survival, growth, and reproduction with alternate diets provided as increased rations over time in water-only or whole-sediment toxicity tests. A total of 24 laboratories volunteered to participate in the present interlaboratory study evaluating the performance of </span><i>H. azteca</i><span> in 42-d studies in control sand or control sediment using the refined methods. Improved growth and reproduction of </span><i>H. azteca</i><span> was observed with 2 alternate diets of 1) ramped diatoms (</span><i>Thalassiosira weissflogii</i><span>) + ramped Tetramin or 2) yeast–cerophyll–trout chow (YCT) + ramped Tetramin, especially when compared with results from the traditional diet of 1.8 mg YCT/d. Laboratories were able to meet proposed test acceptability criteria and in most cases had lower variation in growth or reproduction compared with previous interlaboratory studies using the traditional YCT diet. Laboratory success in conducting 42-d </span><i>H. azteca</i><span> exposures benefited from adherence to several key requirements of the detailed testing, culturing, and handling methods. Results from the present interlaboratory study are being used to help revise standard methods for conducting 10-d to 42-d water or sediment toxicity exposures with </span><i>H. azteca</i><span>.</span></p>","language":"English","publisher":"SETAC Press","doi":"10.1002/etc.3417","usgsCitation":"Ivey, C.D., Ingersoll, C.G., Brumbaugh, W.G., Hammer, E.J., Mount, D.R., Hockett, J.R., Norberg-King, T.J., Soucek, D., and Taylor, L., 2016, Using an interlaboratory study to revise methods for conducting 10-d to 42-d water or sediment toxicity tests with <i>Hyalella azteca</i>: Environmental Toxicology and Chemistry, v. 35, no. 10, p. 2439-2447, https://doi.org/10.1002/etc.3417.","productDescription":"9 p.","startPage":"2439","endPage":"2447","ipdsId":"IP-071150","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":329256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-02","publicationStatus":"PW","scienceBaseUri":"57f7c639e4b0bc0bec09c816","contributors":{"authors":[{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":649937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":649938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":649939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hammer, Edward J.","contributorId":150723,"corporation":false,"usgs":false,"family":"Hammer","given":"Edward","email":"","middleInitial":"J.","affiliations":[{"id":18077,"text":"U. S. Environmental Protection Agency, Region 5, Water Quality Branch, Chicago, Illinois","active":true,"usgs":false}],"preferred":false,"id":649940,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mount, David R.","contributorId":150725,"corporation":false,"usgs":false,"family":"Mount","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":18078,"text":"U. S. Environmental Protection Agency, Environmental Effects Research Laboratory, Duluth, Minnesota","active":true,"usgs":false}],"preferred":false,"id":649941,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hockett, J. Russell","contributorId":175086,"corporation":false,"usgs":false,"family":"Hockett","given":"J.","email":"","middleInitial":"Russell","affiliations":[{"id":13485,"text":"U.S. Environmental Protection Agency, Duluth, MN","active":true,"usgs":false}],"preferred":false,"id":649942,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Norberg-King, Teresa J.","contributorId":175087,"corporation":false,"usgs":false,"family":"Norberg-King","given":"Teresa","email":"","middleInitial":"J.","affiliations":[{"id":13485,"text":"U.S. Environmental Protection Agency, Duluth, MN","active":true,"usgs":false}],"preferred":false,"id":649943,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Soucek, Dave","contributorId":175088,"corporation":false,"usgs":false,"family":"Soucek","given":"Dave","affiliations":[{"id":27529,"text":"Illinois Natural History Survey, Champaign, Il","active":true,"usgs":false}],"preferred":false,"id":649944,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Taylor, Lisa","contributorId":175089,"corporation":false,"usgs":false,"family":"Taylor","given":"Lisa","email":"","affiliations":[{"id":27530,"text":"Environment Canada, Ottawa, ONT Canada","active":true,"usgs":false}],"preferred":false,"id":649945,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70176465,"text":"ds1020 - 2016 - Characterization of fractures and flow zones in a contaminated crystalline-rock aquifer in the Tylerville section of Haddam, Connecticut","interactions":[],"lastModifiedDate":"2016-10-04T10:56:37","indexId":"ds1020","displayToPublicDate":"2016-10-04T07:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1020","title":"Characterization of fractures and flow zones in a contaminated crystalline-rock aquifer in the Tylerville section of Haddam, Connecticut","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Connecticut Department of Energy and Environmental Protection, investigated the characteristics of the bedrock aquifer in the Tylerville section of Haddam, Connecticut, from June to August 2014. As part of this investigation, geophysical logs were collected from six water-supply wells and were analyzed to (1) identify well construction, (2) determine the rock type and orientation of the foliation and layering of the rock, (3) characterize the depth and orientation of fractures, (4) evaluate fluid properties of the water in the well, and (5) determine the relative transmissivity and head of discrete fractures or fracture zones. The logs included the following: caliper, electromagnetic induction, gamma, acoustic and (or) optical televiewer, heat-pulse flowmeter under ambient and pumped conditions, hydraulic head data, fluid electrical conductivity and temperature under postpumping conditions, and borehole-radar reflection collected in single-hole mode. In a seventh borehole, a former water-supply well, only caliper, fluid electrical conductivty, and temperature logs were collected, because of a constriction in the borehole.</p><p>This report includes a description of the methods used to collect and process the borehole geophysical data, the description of the data collected in each of the wells, and a comparison of the results collected in all of the wells. The data are presented in plots of the borehole geophysical logs, tables, and figures. Collectively these data provide valuable characterizations that can be used to improve or inform site conceptual models of groundwater flow in the study area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1020","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Johnson, C.D., Kiel, K.F., Joesten, P.K., and Pappas, K.L., 2016, Characterization of fractures and flow zones in a contaminated crystalline-rock aquifer in the Tylerville section of Haddam, Connecticut: U.S. Geological Survey Data Series 1020, 40 p., https://dx.doi.org/10.3133/ds1020.","productDescription":"Report: viii, 40 p.; Appendixes: 1-7","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-067211","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":329127,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1020/appendix/ds1020_appendix2.zip","text":"Appendix 2","size":"7.27 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1020","linkHelpText":"- Borehole-Geophysical Logs From Borehole 76–BR in the Tylerville Study Area, Haddam, Connecticut, 2014"},{"id":329131,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1020/appendix/ds1020_appendix6.zip","text":"Appendix 6","size":"19.9 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1020","linkHelpText":"- Borehole-Geophysical Logs From Borehole 130–LMR in the Tylerville Study Area, Haddam, Connecticut, 2014"},{"id":329132,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1020/appendix/ds1020_appendix7.zip","text":"Appendix 7","size":"658 KB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1020","linkHelpText":"- Borehole-Geophysical Logs From Borehole 95–BR in the Tylerville Study Area, Haddam, Connecticut, 2014"},{"id":329133,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1020/appendix/ds1020_appendixes_1-7.zip","text":"Appendixes 1–7","size":"76.9 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1020","linkHelpText":"- Borehole-Geophysical Logs From Seven Boreholes in the Tylerville Study Area, Haddam, Connecticut, 2014"},{"id":329128,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1020/appendix/ds1020_appendix3.zip","text":"Appendix 3","size":"5.84 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1020","linkHelpText":"- Borehole-Geophysical Logs From Borehole 85–BR in the Tylerville Study Area, Haddam, Connecticut, 2014"},{"id":329130,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1020/appendix/ds1020_appendix5.zip","text":"Appendix 5","size":"18 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1020","linkHelpText":"- Borehole-Geophysical Logs From Borehole 77–LMR in the Tylerville Study Area, Haddam, Connecticut, 2014"},{"id":329129,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1020/appendix/ds1020_appendix4.zip","text":"Appendix 4","size":"10.7 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1020","linkHelpText":"- Borehole-Geophysical Logs From Borehole 79/81–BR in the Tylerville Study Area, Haddam, Connecticut, 2014"},{"id":329124,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1020/coverthb.jpg"},{"id":329125,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1020/ds1020.pdf","text":"Report","size":"8.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1020"},{"id":329126,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1020/appendix/ds1020_appendix1.zip","text":"Appendix 1","size":"14.4 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1020","linkHelpText":"- Borehole-Geophysical Logs From Borehole 1640–SR in the Tylerville Study Area, Haddam, Connecticut, 2014"}],"country":"United States","state":"Connecticut","county":"Middlesex County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -72.48126983642578,\n              41.43944494429659\n            ],\n            [\n              -72.48126983642578,\n              41.45745861169602\n            ],\n            [\n              -72.46135711669922,\n              41.45745861169602\n            ],\n            [\n              -72.46135711669922,\n              41.43944494429659\n            ],\n            [\n              -72.48126983642578,\n              41.43944494429659\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:jwlane@usgs.gov\" data-mce-href=\"mailto:jwlane@usgs.gov\">Chief</a>, Branch of Geophysics<br> Office of Groundwater<br> U.S. Geological Survey<br> 11 Sherman Place, Unit 5015<br> Storrs, CT 06269<br> <a href=\"http://water.usgs.gov/ogw/bgas\" data-mce-href=\"http://water.usgs.gov/ogw/bgas\">http://water.usgs.gov/ogw/bgas</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods of Investigation</li><li>Data and Results by Well&nbsp;</li><li>Combined Results From All Wells</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendixes 1–7. Borehole-Geophysical Logs From Boreholes in the Tylerville Study Area, Haddam, Connecticut, 2014</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-10-04","noUsgsAuthors":false,"publicationDate":"2016-10-04","publicationStatus":"PW","scienceBaseUri":"57f7c639e4b0bc0bec09c818","contributors":{"authors":[{"text":"Johnson, Carole D. 0000-0001-6941-1578 cjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":1891,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole","email":"cjohnson@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":649902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiel, Kristal F.","contributorId":174636,"corporation":false,"usgs":false,"family":"Kiel","given":"Kristal","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":649903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Joesten, Peter K. pjoesten@usgs.gov","contributorId":1929,"corporation":false,"usgs":true,"family":"Joesten","given":"Peter","email":"pjoesten@usgs.gov","middleInitial":"K.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":649904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pappas, Katherine L.","contributorId":175026,"corporation":false,"usgs":true,"family":"Pappas","given":"Katherine L.","affiliations":[],"preferred":false,"id":649908,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70176702,"text":"70176702 - 2016 - Economic value of angling on the Colorado River at Lees Ferry: Using secondary data to estimate the influence of seasonality","interactions":[],"lastModifiedDate":"2016-10-04T12:10:11","indexId":"70176702","displayToPublicDate":"2016-10-04T00:00:00","publicationYear":"2016","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":"Economic value of angling on the Colorado River at Lees Ferry: Using secondary data to estimate the influence of seasonality","docAbstract":"<p><span>Glen Canyon Dam (GCD) on the Colorado River in northern Arizona provides water storage, flood control, and power system benefits to approximately 40 million people who rely on water and energy resources in the Colorado River basin. Downstream resources (e.g., angling, whitewater floating) in Glen Canyon National Recreation Area (GCNRA) and Grand Canyon National Park are impacted by the operation of GCD. The GCD Adaptive Management Program was established in 1997 to monitor and research the effects of dam operations on the downstream environment. We utilized secondary survey data and an individual observation travel cost model to estimate the net economic benefit of angling in GCNRA for each season and each type of angler. As expected, the demand for angling decreased with increasing travel cost; the annual value of angling at Lees Ferry totaled US$2.7 million at 2014 visitation levels. Demand for angling was also affected by season, with per-trip values of $210 in the summer, $237 in the spring, $261 in the fall, and $399 in the winter. This information provides insight into the ways in which anglers are potentially impacted by seasonal GCD operations and adaptive management experiments aimed at improving downstream resource conditions.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2016.1204388","usgsCitation":"Bair, L.S., Rogowski, D.L., and Neher, C., 2016, Economic value of angling on the Colorado River at Lees Ferry: Using secondary data to estimate the influence of seasonality: North American Journal of Fisheries Management, v. 36, no. 6, p. 1229-1239, https://doi.org/10.1080/02755947.2016.1204388.","productDescription":"11 p.","startPage":"1229","endPage":"1239","ipdsId":"IP-066706","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":329258,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Lees Ferry","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.63894653320311,\n              36.824676208856175\n            ],\n            [\n              -111.63894653320311,\n              36.943855400282494\n            ],\n            [\n              -111.47758483886719,\n              36.943855400282494\n            ],\n            [\n              -111.47758483886719,\n              36.824676208856175\n            ],\n            [\n              -111.63894653320311,\n              36.824676208856175\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57f7c63ae4b0bc0bec09c81c","contributors":{"authors":[{"text":"Bair, Lucas S. 0000-0002-9911-3624 lbair@usgs.gov","orcid":"https://orcid.org/0000-0002-9911-3624","contributorId":5270,"corporation":false,"usgs":true,"family":"Bair","given":"Lucas","email":"lbair@usgs.gov","middleInitial":"S.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":649934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogowski, David L.","contributorId":175084,"corporation":false,"usgs":false,"family":"Rogowski","given":"David","email":"","middleInitial":"L.","affiliations":[{"id":27527,"text":"AZ Game and FIsh Department","active":true,"usgs":false}],"preferred":false,"id":649935,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Neher, Christopher","contributorId":175085,"corporation":false,"usgs":false,"family":"Neher","given":"Christopher","email":"","affiliations":[{"id":27528,"text":"Uni. of Montana, Dept. of Mathematical Sciences","active":true,"usgs":false}],"preferred":false,"id":649936,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70175322,"text":"sir20165112 - 2016 - Status of groundwater quality in the Santa Barbara Study Unit, 2011: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2016-10-03T16:15:22","indexId":"sir20165112","displayToPublicDate":"2016-10-03T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5112","title":"Status of groundwater quality in the Santa Barbara Study Unit, 2011: California GAMA Priority Basin Project","docAbstract":"<p class=\"p1\">Groundwater quality in the 48-square-mile Santa Barbara study unit was investigated in 2011 as part of the California State Water Resources Control Board’s Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project. The study unit is mostly in Santa Barbara County and is in the Transverse and Selected Peninsular Ranges hydrogeologic province. The GAMA Priority Basin Project is carried out by the U.S. Geological Survey in collaboration with the California State Water Resources Control Board and Lawrence Livermore National Laboratory.</p><p class=\"p1\">The GAMA Priority Basin Project was designed to provide a statistically unbiased, spatially distributed assessment of the quality of untreated groundwater in the primary aquifer system of California. The primary aquifer system is defined as that part of the aquifer corresponding to the perforation interval of wells listed in the California Department of Public Health database for the Santa Barbara study unit. This status assessment is intended to characterize the quality of groundwater resources in the primary aquifer system of the Santa Barbara study unit, not the treated drinking water delivered to consumers by water purveyors.</p><p class=\"p1\">The <i>status assessment </i>for the Santa Barbara study unit was based on water-quality and ancillary data collected in 2011 by the U.S. Geological Survey from 23 sites and on water-quality data from the California Department of Public Health database for January 24, 2008–January 23, 2011. The data used for the assessment included volatile organic compounds; pesticides; pharmaceutical compounds; two constituents of special interest, perchlorate and <i>N</i>-nitrosodimethylamine (NDMA); and naturally present inorganic constituents, such as major ions and trace elements. Relative-concentrations (sample concentration divided by the health- or aesthetic-based benchmark concentration) were used to evaluate groundwater quality for those constituents that have federal or California regulatory and non-regulatory benchmarks for drinking-water quality. For inorganic, organic, and special-interest constituents, a relative-concentration greater than 1.0 indicates a concentration greater than the benchmark and is classified as high. Inorganic constituents are classified as moderate if relative-concentrations are greater than 0.5 and less than or equal to 1.0 and are classified as low if relative-concentrations are less than or equal to 0.5. For organic and special-interest constituents, the boundary between moderate and low relative-concentrations was set at 0.1.</p><p class=\"p2\">Aquifer-scale proportion was used as the primary metric for evaluating regional-scale groundwater quality. High aquifer-scale proportion is defined as the areal percentage of the primary aquifer system with a relative-concentration greater than 1.0 for a particular constituent or class of constituents. Moderate and low aquifer-scale proportions were defined as the areal percentage of the primary aquifer system that had moderate and low relative-concentrations, respectively. Two statistical approaches—grid based and spatially weighted—were used to calculate aquifer-scale proportions for individual constituents and constituent classes. Grid-based and spatially weighted estimates were comparable in this the study (within 90-percent confidence intervals). Grid-based results were selected for use in the status assessment unless, as was observed in a few cases, a grid-based result was zero and the spatially weighted result was not zero, in which case, the spatially weighted result was used.</p><p class=\"p2\">Inorganic constituents that have human-health benchmarks were present at high relative-concentrations in 5.3 percent of the primary aquifer system and at moderate concentrations in 32 percent. High aquifer-scale proportions of inorganic constituents primarily were a result of high aquifer-scale proportions of boron (5.3 percent) and fluoride (5.3 percent). Inorganic constituents that have aesthetic-based benchmarks, referred to as secondary maximum contaminant levels, were present at high relative-concentrations in 58 percent of the primary aquifer system and at moderate concentrations in 37 percent. Iron, manganese, sulfate, and total dissolved solids were the inorganic constituents with secondary maximum contaminant levels present at high relative-concentrations.</p><p class=\"p1\">In contrast, organic and special-interest constituents that have health-based benchmarks were not detected at high relative-concentrations in the primary aquifer system. Of the 218 organic constituents analyzed, 10 were detected—9 that had human-health benchmarks. Organic constituents were present at moderate relative-concentrations in 11 percent of the primary aquifer system. The moderate aquifer-scale proportions were a result of moderate relative-concentrations of the volatile organic compounds methyl <i>tert-</i>butyl ether (MTBE, 11 percent) and 1,2-dichloroethane (5.6 percent). The volatile organic compounds 1,1,1-trichloroethane, 1,1-dichloroethane, bromodichloromethane, chloroform, MTBE, and perchloroethene (PCE); the pesticide simazine; and the special-interest constituent perchlorate were detected at more than 10 percent of the sites in the Santa Barbara study unit. Perchlorate was present at moderate relative-concentrations in 50 percent of the primary aquifer system. Pharmaceutical compounds and NDMA were not detected in the Santa Barbara study unit.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165112","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Davis, T.A., and Kulongoski, J.T., 2016, Status of groundwater quality in the Santa Barbara Study Unit, 2011: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2016–5112, 70 p., https://dx.doi.org/10.3133/sir20165112.","productDescription":"viii, 70 p.","numberOfPages":"82","ipdsId":"IP-077335","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":329221,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5112/sir20165112.pdf","text":"Report","size":"14.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5112"},{"id":329220,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5112/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Barbara Study Unit","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.92813110351561,\n              34.37461214493789\n            ],\n            [\n              -119.92813110351561,\n              34.47203335543746\n            ],\n            [\n              -119.43237304687499,\n              34.47203335543746\n            ],\n            [\n              -119.43237304687499,\n              34.37461214493789\n            ],\n            [\n              -119.92813110351561,\n              34.37461214493789\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publicComments":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>, California Water Science Center<br> U.S. Geological Survey<br> 6000 J Street, Placer Hall<br> Sacramento, California 95819<br> <a href=\"http://ca.water.usgs.gov\" target=\"blank\" data-mce-href=\"http://ca.water.usgs.gov\">http://ca.water.usgs.gov</a></p>","tableOfContents":"<ul><li>Acknowledgments<br></li><li>Abstract<br></li><li>Introduction<br></li><li>Methods<br></li><li>Potential Explanatory Factors<br></li><li>Status of Groundwater Quality<br></li><li>Summary<br></li><li>References Cited<br></li><li>Tables<br></li><li>Appendixes 1–3<br></li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2016-10-03","noUsgsAuthors":false,"publicationDate":"2016-10-03","publicationStatus":"PW","scienceBaseUri":"57f7c63ae4b0bc0bec09c82e","contributors":{"authors":[{"text":"Davis, Tracy A. 0000-0003-0253-6661 tadavis@usgs.gov","orcid":"https://orcid.org/0000-0003-0253-6661","contributorId":2715,"corporation":false,"usgs":true,"family":"Davis","given":"Tracy","email":"tadavis@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":644759,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":156272,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":644760,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70177058,"text":"70177058 - 2016 - Why do trees die? Characterizing the drivers of background tree mortality","interactions":[],"lastModifiedDate":"2017-03-09T15:06:17","indexId":"70177058","displayToPublicDate":"2016-10-03T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Why do trees die? Characterizing the drivers of background tree mortality","docAbstract":"The drivers of background tree mortality rates—the typical low rates of tree mortality found in forests in the absence of acute stresses like drought—are central to our understanding of forest dynamics, the effects of ongoing environmental changes on forests, and the causes and consequences of geographical gradients in the nature and strength of biotic interactions. To shed light on factors contributing to background tree mortality, we analyzed detailed pathological data from 200,668 tree-years of observation and 3,729 individual tree deaths, recorded over a 13-yr period in a network of old-growth forest plots in California's Sierra Nevada mountain range. We found that: (1) Biotic mortality factors (mostly insects and pathogens) dominated (58%), particularly in larger trees (86%). Bark beetles were the most prevalent (40%), even though there were no outbreaks during the study period; in contrast, the contribution of defoliators was negligible. (2) Relative occurrences of broad classes of mortality factors (biotic, 58%; suppression, 51%; and mechanical, 25%) are similar among tree taxa, but may vary with tree size and growth rate. (3) We found little evidence of distinct groups of mortality factors that predictably occur together on trees. Our results have at least three sets of implications. First, rather than being driven by abiotic factors such as lightning or windstorms, the “ambient” or “random” background mortality that many forest models presume to be independent of tree growth rate is instead dominated by biotic agents of tree mortality, with potentially critical implications for forecasting future mortality. Mechanistic models of background mortality, even for healthy, rapidly growing trees, must therefore include the insects and pathogens that kill trees. Second, the biotic agents of tree mortality, instead of occurring in a few predictable combinations, may generally act opportunistically and with a relatively large degree of independence from one another. Finally, beyond the current emphasis on folivory and leaf defenses, studies of broad-scale gradients in the nature and strength of biotic interactions should also include biotic attacks on, and defenses of, tree stems and roots.","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1002/ecy.1497","usgsCitation":"Das, A., Stephenson, N.L., and Davis, K., 2016, Why do trees die? Characterizing the drivers of background tree mortality: Ecology, v. 97, no. 10, p. 2616-2627, https://doi.org/10.1002/ecy.1497.","productDescription":"22 p.","startPage":"2616","endPage":"2627","numberOfPages":"22","ipdsId":"IP-067123","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":438540,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71Z42G6","text":"USGS data release","linkHelpText":"Mortality factors for dead trees from a subset of plots from the Sierra Nevada Forest Dynamics Plot Network from 1998 to 2010"},{"id":337252,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F71Z42G6","text":"Mortality factors for dead trees from a subset of plots from the Sierra Nevada Forest Dynamics Plot Network from 1998 to 2010"},{"id":329647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5805e34de4b0824b2d1c24b8","chorus":{"doi":"10.1002/ecy.1497","url":"http://dx.doi.org/10.1002/ecy.1497","publisher":"Wiley-Blackwell","authors":"Das Adrian J., Stephenson Nathan L., Davis Kristin P.","journalName":"Ecology","publicationDate":"9/1/2016","auditedOn":"12/19/2016"},"contributors":{"authors":[{"text":"Das, Adrian J. 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":3842,"corporation":false,"usgs":true,"family":"Das","given":"Adrian J.","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":651160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stephenson, Nathan L. 0000-0003-0208-7229 nstephenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0208-7229","contributorId":2836,"corporation":false,"usgs":true,"family":"Stephenson","given":"Nathan","email":"nstephenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":651159,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Kristin P.","contributorId":175448,"corporation":false,"usgs":false,"family":"Davis","given":"Kristin P.","affiliations":[{"id":27570,"text":"Natural Resource Ecology Lab, Colorado State U, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":651161,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70176468,"text":"sir20165131 - 2016 - Paleomagnetic correlation of basalt flows in selected coreholes near the Advanced Test Reactor Complex, the Idaho Nuclear Technology and Engineering Center, and along the southern boundary, Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2016-10-04T10:41:58","indexId":"sir20165131","displayToPublicDate":"2016-10-03T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5131","title":"Paleomagnetic correlation of basalt flows in selected coreholes near the Advanced Test Reactor Complex, the Idaho Nuclear Technology and Engineering Center, and along the southern boundary, Idaho National Laboratory, Idaho","docAbstract":"<p class=\"p1\">The U.S. Geological Survey, in cooperation with the U.S. Department of Energy, used paleomagnetic data from 18 coreholes to construct three cross sections of subsurface basalt flows in the southern part of the Idaho National Laboratory (INL). These cross sections, containing descriptions of the subsurface horizontal and vertical distribution of basalt flows and sediment layers, will be used in geological studies, and to construct numerical models of groundwater flow and contaminant transport.</p><p class=\"p1\">Subsurface cross sections were used to correlate surface vents to their subsurface flows intersected by coreholes, to correlate subsurface flows between coreholes, and to identify possible subsurface vent locations of subsurface flows. Correlations were identified by average paleomagnetic inclinations of flows, and depth from land surface in coreholes, normalized to the North American Datum of 1927. Paleomagnetic data were combined, in some cases, with other data, such as radiometric ages of flows. Possible vent locations of buried basalt flows were identified by determining the location of the maximum thickness of flows penetrated by more than one corehole.</p><p class=\"p1\">Flows from the surface volcanic vents Quaking Aspen Butte, Vent 5206, Mid Butte, Lavatoo Butte, Crater Butte, Pond Butte, Vent 5350, Vent 5252, Tin Cup Butte, Vent 4959, Vent 5119, and AEC Butte are found in coreholes, and were correlated to the surface vents by matching their paleomagnetic inclinations, and in some cases, their stratigraphic positions.</p><p class=\"p1\">Some subsurface basalt flows that do not correlate to surface vents, do correlate over several coreholes, and may correlate to buried vents. Subsurface flows which correlate across several coreholes, but not to a surface vent include the D3 flow, the Big Lost flow, the CFA buried vent flow, the Early, Middle, and Late Basal Brunhes flows, the South Late Matuyama flow, the Matuyama flow, and the Jaramillo flow. The location of vents buried in the subsurface by younger basalt flows can be inferred if their flows are penetrated by several coreholes, by tracing the flows in the subsurface, and determining where the greatest thickness occurs.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165131","collaboration":"DOE/ID-22240<br/>Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Hodges, M.K.V., and Champion, D.E., 2016, Paleomagnetic correlation of basalt flows in selected coreholes near the Advanced Test Reactor Complex, the Idaho Nuclear Technology and Engineering Center, and along the southern boundary, Idaho National Laboratory, Idaho: U.S. Geological Survey Scientific Investigations Report 2016-5131\n(DOE/ID-22240), 65 p., 1 pl., https://dx.doi.org/10.3133/sir20165131.","productDescription":"Report: v, 65 p.; Plate: 34.00 x 40.00 inches","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065469","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":329237,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5131/sir20165131.pdf","text":"Report","size":"965 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5131"},{"id":329238,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5131/sir20165131_plate01.pdf","text":"Plate 1","size":"543 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5131 Plate 1","linkHelpText":"Map and subsurface stratigraphic cross sections interpreted from paleomagnetic inclination data from coreholes in the southern part of the Idaho National Laboratory, Idaho."},{"id":329236,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5131/coverthb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.45581054687499,\n              43.22519255488632\n            ],\n            [\n              -113.45581054687499,\n              44.11914151643737\n            ],\n            [\n              -112.3516845703125,\n              44.11914151643737\n            ],\n            [\n              -112.3516845703125,\n              43.22519255488632\n            ],\n            [\n              -113.45581054687499,\n              43.22519255488632\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_id@usgs.gov\" data-mce-href=\"mailto:dc_id@usgs.gov\">Director</a>, Idaho Water Science Center<br> U.S. Geological Survey<br> 230 Collins Road<br> Boise, Idaho 83702<br> <a href=\"http://id.water.usgs.gov\" target=\"blank\" data-mce-href=\"http://id.water.usgs.gov\">http://id.water.usgs.gov</a></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Geologic Setting<br></li><li>Sampling and Analytical Techniques<br></li><li>Correlation Techniques<br></li><li>Paleomagnetic Correlations of Basalt Flows<br></li><li>Summary and Conclusions<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendix A. Previously Unpublished Paleomagnetic Data<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-10-03","noUsgsAuthors":false,"publicationDate":"2016-10-03","publicationStatus":"PW","scienceBaseUri":"57f7c63ae4b0bc0bec09c82c","contributors":{"authors":[{"text":"Hodges, Mary K.V.","contributorId":66848,"corporation":false,"usgs":true,"family":"Hodges","given":"Mary K.V.","affiliations":[],"preferred":false,"id":648850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Champion, Duane E. 0000-0001-7854-9034 dchamp@usgs.gov","orcid":"https://orcid.org/0000-0001-7854-9034","contributorId":2912,"corporation":false,"usgs":true,"family":"Champion","given":"Duane","email":"dchamp@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":648851,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70178579,"text":"70178579 - 2016 - Remote estimation of surface pCO2 on the West Florida Shelf","interactions":[],"lastModifiedDate":"2018-08-07T14:13:27","indexId":"70178579","displayToPublicDate":"2016-10-01T14:13:20","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Remote estimation of surface <i>p</i>CO<sub>2</sub> on the West Florida Shelf","title":"Remote estimation of surface pCO2 on the West Florida Shelf","docAbstract":"<p><span>Surface&nbsp;</span><i>p</i><span>CO</span><sub>2</sub><span>&nbsp;data from the West Florida Shelf (WFS) have been collected during 25 cruise surveys between 2003 and 2012. The data were scaled up using remote sensing measurements of surface water properties in order to provide a more nearly synoptic map of&nbsp;</span><i>p</i><span>CO</span><sub>2</sub><span>&nbsp;spatial distributions and describe their temporal variations. This investigation involved extensive tests of various model forms through parsimony and Principal Component Analysis, which led to the development of a multi-variable empirical surface&nbsp;</span><i>p</i><span>CO</span><sub>2</sub><span>&nbsp;model based on concurrent MODIS (Moderate Resolution Imaging Spectroradiometer) estimates of surface chlorophyll&nbsp;</span><i>a</i><span>&nbsp;concentrations (CHL, mg m</span><sup>−3</sup><span>), diffuse light attenuation at 490</span><span>&nbsp;</span><span>nm (Kd_Lee, m</span><sup>−1</sup><span>), and sea surface temperature (SST, °C). Validation using an independent dataset showed a&nbsp;</span><i>p</i><span>CO</span><sub>2</sub><span>&nbsp;Root Mean Square Error (RMSE) of &lt;12</span><span>&nbsp;</span><span>µatm and a 0.88 coefficient of determination (R</span><sup>2</sup><span>) for measured and model-predicted&nbsp;</span><i>p</i><span>CO</span><sub>2</sub><span>&nbsp;ranging from 300 to 550</span><span>&nbsp;</span><span>µatm. The model was more sensitive to SST than to CHL and Kd_Lee, with a 1</span><span>&nbsp;</span><span>°C change in SST leading to a ~16</span><span>&nbsp;</span><span>µatm change in the predicted&nbsp;</span><i>p</i><span>CO</span><sub>2</sub><span>. Application of the model to the entire WFS MODIS time series between 2002 and 2014 showed clear seasonality, with maxima (~450</span><span>&nbsp;</span><span>µatm) in summer and minima (~350</span><span>&nbsp;</span><span>µatm) in winter. The seasonality was positively correlated to SST (high in summer and low in winter) and negatively correlated to CHL and Kd_Lee (high in winter and low in summer). Inter-annual variations of&nbsp;</span><i>p</i><span>CO</span><sub>2</sub><span>&nbsp;were consistent with inter-annual variations of SST, CHL, and Kd_Lee. These results suggest that surface water&nbsp;</span><i>p</i><span>CO</span><sub>2</sub><span>&nbsp;of the WFS can be estimated, with known uncertainties, from remote sensing. However, while the general approach of empirical regression may work for waters from other areas of the Gulf of Mexico, model coefficients need to be empirically determined in a similar fashion.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2016.09.004","usgsCitation":"Chen, S., Hu, C., Byrne, R., Robbins, L.L., and Yang, B., 2016, Remote estimation of surface pCO2 on the West Florida Shelf: Continental Shelf Research, v. 128, p. 10-25, https://doi.org/10.1016/j.csr.2016.09.004.","productDescription":"16 p.","startPage":"10","endPage":"25","ipdsId":"IP-071209","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":462067,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2016.09.004","text":"Publisher Index Page"},{"id":356293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"West Florida Shelf","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -85,\n              24\n            ],\n            [\n              -80,\n              24\n            ],\n            [\n              -80,\n              30\n            ],\n            [\n              -85,\n              30\n            ],\n            [\n              -85,\n              24\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"128","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc864e4b0f5d57878ec28","contributors":{"authors":[{"text":"Chen, Shuangling","contributorId":177054,"corporation":false,"usgs":false,"family":"Chen","given":"Shuangling","email":"","affiliations":[],"preferred":false,"id":654429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hu, Chuanmin","contributorId":177055,"corporation":false,"usgs":false,"family":"Hu","given":"Chuanmin","email":"","affiliations":[],"preferred":false,"id":654430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Byrne, Robert H.","contributorId":83260,"corporation":false,"usgs":true,"family":"Byrne","given":"Robert H.","affiliations":[],"preferred":false,"id":654431,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robbins, Lisa L. 0000-0003-3681-1094 lrobbins@usgs.gov","orcid":"https://orcid.org/0000-0003-3681-1094","contributorId":422,"corporation":false,"usgs":true,"family":"Robbins","given":"Lisa","email":"lrobbins@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":654428,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yang, Bo","contributorId":149369,"corporation":false,"usgs":false,"family":"Yang","given":"Bo","email":"","affiliations":[{"id":13653,"text":"University South Florida","active":true,"usgs":false}],"preferred":false,"id":741896,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70188067,"text":"70188067 - 2016 - Forecasting climate change impacts on plant populations over large spatial extents","interactions":[],"lastModifiedDate":"2018-03-08T12:59:33","indexId":"70188067","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting climate change impacts on plant populations over large spatial extents","docAbstract":"<p><span>Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (</span><i>Artemisia</i><span> spp.) percent cover over a 2.5&nbsp;×&nbsp;5&nbsp;km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1525","usgsCitation":"Tredennick, A.T., Hooten, M., Aldridge, C.L., Homer, C.G., Kleinhesselink, A.R., and Adler, P.B., 2016, Forecasting climate change impacts on plant populations over large spatial extents: Ecosphere, v. 7, no. 10, e01525; 16 p., https://doi.org/10.1002/ecs2.1525.","productDescription":"e01525; 16 p.","ipdsId":"IP-071731","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470538,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1525","text":"Publisher Index Page"},{"id":341852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","volume":"7","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-24","publicationStatus":"PW","scienceBaseUri":"592e84b9e4b092b266f10d30","contributors":{"authors":[{"text":"Tredennick, Andrew T.","contributorId":152688,"corporation":false,"usgs":false,"family":"Tredennick","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":18962,"text":"Dept. of Wildland Resources and the Ecology Center, Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":696411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":696382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":696412,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696413,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kleinhesselink, Andrew R.","contributorId":192387,"corporation":false,"usgs":false,"family":"Kleinhesselink","given":"Andrew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":696414,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adler, Peter B.","contributorId":64789,"corporation":false,"usgs":false,"family":"Adler","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":696415,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70188153,"text":"70188153 - 2016 - Lateral and subsurface flows impact arctic coastal plain lake water budgets","interactions":[],"lastModifiedDate":"2018-10-25T16:43:24","indexId":"70188153","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Lateral and subsurface flows impact arctic coastal plain lake water budgets","docAbstract":"<p><span>Arctic thaw lakes are an important source of water for aquatic ecosystems, wildlife, and humans. Many recent studies have observed changes in Arctic surface waters related to climate warming and permafrost thaw; however, explaining the trends and predicting future responses to warming is difficult without a stronger fundamental understanding of Arctic lake water budgets. By measuring and simulating surface and subsurface hydrologic fluxes, this work quantified the water budgets of three lakes with varying levels of seasonal drainage, and tested the hypothesis that lateral and subsurface flows are a major component of the post-snowmelt water budgets. A water budget focused only on post-snowmelt surface water fluxes (stream discharge, precipitation, and evaporation) could not close the budget for two of three lakes, even when uncertainty in input parameters was rigorously considered using a Monte Carlo approach. The water budgets indicated large, positive residuals, consistent with up to 70% of mid-summer inflows entering lakes from lateral fluxes. Lateral inflows and outflows were simulated based on three processes; supra-permafrost subsurface inflows from basin-edge polygonal ground, and exchange between seasonally drained lakes and their drained margins through runoff and evapotranspiration. Measurements and simulations indicate that rapid subsurface flow through highly conductive flowpaths in the polygonal ground can explain the majority of the inflow. Drained lakes were hydrologically connected to marshy areas on the lake margins, receiving water from runoff following precipitation and losing up to 38% of lake efflux to drained margin evapotranspiration. Lateral fluxes can be a major part of Arctic thaw lake water budgets and a major control on summertime lake water levels. Incorporating these dynamics into models will improve our ability to predict lake volume changes, solute fluxes, and habitat availability in the changing Arctic.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10917","usgsCitation":"Koch, J.C., 2016, Lateral and subsurface flows impact arctic coastal plain lake water budgets: Hydrological Processes, v. 30, no. 21, p. 3918-3931, https://doi.org/10.1002/hyp.10917.","productDescription":"14 p.","startPage":"3918","endPage":"3931","ipdsId":"IP-064008","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":342033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"30","issue":"21","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-21","publicationStatus":"PW","scienceBaseUri":"59327926e4b0e9bd0eab5513","contributors":{"authors":[{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":696929,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70188434,"text":"70188434 - 2016 - Seismic evidence of glacial-age river incision into the Tahaa barrier reef, French Polynesia","interactions":[],"lastModifiedDate":"2017-06-09T14:29:21","indexId":"70188434","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Seismic evidence of glacial-age river incision into the Tahaa barrier reef, French Polynesia","docAbstract":"<p><span>Rivers have long been recognized for their ability to shape reef-bound volcanic islands. On the time-scale of glacial–interglacial sea-level cycles, fluvial incision of exposed barrier reef lagoons may compete with constructional coral growth to shape the coastal geomorphology of ocean islands. However, overprinting of Pleistocene landscapes by Holocene erosion or sedimentation has largely obscured the role lowstand river incision may have played in developing the deep lagoons typical of modern barrier reefs. Here we use high-resolution seismic imagery and core stratigraphy to examine how erosion and/or deposition by upland drainage networks has shaped coastal morphology on Tahaa, a barrier reef-bound island located along the Society Islands hotspot chain in French Polynesia. At Tahaa, we find that many channels, incised into the lagoon floor during Pleistocene sea-level lowstands, are located near the mouths of upstream terrestrial drainages. Steeper antecedent topography appears to have enhanced lowstand fluvial erosion along Tahaa's southwestern coast and maintained a deep pass. During highstands, upland drainages appear to contribute little sediment to refilling accommodation space in the lagoon. Rather, the flushing of fine carbonate sediment out of incised fluvial channels by storms and currents appears to have limited lagoonal infilling and further reinforced development of deep barrier reef lagoons during periods of highstand submersion.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2016.04.008","usgsCitation":"Toomey, M., Woodruff, J.D., Ashton, A.D., and Perron, J.T., 2016, Seismic evidence of glacial-age river incision into the Tahaa barrier reef, French Polynesia: Marine Geology, v. 380, p. 284-289, https://doi.org/10.1016/j.margeo.2016.04.008.","productDescription":"6 p.","startPage":"284","endPage":"289","ipdsId":"IP-070030","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":470539,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.margeo.2016.04.008","text":"External Repository"},{"id":342343,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"French Polynesia","otherGeospatial":"Tahaa barrier reef","volume":"380","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593bb39fe4b0764e6c60e7b0","contributors":{"authors":[{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":697719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodruff, Jonathan D.","contributorId":192777,"corporation":false,"usgs":false,"family":"Woodruff","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":697720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ashton, Andrew D.","contributorId":96970,"corporation":false,"usgs":true,"family":"Ashton","given":"Andrew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":697721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perron, J. Taylor","contributorId":184100,"corporation":false,"usgs":false,"family":"Perron","given":"J.","email":"","middleInitial":"Taylor","affiliations":[],"preferred":false,"id":697722,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193041,"text":"70193041 - 2016 - Comparative use of side and main channels by small-bodied fish in a large, unimpounded river","interactions":[],"lastModifiedDate":"2017-11-06T16:39:50","indexId":"70193041","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","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":"Comparative use of side and main channels by small-bodied fish in a large, unimpounded river","docAbstract":"<ol id=\"fwb12796-list-0001\" class=\"o-list--numbered o-list--paragraph\"><li>Ecological theory and field studies suggest that lateral floodplain connectivity and habitat heterogeneity provided by side channels impart favourable habitat conditions for lotic fishes, especially fluvial fishes dependent on large patches of shallow, slow velocity habitats for some portion of their life cycle. However, anthropogenic modification of large, temperate floodplain rivers has led to extensive channel simplification and side-channel loss. Highly modified rivers consist of simplified channels in contracted, less dynamic floodplains.</li><li>Most research examining the seasonal importance of side channels for fish assemblages in large rivers has been carried out in heavily modified rivers, where side-channel extents are substantially reduced from pre-settlement times, and has often overlooked small-bodied fishes. Inferences about the ecological importance of side channels for small-bodied fishes in large rivers can be ascertained only from investigations of large rivers with largely intact floodplains. The Yellowstone River, our study area, is a rare example of one such river.</li><li>We targeted small-bodied fishes and compared their habitat use in side and main channels in two geomorphically distinct types of river bends during early and late snowmelt runoff, and autumn base flow. Species compositions of side and main channels differed throughout hydroperiods concurrent with the seasonal redistribution of the availability of shallow, slow current-velocity habitats. More species of fish used side channels than main channels during runoff. Additionally, catch rates of small fishes were generally greater in side channels than in main channels and quantitative assemblage compositions differed between channel types during runoff, but not during base flow. Presence of and access to diverse habitats facilitated the development and persistence of diverse fish assemblages in our study area.</li><li>Physical dissimilarities between side and main channels may have differentially structured the side- and main-channel fish assemblages during runoff. Patches of shallow, slow current-velocity (SSCV) habitats in side channels were larger and had slightly slower water velocities than SSCV habitat patches in main channels during runoff, but not during base flow.</li><li>Our findings establish a baseline importance of side channels to riverine fishes in a large, temperate river without heavy anthropogenic modification. Establishing this baseline contributes to basic fluvial ecology and provides empirical justification for restoration efforts that reconnect large rivers with their floodplains.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1111/fwb.12796","usgsCitation":"Reinhold, A.M., Bramblett, R.G., Zale, A.V., Roberts, D.W., and Poole, G., 2016, Comparative use of side and main channels by small-bodied fish in a large, unimpounded river: Freshwater Biology, v. 61, no. 10, p. 1611-1626, https://doi.org/10.1111/fwb.12796.","productDescription":"16 p.","startPage":"1611","endPage":"1626","ipdsId":"IP-064958","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":482071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/fwb.12796","text":"Publisher Index Page"},{"id":348310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Yellowstone River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.0498046875,\n              45.01141864227728\n            ],\n            [\n              -104.0185546875,\n              45.01141864227728\n            ],\n            [\n              -104.0185546875,\n              47.83528342275264\n            ],\n            [\n              -111.0498046875,\n              47.83528342275264\n            ],\n            [\n              -111.0498046875,\n              45.01141864227728\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"61","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-18","publicationStatus":"PW","scienceBaseUri":"5a07e9c5e4b09af898c8cc4b","contributors":{"authors":[{"text":"Reinhold, Ann Marie","contributorId":200043,"corporation":false,"usgs":false,"family":"Reinhold","given":"Ann","email":"","middleInitial":"Marie","affiliations":[],"preferred":false,"id":720781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bramblett, Robert G.","contributorId":169857,"corporation":false,"usgs":false,"family":"Bramblett","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":5098,"text":"Department of Ecology, Montana State University","active":true,"usgs":false}],"preferred":false,"id":720782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zale, Alexander V. 0000-0003-1703-885X zale@usgs.gov","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":3010,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"zale@usgs.gov","middleInitial":"V.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":717734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roberts, David W.","contributorId":56235,"corporation":false,"usgs":true,"family":"Roberts","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":720783,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poole, Geoffrey C.","contributorId":25540,"corporation":false,"usgs":true,"family":"Poole","given":"Geoffrey C.","affiliations":[],"preferred":false,"id":720784,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70193723,"text":"70193723 - 2016 - Magma decompression rates during explosive eruptions of Kīlauea volcano, Hawaii, recorded by melt embayments","interactions":[],"lastModifiedDate":"2017-11-03T18:01:31","indexId":"70193723","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Magma decompression rates during explosive eruptions of Kīlauea volcano, Hawaii, recorded by melt embayments","docAbstract":"<p>The decompression rate of magma as it ascends during volcanic eruptions is an important but poorly constrained parameter that controls many of the processes that influence eruptive behavior. In this study, we quantify decompression rates for basaltic magmas using volatile diffusion in olivine-hosted melt tubes (embayments) for three contrasting eruptions of Kīlauea volcano, Hawaii. Incomplete exsolution of H<sub>2</sub>O, CO<sub>2</sub>, and S from the embayment melts during eruptive ascent creates diffusion profiles that can be measured using microanalytical techniques, and then modeled to infer the average decompression rate. We obtain average rates of ~0.05–0.45&nbsp;MPa&nbsp;s<sup>−1</sup> for eruptions ranging from Hawaiian style fountains to basaltic subplinian, with the more intense eruptions having higher rates. The ascent timescales for these magmas vary from around ~5 to ~36&nbsp;min from depths of ~2 to ~4&nbsp;km, respectively. Decompression-exsolution models based on the embayment data also allow for an estimate of the mass fraction of pre-existing exsolved volatiles within the magma body. In the eruptions studied, this varies from 0.1 to 3.2&nbsp;wt% but does not appear to be the key control on eruptive intensity. Our results do not support a direct link between the concentration of pre-eruptive volatiles and eruptive intensity; rather, they suggest that for these eruptions, decompression rates are proportional to independent estimates of mass discharge rate. Although the intensity of eruptions is defined by the discharge rate, based on the currently available dataset of embayment analyses, it does not appear to scale linearly with average decompression rate. This study demonstrates the utility of the embayment method for providing quantitative constraints on magma ascent during explosive basaltic eruptions.</p>","language":"English","publisher":"Springer","doi":"10.1007/s00445-016-1064-x","usgsCitation":"Ferguson, D.J., Gonnermann, H.M., Ruprecht, P., Plank, T., Hauri, E.H., Houghton, B.F., and Swanson, D., 2016, Magma decompression rates during explosive eruptions of Kīlauea volcano, Hawaii, recorded by melt embayments: Bulletin of Volcanology, v. 78, no. 10, Article 71, https://doi.org/10.1007/s00445-016-1064-x.","productDescription":"Article 71","ipdsId":"IP-058137","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470599,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://eprints.whiterose.ac.uk/104505/1/Ferguson%20et%20al%202016.pdf","text":"External Repository"},{"id":348176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano","volume":"78","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-22","publicationStatus":"PW","scienceBaseUri":"59fd8029e4b0531197b50144","contributors":{"authors":[{"text":"Ferguson, David J.","contributorId":199795,"corporation":false,"usgs":false,"family":"Ferguson","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":13619,"text":"Department of Earth & Planetary Sciences, Harvard University, Cambridge, MA","active":true,"usgs":false},{"id":7135,"text":"Lamont Doherty Earth Observatory, Columbia University, Palisades, NY","active":true,"usgs":false},{"id":35453,"text":"University of Leeds, UK","active":true,"usgs":false}],"preferred":false,"id":720065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gonnermann, Helge M.","contributorId":48465,"corporation":false,"usgs":false,"family":"Gonnermann","given":"Helge","email":"","middleInitial":"M.","affiliations":[{"id":35613,"text":"Department of Earth Science, Rice University, Houston, TX 77005","active":true,"usgs":false}],"preferred":false,"id":720139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruprecht, Philipp","contributorId":199796,"corporation":false,"usgs":false,"family":"Ruprecht","given":"Philipp","email":"","affiliations":[{"id":35453,"text":"University of Leeds, UK","active":true,"usgs":false},{"id":7135,"text":"Lamont Doherty Earth Observatory, Columbia University, Palisades, NY","active":true,"usgs":false}],"preferred":false,"id":720140,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plank, Terry","contributorId":16743,"corporation":false,"usgs":false,"family":"Plank","given":"Terry","affiliations":[{"id":7135,"text":"Lamont Doherty Earth Observatory, Columbia University, Palisades, NY","active":true,"usgs":false}],"preferred":false,"id":720141,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hauri, Erik H.","contributorId":199798,"corporation":false,"usgs":false,"family":"Hauri","given":"Erik","email":"","middleInitial":"H.","affiliations":[{"id":35612,"text":"Department of Terrestrial Magnetism, Carnegie Institution of Washington, Washington DC 20015","active":true,"usgs":false}],"preferred":false,"id":720142,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false},{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":720143,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swanson, Donald A. donswan@usgs.gov","contributorId":149804,"corporation":false,"usgs":true,"family":"Swanson","given":"Donald A.","email":"donswan@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":720144,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
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