Here we document Alexandrium fundyense cyst abundance and distribution patterns over nine years (1997 and 2004–2011) in the coastal waters of the Gulf of Maine (GOM) and identify linkages between those patterns and several metrics of the severity or magnitude of blooms occurring before and after each autumn cyst survey. We also explore the relative utility of two measures of cyst abundance and demonstrate that GOM cyst counts can be normalized to sediment volume, revealing meaningful patterns equivalent to those determined with dry weight normalization.
\nCyst concentrations were highly variable spatially. Two distinct seedbeds (defined here as accumulation zones with>300 cysts cm−3) are evident, one in the Bay of Fundy (BOF) and one in mid-coast Maine. Overall, seedbed locations remained relatively constant through time, but their area varied 3–4 fold, and total cyst abundance more than 10 fold among years. A major expansion of the mid-coast Maine seedbed occurred in 2009 following an unusually intense A. fundyense bloom with visible red-water conditions, but that feature disappeared by late 2010. The regional system thus has only two seedbeds with the bathymetry, sediment characteristics, currents, biology, and environmental conditions necessary to persist for decades or longer. Strong positive correlations were confirmed between the abundance of cysts in both the 0–1 and the 0–3 cm layers of sediments in autumn and geographic measures of the extent of the bloom that occurred the next year (i.e., cysts→blooms), such as the length of coastline closed due to shellfish toxicity or the southernmost latitude of shellfish closures. In general, these metrics of bloom geographic extent did not correlate with the number of cysts in sediments following the blooms (blooms→cysts). There are, however, significant positive correlations between 0–3 cm cyst abundances and metrics of the preceding bloom that are indicative of bloom intensity or vegetative cell abundance (e.g., cumulative shellfish toxicity, duration of detectable toxicity in shellfish, and bloom termination date). These data suggest that it may be possible to use cyst abundance to empirically forecast the geographic extent of the forthcoming bloom and, conversely, to use other metrics from bloom and toxicity events to forecast the size of the subsequent cyst population as the inoculum for the next year's bloom. This is an important step towards understanding the excystment/encystment cycle in A. fundyense bloom dynamics while also augmenting our predictive capability for this HAB-forming species in the GOM.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Deep-Sea Research Part II: Topical Studies in Oceanography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2013.10.002","usgsCitation":"Anderson, D.M., Keafer, B.A., Kleindinst, J.L., McGillicuddy, D.J., Martin, J.L., Norton, K., Pilskaln, C.H., Smith, J.L., Sherwood, C.R., and Butman, B., 2014, Alexandrium fundyense cysts in the Gulf of Maine: long-term time series of abundance and distribution, and linkages to past and future blooms: Deep-Sea Research Part II: Topical Studies in Oceanography, v. 103, p. 6-26, https://doi.org/10.1016/j.dsr2.2013.10.002.","productDescription":"21 p.","startPage":"6","endPage":"26","numberOfPages":"21","ipdsId":"IP-049742","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472950,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4085992","text":"External Repository"},{"id":288095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288092,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.dsr2.2013.10.002"}],"country":"United States","state":"Maine","otherGeospatial":"Bay Of Fundy;Gulf Of Maine","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -72.0,40.0 ], [ -72.0,46.0 ], [ -65.0,46.0 ], [ -65.0,40.0 ], [ -72.0,40.0 ] ] ] } } ] }","volume":"103","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"539031cfe4b04eea98bf84b1","contributors":{"authors":[{"text":"Anderson, Donald M.","contributorId":79801,"corporation":false,"usgs":true,"family":"Anderson","given":"Donald","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":494358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keafer, Bruce A.","contributorId":102795,"corporation":false,"usgs":true,"family":"Keafer","given":"Bruce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":494360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kleindinst, Judith L.","contributorId":78251,"corporation":false,"usgs":true,"family":"Kleindinst","given":"Judith","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":494357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGillicuddy, Dennis J. Jr.","contributorId":13541,"corporation":false,"usgs":true,"family":"McGillicuddy","given":"Dennis","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":494354,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin, Jennifer L. jlmartin@usgs.gov","contributorId":2658,"corporation":false,"usgs":true,"family":"Martin","given":"Jennifer","email":"jlmartin@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":494352,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Norton, Kerry","contributorId":22692,"corporation":false,"usgs":true,"family":"Norton","given":"Kerry","email":"","affiliations":[],"preferred":false,"id":494356,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pilskaln, Cynthia H.","contributorId":90818,"corporation":false,"usgs":true,"family":"Pilskaln","given":"Cynthia","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":494359,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smith, Juliette L.","contributorId":20258,"corporation":false,"usgs":true,"family":"Smith","given":"Juliette","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":494355,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494353,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Butman, Bradford 0000-0002-4174-2073 bbutman@usgs.gov","orcid":"https://orcid.org/0000-0002-4174-2073","contributorId":943,"corporation":false,"usgs":true,"family":"Butman","given":"Bradford","email":"bbutman@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494351,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70111382,"text":"ds839 - 2014 - Topographic lidar survey of the Alabama, Mississippi, and Southeast Louisiana Barrier Islands, from September 5 to October 11, 2012","interactions":[],"lastModifiedDate":"2015-02-02T15:14:23","indexId":"ds839","displayToPublicDate":"2014-06-04T11:49:47","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"839","title":"Topographic lidar survey of the Alabama, Mississippi, and Southeast Louisiana Barrier Islands, from September 5 to October 11, 2012","docAbstract":"This Data Series Report contains lidar elevation data collected from September 5 to October 11, 2012, for the barrier islands of Alabama, Mississippi and southeast Louisiana, including the coast near Port Fourchon. Most of the data were collected September 5–10, 2012, with a reflight conducted on October 11, 2012, to increase point density in some areas. Point cloud data—data points described in three dimensions—in lidar data exchange format (LAS), and bare earth digital elevation models (DEMs) in ERDAS Imagine raster format (IMG), are available as downloadable files. The point cloud data were processed to extract bare earth data; therefore, the point cloud data are organized into four classes: 1-unclassified, 2-ground, 7-noise and 9-water. Aero-Metric, Inc., was contracted by the U.S. Geological Survey (USGS) to collect and process these data.
\n\n
The lidar data were acquired at a horizontal spacing (or nominal pulse spacing) of 1 meter (m) or less. The USGS conducted two ground surveys in a small area on Chandeleur Island on September 6, 2012, one on bare earth and the other in both bare earth and vegetated areas. The USGS calculated a vertical root mean square error (RMSEz) of 0.072 m and an offset of 0.007 m using interpolated 2-m by 2-m resolution grid surfaces made from the lidar bare-earth data and the combined USGS ground surveys. Aero-Metric, Inc., calculated an RMSEz of 0.025 m by comparing the USGS bare earth ground survey point data to the closest lidar points. The USGS also conducted a terrestrial lidar survey on Dauphin Island, Louisiana, on September 3, 2012. The USGS calculated a RMSEz of 0.32 m and an offset of 0.27 m, meaning the lidar data were 0.27 m higher than the ground truth (Guy and others, 2013), using interpolated 2-m by 2-m resolution grid surfaces from the airborne lidar bare-earth data and the terrestrial lidar survey.
\n\n
This lidar survey was acquired to document the changes of several different barrier island systems resulting from Hurricane Isaac (Guy and others, 2013). The survey supports detailed studies of Louisiana, Mississippi and Alabama barrier islands that resolve annual and episodic changes in beaches, berms and dunes associated with processes driven by storms, sea-level rise, and even human restoration activities.
\n\n
These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds839","usgsCitation":"Guy, K.K., Doran, K., Stockdon, H.F., and Plant, N.G., 2014, Topographic lidar survey of the Alabama, Mississippi, and Southeast Louisiana Barrier Islands, from September 5 to October 11, 2012: U.S. Geological Survey Data Series 839, HTML Document, https://doi.org/10.3133/ds839.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052682","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds839.jpg"},{"id":288070,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0839/ds839title.html"},{"id":288059,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0839/"}],"country":"United States","state":"Alabama; Louisiana; Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.131591796875,\n 28.695406284421967\n ],\n [\n -91.131591796875,\n 30.467614102257855\n ],\n [\n -87.967529296875,\n 30.467614102257855\n ],\n [\n -87.967529296875,\n 28.695406284421967\n ],\n [\n -91.131591796875,\n 28.695406284421967\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"539031d5e4b04eea98bf84cd","contributors":{"authors":[{"text":"Guy, Kristy K. kguy@usgs.gov","contributorId":45010,"corporation":false,"usgs":true,"family":"Guy","given":"Kristy","email":"kguy@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":false,"id":494325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doran, Kara S. 0000-0001-8050-5727 kdoran@usgs.gov","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":2496,"corporation":false,"usgs":true,"family":"Doran","given":"Kara S.","email":"kdoran@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":494323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stockdon, Hilary F. 0000-0003-0791-4676 hstockdon@usgs.gov","orcid":"https://orcid.org/0000-0003-0791-4676","contributorId":2153,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","email":"hstockdon@usgs.gov","middleInitial":"F.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":494322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":494324,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70111383,"text":"ds840 - 2014 - Topographic lidar survey of the Chandeleur Islands, Louisiana, February 6, 2012","interactions":[],"lastModifiedDate":"2014-06-04T11:54:19","indexId":"ds840","displayToPublicDate":"2014-06-04T11:49:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"840","title":"Topographic lidar survey of the Chandeleur Islands, Louisiana, February 6, 2012","docAbstract":"This Data Series Report contains lidar elevation data collected February 6, 2012, for Chandeleur Islands, Louisiana. Point cloud data in lidar data exchange format (LAS) and bare earth digital elevation models (DEMs) in ERDAS Imagine raster format (IMG) are available as downloadable files. The point cloud data—data points described in three dimensions—were processed to extract bare earth data; therefore, the point cloud data are organized into the following classes: 1– and 17–unclassified, 2–ground, 9–water, and 10–breakline proximity. Digital Aerial Solutions, LLC, (DAS) was contracted by the U.S. Geological Survey (USGS) to collect and process these data.
\nThe lidar data were acquired at a horizontal spacing (or nominal pulse spacing) of 0.5 meters (m) or less. The USGS conducted two ground surveys in small areas on the Chandeleur Islands on February 5, 2012. DAS calculated a root mean square error (RMSEz) of 0.034 m by comparing the USGS ground survey point data to triangulated irregular network (TIN) models built from the lidar elevation data.
\nThis lidar survey was conducted to document the topography and topographic change of the Chandeleur Islands. The survey supports detailed studies of Louisiana, Mississippi and Alabama barrier islands that resolve annual and episodic changes in beaches, berms and dunes associated with processes driven by storms, sea-level rise, and even human restoration activities. These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds840","usgsCitation":"Guy, K.K., Plant, N.G., and Bonisteel-Cormier, J.M., 2014, Topographic lidar survey of the Chandeleur Islands, Louisiana, February 6, 2012: U.S. Geological Survey Data Series 840, HTML document, https://doi.org/10.3133/ds840.","productDescription":"HTML document","onlineOnly":"Y","ipdsId":"IP-052857","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds840.jpg"},{"id":288060,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0840/"},{"id":288068,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0840/ds840title.html"}],"projection":"Universal Transverse Mercator projection, zone 16N","datum":"North American Datum of 1983","country":"United States","state":"Louisiana","otherGeospatial":"Chandeleur Islands","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.4946,29.1929 ], [ -89.4946,30.5019 ], [ -87.8975,30.5019 ], [ -87.8975,29.1929 ], [ -89.4946,29.1929 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"539031d5e4b04eea98bf84d1","contributors":{"authors":[{"text":"Guy, Kristy K. kguy@usgs.gov","contributorId":45010,"corporation":false,"usgs":true,"family":"Guy","given":"Kristy","email":"kguy@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":false,"id":494328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":494326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonisteel-Cormier, Jamie M.","contributorId":18085,"corporation":false,"usgs":true,"family":"Bonisteel-Cormier","given":"Jamie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":494327,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70111381,"text":"ds838 - 2014 - Topographic lidar survey of Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana, July 12-14, 2013","interactions":[],"lastModifiedDate":"2014-06-04T11:43:22","indexId":"ds838","displayToPublicDate":"2014-06-04T11:32:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"838","title":"Topographic lidar survey of Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana, July 12-14, 2013","docAbstract":"This Data Series Report contains lidar elevation data collected on July 12 and 14, 2013, for Dauphin Island, Alabama, and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana. Classified point cloud data—data points described in three dimensions—in lidar data exchange format (LAS) and bare earth digital elevation models (DEMs) in ERDAS Imagine raster format (IMG) are available as downloadable files. Photo Science, Inc., was contracted by the U.S. Geological Survey (USGS) to collect and process these data.
\nThe lidar data were acquired at a horizontal spacing (or nominal pulse spacing) of 1 meter (m) or less. The USGS surveyed points within the project area from July 14–23, 2013, for use in ground control and accuracy assessment. Photo Science, Inc., calculated a vertical root mean square error (RMSEz) of 0.012 m by comparing 10 surveyed points to an interpolated elevation surface of unclassified lidar data. The USGS also checked the data using 80 surveyed points and unclassified lidar point elevation data and found an RMSEz of 0.073 m. The project specified an RMSEz of 0.0925 m or less.
\nThe lidar survey was acquired to document the short- and long-term changes of several different barrier island systems. Specifically, this survey supports detailed studies of Chandeleur and Dauphin Islands that resolve annual changes in beaches, berms and dunes associated with processes driven by storms, sea-level rise, and even human restoration activities.
\nThese lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds838","usgsCitation":"Guy, K.K., and Plant, N.G., 2014, Topographic lidar survey of Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana, July 12-14, 2013: U.S. Geological Survey Data Series 838, HTML document, https://doi.org/10.3133/ds838.","productDescription":"HTML document","onlineOnly":"Y","ipdsId":"IP-052146","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds838.jpg"},{"id":288066,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0838/ds838title.html"},{"id":288058,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0838/"}],"projection":"Universal Transverse Mercator projection, zone 16N","datum":"North American Datum of 1983","country":"United States","state":"Alabama;Louisiana","otherGeospatial":"Breton Island;Chandeleur Islands;Dauphin Island;Grand Gosier Island;Stake Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.4946,29.1929 ], [ -89.4946,30.5019 ], [ -87.8975,30.5019 ], [ -87.8975,29.1929 ], [ -89.4946,29.1929 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"539031d4e4b04eea98bf84c9","contributors":{"authors":[{"text":"Guy, Kristy K. kguy@usgs.gov","contributorId":45010,"corporation":false,"usgs":true,"family":"Guy","given":"Kristy","email":"kguy@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":false,"id":494321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":494320,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70074260,"text":"sir20145017 - 2014 - Brine contamination to aquatic resources from oil and gas development in the Williston Basin, United States","interactions":[],"lastModifiedDate":"2022-04-22T20:32:36.016333","indexId":"sir20145017","displayToPublicDate":"2014-06-04T11:04:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5017","title":"Brine contamination to aquatic resources from oil and gas development in the Williston Basin, United States","docAbstract":"The Williston Basin, which includes parts of Montana, North Dakota, and South Dakota in the United States and the provinces of Manitoba and Saskatchewan in Canada, has been a leading domestic oil and gas producing region for more than one-half a century. Currently, there are renewed efforts to develop oil and gas resources from deep geologic formations, spurred by advances in recovery technologies and economic incentives associated with the price of oil. Domestic oil and gas production has many economic benefits and provides a means for the United States to fulfill a part of domestic energy demands; however, environmental hazards can be associated with this type of energy production in the Williston Basin, particularly to aquatic resources (surface water and shallow groundwater) by extremely saline water, or brine, which is produced with oil and gas. The primary source of concern is the migration of brine from buried reserve pits that were used to store produced water during recovery operations; however, there also are considerable risks of brine release from pipeline failures, poor infrastructure construction, and flow-back water from hydraulic fracturing associated with modern oilfield operations.
\nDuring 2008, a multidisciplinary (biology, geology, water) team of U.S. Geological Survey researchers was assembled to investigate potential energy production effects in the Williston Basin. Researchers from the U.S. Geological Survey participated in field tours and met with representatives from county, State, tribal, and Federal agencies to identify information needs and focus research objectives. Common questions from agency personnel, especially those from the U.S. Fish and Wildlife Service, were “are the brine plumes (plumes of brine-contaminated groundwater) from abandoned oil wells affecting wetlands on Waterfowl Production Areas and National Wildlife Refuges?” and “are newer wells related to Bakken and Three Forks development different than the older, abandoned wells (in terms of potential for affecting aquatic resources)?” Of special concern were the wetland habitats of the ecologically important Prairie Pothole Region, which overlays a part of the Williston Basin and is recognized for the production of a majority of North America’s migratory waterfowl.
\nOn the basis of the concerns raised by on-the-ground land managers, as well as findings from previous research, a comprehensive study was developed with the following goals: summarize existing information pertaining to oil and gas production and aquatic resources in the Williston Basin; assess brine plume migration from new and previously studied sites in the Prairie Pothole Region; perform a regional, spatial evaluation of oil and gas production activities and aquatic resources; assess the potential for brine contamination to wetlands and streams; and hold a decision analysis workshop with key stakeholders to discuss issues pertaining to oil and gas production and environmental effects and to identify information gaps and research needs.
\nThis report represents an initial, multidisciplinary evaluation of measured and potential environmental effects associated with oil and gas production in the Williston Basin and Prairie Pothole Region. Throughout this report there are reviews of current knowledge, and discussions relating to data gaps and research needs. On the basis of the information presented, future research needs include: regional geophysical and water-quality assessments to establish baselines for current conditions and estimate the extent of previous brine contamination, investigations into the direct effects of brine to biotic communities, and evaluations to identify the most effective techniques to mitigate brine contamination.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145017","usgsCitation":"Chesley-Preston, T.L., Coleman, J.L., Gleason, R.A., Haines, S.S., Jenni, K., Nieman, T.L., Peterman, Z., van der Burg, M.P., Preston, T.M., Smith, B.D., Tangen, B., and Thamke, J., 2014, Brine contamination to aquatic resources from oil and gas development in the Williston Basin, United States: U.S. Geological Survey Scientific Investigations Report 2014-5017, 140 p., https://doi.org/10.3133/sir20145017.","productDescription":"140 p.","onlineOnly":"N","ipdsId":"IP-044530","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science 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48.93693495409401\n ],\n [\n -105.5126953125,\n 46.08847179577592\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"539031d1e4b04eea98bf84bd","contributors":{"editors":[{"text":"Gleason, Robert A. 0000-0001-5308-8657 rgleason@usgs.gov","orcid":"https://orcid.org/0000-0001-5308-8657","contributorId":2402,"corporation":false,"usgs":true,"family":"Gleason","given":"Robert","email":"rgleason@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":509774,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Tangen, Brian A.","contributorId":78419,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian A.","affiliations":[],"preferred":false,"id":509775,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Chesley-Preston, Tara L. tchesley-preston@usgs.gov","contributorId":5557,"corporation":false,"usgs":true,"family":"Chesley-Preston","given":"Tara","email":"tchesley-preston@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":489437,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coleman, James L. jlcoleman@usgs.gov","contributorId":141060,"corporation":false,"usgs":true,"family":"Coleman","given":"James","email":"jlcoleman@usgs.gov","middleInitial":"L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":489436,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gleason, Robert A. 0000-0001-5308-8657 rgleason@usgs.gov","orcid":"https://orcid.org/0000-0001-5308-8657","contributorId":2402,"corporation":false,"usgs":true,"family":"Gleason","given":"Robert","email":"rgleason@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":489430,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haines, Seth S. 0000-0003-2611-8165 shaines@usgs.gov","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":1344,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","email":"shaines@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":489434,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jenni, Karen E.","contributorId":21256,"corporation":false,"usgs":true,"family":"Jenni","given":"Karen E.","affiliations":[],"preferred":false,"id":489438,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nieman, Timothy L.","contributorId":103967,"corporation":false,"usgs":true,"family":"Nieman","given":"Timothy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":489441,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Peterman, Zell E. 0000-0002-5694-8082 peterman@usgs.gov","orcid":"https://orcid.org/0000-0002-5694-8082","contributorId":620,"corporation":false,"usgs":true,"family":"Peterman","given":"Zell E.","email":"peterman@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":489431,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"van der Burg, Max Post","contributorId":92580,"corporation":false,"usgs":true,"family":"van der Burg","given":"Max","email":"","middleInitial":"Post","affiliations":[],"preferred":false,"id":489440,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Preston, Todd M. 0000-0002-8812-9233 tmpreston@usgs.gov","orcid":"https://orcid.org/0000-0002-8812-9233","contributorId":1664,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","email":"tmpreston@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":489435,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Smith, Bruce D. 0000-0002-1643-2997 bsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-1643-2997","contributorId":845,"corporation":false,"usgs":true,"family":"Smith","given":"Bruce","email":"bsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":489432,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Tangen, Brian A.","contributorId":78419,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian A.","affiliations":[],"preferred":false,"id":489439,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thamke, Joanna N. 0000-0002-6917-1946 jothamke@usgs.gov","orcid":"https://orcid.org/0000-0002-6917-1946","contributorId":1012,"corporation":false,"usgs":true,"family":"Thamke","given":"Joanna N.","email":"jothamke@usgs.gov","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":489433,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70049024,"text":"ofr20131272 - 2014 - Compilation of gallium resource data for bauxite deposits","interactions":[],"lastModifiedDate":"2018-10-22T10:13:33","indexId":"ofr20131272","displayToPublicDate":"2014-06-03T15:29:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1272","title":"Compilation of gallium resource data for bauxite deposits","docAbstract":"Gallium (Ga) concentrations for bauxite deposits worldwide have been compiled from the literature to provide a basis for research regarding the occurrence and distribution of Ga worldwide, as well as between types of bauxite deposits. In addition, this report is an attempt to bring together reported Ga concentration data into one database to supplement ongoing U.S. Geological Survey studies of critical mineral resources.
\nThe compilation of Ga data consists of location, deposit size, bauxite type and host rock, development status, major oxide data, trace element (Ga) data and analytical method(s) used to derive the data, and tonnage values for deposits within bauxite provinces and districts worldwide. The range in Ga concentrations for bauxite deposits worldwide is <10 to 812 parts per million (ppm), with an average of 57 ppm. Gallium concentrations in lateritic bauxites range from below detection (< 8 ppm) to 146 ppm; the average concentration is 57 ppm Ga. The average Ga concentration for karst bauxite deposits is 58 ppm with a range between <10 to 180 ppm Ga. As a result, there are no substantial differences in gallium concentrations between karst- and laterite-type bauxites. We calculate the range in geologically available Ga in bauxite deposits worldwide between 30 and 82,720 metric tons (t), with an average of 14,909 t.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131272","issn":"2331-1258","collaboration":"Mineral Resources Program","usgsCitation":"Schulte, R., and Foley, N.K., 2014, Compilation of gallium resource data for bauxite deposits: U.S. Geological Survey Open-File Report 2013-1272, Report: iv, 14 p.; Table: ZIP file, https://doi.org/10.3133/ofr20131272.","productDescription":"Report: iv, 14 p.; Table: ZIP file","numberOfPages":"21","onlineOnly":"Y","ipdsId":"IP-048881","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":288047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131272.jpg"},{"id":288044,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1272/","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":288046,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1272/table/ofr2013-1272_tables.zip","linkFileType":{"id":6,"text":"zip"}},{"id":288045,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1272/pdf/ofr2013-1272.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"538ee050e4b0d497d49684bd","contributors":{"authors":[{"text":"Schulte, Ruth F.","contributorId":68604,"corporation":false,"usgs":true,"family":"Schulte","given":"Ruth F.","affiliations":[],"preferred":false,"id":486040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foley, Nora K. 0000-0003-0124-3509 nfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-0124-3509","contributorId":4010,"corporation":false,"usgs":true,"family":"Foley","given":"Nora","email":"nfoley@usgs.gov","middleInitial":"K.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":486039,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70068743,"text":"sir20135241 - 2014 - Spatial and stratigraphic distribution of water in oil shale of the Green River Formation using Fischer assay, Piceance Basin, northwestern Colorado","interactions":[],"lastModifiedDate":"2014-06-03T14:13:22","indexId":"sir20135241","displayToPublicDate":"2014-06-03T14:07:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5241","title":"Spatial and stratigraphic distribution of water in oil shale of the Green River Formation using Fischer assay, Piceance Basin, northwestern Colorado","docAbstract":"The spatial and stratigraphic distribution of water in oil shale of the Eocene Green River Formation in the Piceance Basin of northwestern Colorado was studied in detail using some 321,000 Fischer assay analyses in the U.S. Geological Survey oil-shale database. The oil-shale section was subdivided into 17 roughly time-stratigraphic intervals, and the distribution of water in each interval was assessed separately. This study was conducted in part to determine whether water produced during retorting of oil shale could provide a significant amount of the water needed for an oil-shale industry. Recent estimates of water requirements vary from 1 to 10 barrels of water per barrel of oil produced, depending on the type of retort process used. Sources of water in Green River oil shale include (1) free water within clay minerals; (2) water from the hydrated minerals nahcolite (NaHCO3), dawsonite (NaAl(OH)2CO3), and analcime (NaAlSi2O6.H20); and (3) minor water produced from the breakdown of organic matter in oil shale during retorting. The amounts represented by each of these sources vary both stratigraphically and areally within the basin. Clay is the most important source of water in the lower part of the oil-shale interval and in many basin-margin areas. Nahcolite and dawsonite are the dominant sources of water in the oil-shale and saline-mineral depocenter, and analcime is important in the upper part of the formation. Organic matter does not appear to be a major source of water. The ratio of water to oil generated with retorting is significantly less than 1:1 for most areas of the basin and for most stratigraphic intervals; thus water within oil shale can provide only a fraction of the water needed for an oil-shale industry.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135241","issn":"2328-0328","usgsCitation":"Johnson, R.C., Mercier, T.J., and Brownfield, M.E., 2014, Spatial and stratigraphic distribution of water in oil shale of the Green River Formation using Fischer assay, Piceance Basin, northwestern Colorado: U.S. Geological Survey Scientific Investigations Report 2013-5241, Report: vii, 108 p.; 1 Plate: 104.88 x 84.72 inches, https://doi.org/10.3133/sir20135241.","productDescription":"Report: vii, 108 p.; 1 Plate: 104.88 x 84.72 inches","onlineOnly":"Y","ipdsId":"IP-024872","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":288039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135241.jpg"},{"id":288036,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5241/"},{"id":288037,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5241/pdf/sir2013-5241.pdf"},{"id":288038,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5241/download/plate1.pdf"}],"country":"United States","state":"Colorado","otherGeospatial":"Green River Formation;Piceance Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0,38.0 ], [ -109.0,41.0 ], [ -106.0,41.0 ], [ -106.0,38.0 ], [ -109.0,38.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"538ee05ce4b0d497d49684d9","contributors":{"authors":[{"text":"Johnson, Ronald C. 0000-0002-6197-5165 rcjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-6197-5165","contributorId":1550,"corporation":false,"usgs":true,"family":"Johnson","given":"Ronald","email":"rcjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":488095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mercier, Tracey J. 0000-0002-8232-525X tmercier@usgs.gov","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":2847,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey","email":"tmercier@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":488096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":488094,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70111702,"text":"70111702 - 2014 - The carbon cycle and hurricanes in the United States between 1900 and 2011","interactions":[],"lastModifiedDate":"2014-06-06T13:40:00","indexId":"70111702","displayToPublicDate":"2014-06-03T13:35:34","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"The carbon cycle and hurricanes in the United States between 1900 and 2011","docAbstract":"Hurricanes cause severe impacts on forest ecosystems in the United States. These events can substantially alter the carbon biogeochemical cycle at local to regional scales. We selected all tropical storms and more severe events that made U.S. landfall between 1900 and 2011 and used hurricane best track database, a meteorological model (HURRECON), National Land Cover Database (NLCD), U. S. Department of Agirculture Forest Service biomass dataset, and pre- and post-MODIS data to quantify individual event and annual biomass mortality. Our estimates show an average of 18.2 TgC/yr of live biomass mortality for 1900–2011 in the US with strong spatial and inter-annual variability. Results show Hurricane Camille in 1969 caused the highest aboveground biomass mortality with 59.5 TgC. Similarly 1954 had the highest annual mortality with 68.4 TgC attributed to landfalling hurricanes. The results presented are deemed useful to further investigate historical events, and the methods outlined are potentially beneficial to quantify biomass loss in future events.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Scientific Reports","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Nature Publishing Group","doi":"10.1038/srep05197","usgsCitation":"Dahal, D., Liu, S., and Oeding, J., 2014, The carbon cycle and hurricanes in the United States between 1900 and 2011: Scientific Reports, v. 4, no. 5197, 10 p., https://doi.org/10.1038/srep05197.","productDescription":"10 p.","ipdsId":"IP-054728","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472953,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep05197","text":"Publisher Index Page"},{"id":288150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288146,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1038/srep05197"}],"country":"United States","volume":"4","issue":"5197","noUsgsAuthors":false,"publicationDate":"2014-06-06","publicationStatus":"PW","scienceBaseUri":"53ae7863e4b0abf75cf2d3ee","contributors":{"authors":[{"text":"Dahal, Devendra 0000-0001-9594-1249 ddahal@usgs.gov","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":5622,"corporation":false,"usgs":true,"family":"Dahal","given":"Devendra","email":"ddahal@usgs.gov","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":494445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shu-Guang sliu@usgs.gov","contributorId":984,"corporation":false,"usgs":true,"family":"Liu","given":"Shu-Guang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":494443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oeding, Jennifer joeding@usgs.gov","contributorId":4070,"corporation":false,"usgs":true,"family":"Oeding","given":"Jennifer","email":"joeding@usgs.gov","affiliations":[],"preferred":true,"id":494444,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70073693,"text":"sir20135235 - 2014 - Occurrence and hydrogeochemistry of radiochemical constituents in groundwater of Jefferson County and surrounding areas, southwestern Montana, 2007 through 2010","interactions":[],"lastModifiedDate":"2014-07-31T16:03:46","indexId":"sir20135235","displayToPublicDate":"2014-06-03T12:35:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5235","title":"Occurrence and hydrogeochemistry of radiochemical constituents in groundwater of Jefferson County and surrounding areas, southwestern Montana, 2007 through 2010","docAbstract":"The U.S. Geological Survey, in cooperation with Jefferson County and the Jefferson Valley Conservation District, sampled groundwater in southwestern Montana to evaluate the occurrence and concentration of naturally-occurring radioactive constituents and to identify geologic settings and environmental conditions in which elevated concentrations occur. A total of 168 samples were collected from 128 wells within Broadwater, Deer Lodge, Jefferson, Lewis and Clark, Madison, Powell, and Silver Bow Counties from 2007 through 2010. Most wells were used for domestic purposes and were primary sources of drinking water for individual households. Water-quality samples were collected from wells completed within six generalized geologic units, and analyzed for constituents including uranium, radon, gross alpha-particle activity, and gross beta-particle activity. Thirty-eight wells with elevated concentrations or activities were sampled a second time to examine variability in water quality throughout time. These water-quality samples were analyzed for an expanded list of radioactive constituents including the following: three isotopes of uranium (uranium-234, uranium-235, and uranium-238), three isotopes of radium (radium-224, radium-226, and radium-228), and polonium-210. Existing U.S. Geological Survey and Montana Bureau of Mines and Geology uranium and radon water-quality data collected as part of other investigations through 2011 from wells within the study area were compiled as part of this investigation. Water-quality data from this study were compared to data collected nationwide by the U.S. Geological Survey through 2011.
\nRadionuclide samples for this study typically were analyzed within a few days after collection, and therefore data for this study may closely represent the concentrations and activities of water being consumed locally from domestic wells. Radioactive constituents were detected in water from every well sampled during this study regardless of location or geologic unit. Nearly 41 percent of sampled wells had at least one radioactive constituent concentration that exceeded U.S. Environmental Protection Agency drinking-water standards or screening levels. Uranium concentrations were higher than the U.S. Environmental Protection Agency maximum contaminant level (MCL) of 30 micrograms per liter in samples from 14 percent of the wells. Radon concentrations exceeded a proposed MCL of 4,000 picocuries per liter in 27 percent of the wells. Combined radium (radium-226 and radium-228) exceeded the MCL of 5 picocuries per liter in samples from 10 of 47 wells. About 40 percent (42 of 104 wells) of the wells had gross alpha-particle activities (72-hour count) at or greater than a screening level of 15 pCi/L. Gross beta-particle activity exceeded the U.S. Environmental Protection Agency 50 picocuries per liter screening level in samples from 5 of 104 wells. Maximum radium-224 and polonium-210 activities in study wells were 16.1 and 3.08 picocuries per liter, respectively; these isotopes are constituents of human-health concern, but the U.S. Environmental Protection Agency has not established MCLs for them.
\nRadioactive constituent concentrations or activities exceeded at least one established drinking-water standard, proposed drinking-water standard, or screening level in groundwater samples from five of six generalized geologic units assessed during this study. Radioactive constituent concentrations or activities were variable not only within each geologic unit, but also among wells that were completed in the same geologic unit and in close proximity to one another. Established or proposed drinking-water standards were exceeded most frequently in water from wells completed in the generalized geologic unit that includes rocks of the Boulder batholith and other Tertiary through Cretaceous igneous intrusive rocks (commonly described as granite). Specifically, of the wells completed in the Boulder batholith and related rocks sampled as part of this study, 24 percent exceeded the MCL of 30 micrograms per liter for uranium, 50 percent exceeded the proposed alternative MCL of 4,000 picocuries per liter for radon, and 27 percent exceeded the MCL of 5 micrograms per liter for combined radium-226 and radium-228.
\nElevated radioactive constituent values were detected in samples representing a large range of field properties and water types. Correlations between radioactive constituents and pH, dissolved oxygen, and most major ions were not statistically significant (p-value > 0.05) or were weakly correlated with Spearman correlation coefficients (rho) ranging from -0.5 to 0.5. Moderate correlations did exist between gross beta-particle activity and potassium (rho = 0.72 to 0.82), likely because one potassium isotope (potassium-40) is a beta-particle emitter. Total dissolved solids and specific conductance also were moderately correlated (rho = 0.62 to 0.71) with gross alpha-particle and gross beta-particle activity, indicating that higher radioactivity values can be associated with higher total dissolved solids.
\nCorrelations were evaluated among radioactive constituents. Moderate to strong correlations occurred between gross alpha-particle and beta-particle activities (rho = 0.77 to 0.96) and radium isotopes (rho = 0.78 to 0.92). Correlations between gross alpha-particle activity (72-hour count) and all analyzed radioactive constituents were statistically significant (p-value < 0.05), and therefore, gross alpha-particle activity likely may be used as a screening tool for determining the presence of radionuclides in area waters. In this study, gross alpha-particle activities of 7 picocuries per liter or greater were associated with all radioactive constituents whose concentrations exceeded drinking-water standards or screening levels.
\nRadiochemical results varied temporally in samples from several of the thirty-eight wells sampled at least twice during the study. The time between successive sampling events ranged from about 1 to 10 months for 29 wells to about 3 years for the other 9 wells. Radiochemical constituents that varied by greater than 30 percent between sampling events included uranium (29 percent of the resampled wells), and radon (11 percent of the resampled wells), gross alpha-particle activity (38 percent of the resampled wells), and gross beta-particle activity (15 percent of the resampled wells). Variability in uranium concentrations from two wells was sufficiently large that concentrations were less than the MCL in the first set of samples and greater than the MCL in the second.
\nSample holding times affect analytical results in this study. Gross alpha-particle and gross beta-particle activities were measured twice, 72 hours and 30 days after sample collection. Gross alpha-particle activity decreased an average of 37 percent between measurements, indicating the presence of short-lived alpha-emitting radionuclides in these samples. Gross beta-particle activity increased an average of 31 percent between measurements, indicating ingrowth of longer-lived beta-emitting radionuclides.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135235","issn":"2328-0328","collaboration":"Prepared in cooperation with Jefferson County and the Jefferson Valley Conservation District, Montana","usgsCitation":"Caldwell, R.R., Nimick, D.A., and DeVaney, R.M., 2014, Occurrence and hydrogeochemistry of radiochemical constituents in groundwater of Jefferson County and surrounding areas, southwestern Montana, 2007 through 2010: U.S. Geological Survey Scientific Investigations Report 2013-5235, Report: x, 61 p.; Downloads directory, https://doi.org/10.3133/sir20135235.","productDescription":"Report: x, 61 p.; Downloads directory","numberOfPages":"76","onlineOnly":"N","temporalStart":"2007-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-042934","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":287984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135235.jpg"},{"id":287981,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5235/"},{"id":287982,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5235/pdf/sir2013-5235.pdf"},{"id":287983,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5235/downloads/Appendix%20.xlsx"}],"scale":"100000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1927","country":"United States","state":"Montana","county":"Jefferson County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.0,45.5 ], [ -113.0,47.0 ], [ -111.5,47.0 ], [ -111.5,45.5 ], [ -113.0,45.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"538ee05be4b0d497d49684d5","contributors":{"authors":[{"text":"Caldwell, Rodney R. 0000-0002-2588-715X caldwell@usgs.gov","orcid":"https://orcid.org/0000-0002-2588-715X","contributorId":2577,"corporation":false,"usgs":true,"family":"Caldwell","given":"Rodney","email":"caldwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":489047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nimick, David A. dnimick@usgs.gov","contributorId":421,"corporation":false,"usgs":true,"family":"Nimick","given":"David","email":"dnimick@usgs.gov","middleInitial":"A.","affiliations":[{"id":573,"text":"Special Applications Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":489046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeVaney, Rainie M.","contributorId":84668,"corporation":false,"usgs":true,"family":"DeVaney","given":"Rainie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":489048,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70111081,"text":"70111081 - 2014 - Muskie lunacy: does the lunar cycle influence angler catch of muskellunge (Esox masquinongy)?","interactions":[],"lastModifiedDate":"2014-06-04T08:36:13","indexId":"70111081","displayToPublicDate":"2014-06-03T10:32:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Muskie lunacy: does the lunar cycle influence angler catch of muskellunge (Esox masquinongy)?","docAbstract":"We analyzed angling catch records for 341,959 muskellunge (Esox masquinongy) from North America to test for a cyclic lunar influence on the catch. Using periodic regression, we showed that the number caught was strongly related to the 29-day lunar cycle, and the effect was consistent across most fisheries. More muskellunge were caught around the full and new moon than at other times. At night, more muskellunge were caught around the full moon than the new moon. The predicted maximum relative effect was ≈5% overall. Anglers fishing exclusively on the peak lunar day would, on average, catch 5% more muskellunge than anglers fishing on random days. On some lakes and at night, the maximum relative effect was higher. We obtained angler effort data for Wisconsin, Mille Lacs (MN), and Lake Vermilion (MN). For Lake Vermilion there was a significant effect of the lunar cycle on angler effort. We could therefore not conclude that the lunar effect on catch was due to an effect on fish behavior alone. Several factors affected the amount of variation explained by the lunar cycle. The lunar effect was stronger for larger muskellunge (>102 cm) than for smaller fish, stronger in midsummer than in June or October, and stronger for fish caught at high latitudes (>48°N) than for fish caught further south. There was no difference in the lunar effect between expert and novice muskellunge anglers. We argue that this variation is evidence that the effect of the lunar cycle on catch is mediated by biological factors and is not due solely to angler effort and reflects lunar synchronization in feeding. This effect has been attributed to variation among moon phases in lunar illumination, but our results do not support that hypothesis for angler-caught muskellunge.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0098046","usgsCitation":"Vinson, M., and Angradi, T.R., 2014, Muskie lunacy: does the lunar cycle influence angler catch of muskellunge (Esox masquinongy)?: PLoS ONE, v. 9, no. 5, 12 p., https://doi.org/10.1371/journal.pone.0098046.","productDescription":"12 p.","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-053959","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":472954,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0098046","text":"Publisher Index Page"},{"id":287977,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287976,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0098046"}],"country":"Canada;United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -179.6,18.9 ], [ -179.6,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ -179.6,18.9 ] ] ] } } ] }","volume":"9","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-05-28","publicationStatus":"PW","scienceBaseUri":"538ee05be4b0d497d49684d1","contributors":{"authors":[{"text":"Vinson, Mark R.","contributorId":91774,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark R.","affiliations":[],"preferred":false,"id":494241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angradi, Ted R.","contributorId":107618,"corporation":false,"usgs":true,"family":"Angradi","given":"Ted","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":494242,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70111231,"text":"70111231 - 2014 - Ecological factors affecting Rainbow Smelt recruitment in the main basin of Lake Huron, 1976-2010","interactions":[],"lastModifiedDate":"2014-06-03T08:54:34","indexId":"70111231","displayToPublicDate":"2014-06-03T08:45:00","publicationYear":"2014","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":"Ecological factors affecting Rainbow Smelt recruitment in the main basin of Lake Huron, 1976-2010","docAbstract":"Rainbow Smelt Osmerus mordax are native to northeastern Atlantic and Pacific–Arctic drainages and have been widely introduced throughout North America. In the Great Lakes region, Rainbow Smelt are known predators and competitors of native fish and a primary prey species in pelagic food webs. Despite their widespread distribution, importance as a prey species, and potential to negatively interact with native fish species, there is limited information concerning stock–recruitment relationships for Rainbow Smelt. To better understand recruitment mechanisms, we evaluated potential ecological factors determining recruitment dynamics for Rainbow Smelt in Lake Huron using data from bottom trawl catches. We specifically evaluated influence of stock size, environmental factors (water temperature, lake levels, and precipitation), and salmonine predation on the production of age-0 recruits from 1976 to 2010. Rainbow Smelt recruitment was negatively related to stock size exceeding 10 kg/ha, indicating that compensatory, density-dependent mortality from cannibalism or intraspecific competition was an important factor related to the production of age-0 recruits. Recruitment was positively related to spring precipitation suggesting that the amount of stream-spawning habitat as determined by precipitation was important for the production of strong Rainbow Smelt recruitment. Additionally, density of age-0 Rainbow Smelt was positively related to Lake Trout Salvelinus namaycush abundance. However, spawning stock biomass of Rainbow Smelt, which declined substantially from 1989 to 2010, was negatively associated with Lake Trout catch per effort suggesting predation was an important factor related to the decline of age-2 and older Rainbow Smelt in Lake Huron. As such, we found that recruitment of Rainbow Smelt in Lake Huron was regulated by competition with or cannibalism by older conspecifics, spring precipitation influencing stream spawning habitats, and predation by Lake Trout on age-2 and older Rainbow Smelt.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Transactions of the American Fisheries Society","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2014.880736","usgsCitation":"O’Brien, T.P., Taylor, W., Roseman, E., Madenjian, C.P., and Riley, S., 2014, Ecological factors affecting Rainbow Smelt recruitment in the main basin of Lake Huron, 1976-2010: Transactions of the American Fisheries Society, v. 143, no. 3, p. 784-795, https://doi.org/10.1080/00028487.2014.880736.","productDescription":"12 p.","startPage":"784","endPage":"795","numberOfPages":"12","ipdsId":"IP-048900","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":287972,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287971,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/00028487.2014.880736"}],"country":"Canada;United States","otherGeospatial":"Great Lakes;Lake Huron","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.8373,42.874 ], [ -84.8373,46.4985 ], [ -80.8572,46.4985 ], [ -80.8572,42.874 ], [ -84.8373,42.874 ] ] ] } } ] }","volume":"143","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-05-02","publicationStatus":"PW","scienceBaseUri":"538ee055e4b0d497d49684c1","contributors":{"authors":[{"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":494267,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, William W.","contributorId":49735,"corporation":false,"usgs":false,"family":"Taylor","given":"William W.","affiliations":[],"preferred":false,"id":494268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roseman, Edward F.","contributorId":100334,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[],"preferred":false,"id":494270,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":494266,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riley, Stephen C.","contributorId":84183,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen C.","affiliations":[],"preferred":false,"id":494269,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70110391,"text":"fs20143052 - 2014 - Remote sensing of land surface phenology","interactions":[],"lastModifiedDate":"2018-02-21T10:38:42","indexId":"fs20143052","displayToPublicDate":"2014-06-02T15:07:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3052","title":"Remote sensing of land surface phenology","docAbstract":"Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143052","usgsCitation":"Meier, G., and Brown, J.F., 2014, Remote sensing of land surface phenology: U.S. Geological Survey Fact Sheet 2014-3052, 2 p., https://doi.org/10.3133/fs20143052.","productDescription":"2 p.","onlineOnly":"Y","ipdsId":"IP-049727","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":287966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143052.jpg"},{"id":287965,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3052/pdf/fs2014-3052.pdf"},{"id":287963,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3052/"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7813e4b0abf75cf2c8f3","contributors":{"authors":[{"text":"Meier, G.A.","contributorId":85888,"corporation":false,"usgs":true,"family":"Meier","given":"G.A.","email":"","affiliations":[],"preferred":false,"id":494057,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":3241,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":494056,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70102823,"text":"ofr20141020 - 2014 - Transmissivity and storage coefficient estimates from slug tests, Naval Air Warfare Center, West Trenton, New Jersey","interactions":[],"lastModifiedDate":"2020-05-28T20:11:46.424521","indexId":"ofr20141020","displayToPublicDate":"2014-06-02T10:28:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1020","title":"Transmissivity and storage coefficient estimates from slug tests, Naval Air Warfare Center, West Trenton, New Jersey","docAbstract":"Slug tests were conducted on 56 observation wells open to bedrock at the former Naval Air Warfare Center (NAWC) in West Trenton, New Jersey. Aquifer transmissivity (T) and storage coefficient (S) values for most wells were estimated from slug-test data using the Cooper-Bredehoeft-Papadopulos method. Test data from three wells exhibited fast, underdamped water-level responses and were analyzed with the Butler high-K method. The range of T at NAWC was approximately 0.07 to 10,000 square feet per day. At 11 wells, water levels did not change measurably after 20 minutes following slug insertion; transmissivity at these 11 wells was estimated to be less than 0.07 square feet per day. The range of S was approximately 10-10 to 0.01, the mode being 10-10. Water-level responses for tests at three wells fit poorly to the type curves of both methods, indicating that these methods were not appropriate for adequately estimating T and S from those data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141020","collaboration":"Toxic Substances Hydrology Program. Prepared in cooperation with U.S. Department of the Navy","usgsCitation":"Fiore, A.R., 2014, Transmissivity and storage coefficient estimates from slug tests, Naval Air Warfare Center, West Trenton, New Jersey: U.S. Geological Survey Open-File Report 2014-1020, Report: HTML document; Table 1, https://doi.org/10.3133/ofr20141020.","productDescription":"Report: HTML document; Table 1","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049724","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":287950,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1020/report/table/table1.xlsx"},{"id":287949,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1020/report/title.html"},{"id":287948,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1020/"},{"id":375134,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2014/1020/images/coverthb.jpg"}],"country":"United States","state":"New Jersey","city":"West Trenton","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.819974,40.264976 ], [ -74.819974,40.275041 ], [ -74.804359,40.275041 ], [ -74.804359,40.264976 ], [ -74.819974,40.264976 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae787ae4b0abf75cf2d6b7","contributors":{"authors":[{"text":"Fiore, Alex R. 0000-0002-0986-5225 afiore@usgs.gov","orcid":"https://orcid.org/0000-0002-0986-5225","contributorId":4977,"corporation":false,"usgs":true,"family":"Fiore","given":"Alex","email":"afiore@usgs.gov","middleInitial":"R.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493028,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70104569,"text":"70104569 - 2014 - Spatial variability and landscape controls of near-surface permafrost within the Alaskan Yukon River Basin","interactions":[],"lastModifiedDate":"2018-01-12T17:20:31","indexId":"70104569","displayToPublicDate":"2014-06-01T15:39:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Spatial variability and landscape controls of near-surface permafrost within the Alaskan Yukon River Basin","docAbstract":"The distribution of permafrost is important to understand because of permafrost's influence on high-latitude ecosystem structure and functions. Moreover, near-surface (defined here as within 1 m of the Earth's surface) permafrost is particularly susceptible to a warming climate and is generally poorly mapped at regional scales. Subsequently, our objectives were to (1) develop the first-known binary and probabilistic maps of near-surface permafrost distributions at a 30 m resolution in the Alaskan Yukon River Basin by employing decision tree models, field measurements, and remotely sensed and mapped biophysical data; (2) evaluate the relative contribution of 39 biophysical variables used in the models; and (3) assess the landscape-scale factors controlling spatial variations in permafrost extent. Areas estimated to be present and absent of near-surface permafrost occupy approximately 46% and 45% of the Alaskan Yukon River Basin, respectively; masked areas (e.g., water and developed) account for the remaining 9% of the landscape. Strong predictors of near-surface permafrost include climatic indices, land cover, topography, and Landsat 7 Enhanced Thematic Mapper Plus spectral information. Our quantitative modeling approach enabled us to generate regional near-surface permafrost maps and provide essential information for resource managers and modelers to better understand near-surface permafrost distribution and how it relates to environmental factors and conditions.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research: Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/2013JG002594","usgsCitation":"Pastick, N.J., Jorgenson, M., Wylie, B.K., Rose, J.R., Rigge, M., and Walvoord, M.A., 2014, Spatial variability and landscape controls of near-surface permafrost within the Alaskan Yukon River Basin: Journal of Geophysical Research: Biogeosciences, v. 119, no. 6, p. 1244-1265, https://doi.org/10.1002/2013JG002594.","productDescription":"22 p.","startPage":"1244","endPage":"1265","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056842","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472957,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013jg002594","text":"Publisher Index Page"},{"id":294946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294945,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2013JG002594"}],"country":"United States","state":"Alaska","otherGeospatial":"Alaskan Yukon River Basin","volume":"119","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-06-30","publicationStatus":"PW","scienceBaseUri":"542fbaaee4b092f17df61dfa","contributors":{"authors":[{"text":"Pastick, Neal J. 0000-0002-8169-3018 njpastick@usgs.gov","orcid":"https://orcid.org/0000-0002-8169-3018","contributorId":4785,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"njpastick@usgs.gov","middleInitial":"J.","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},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":493735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jorgenson, M. 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Since 1995, hunters have collected gobbling and jake observation data, while the Mississippi Department of Wildlife, Fisheries, and Parks' personnel and cooperating wildlife managers of several natural resource agencies throughout the state have collected brood survey data. Both sources of data serve to forecast poult recruitment and gobbling activity. The objective of this study was to evaluate if these data can serve as a viable predictor of gobbling activity. We used three mixed models to investigate the relationship between the number of jakes observed per hour of hunting 1 y prior and the total number of poults per hens 2 y prior (model 1), number of gobblers heard per hour of hunting and the number of jakes observed per hour of hunting 1 y prior (model 2), the number of gobblers heard per hour of hunting and the total number poults per total hens observed 2 y prior (model 3) using data from 1995 to 2008 among five wild turkey management regions encompassing the state. We incorporated region as a random effect to account for spatial variation. We found the number of jakes observed per hour of hunting 1 y prior correlated with the total number of poults per total hens observed 2 y prior. We also found the number of gobblers heard per hour of hunting correlated with the number of jakes observed per hour of hunting 1 y prior. Additionally, we found that the total poults per total hens observed 2 y prior was correlated to the number of gobblers heard per hour of hunting. Our results show promise for using indices of gobbling activity, jake observations, and brood surveys to estimate gobbling activity.
","language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"Washington, D.C.","doi":"10.3996/032013-JFWM-023","usgsCitation":"Palumbo, M.D., Vilella, F., Strickland, B.K., Wang, G., and Godwin, D., 2014, Brood surveys and hunter observations used to predict gobbling activity wild turkeys in Mississippi: Journal of Fish and Wildlife Management, v. 5, no. 1, p. 151-156, https://doi.org/10.3996/032013-JFWM-023.","productDescription":"6 p.","startPage":"151","endPage":"156","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051370","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":472961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/032013-jfwm-023","text":"Publisher Index Page"},{"id":306286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-01-01","publicationStatus":"PW","scienceBaseUri":"55bc9c29e4b033ef52100f16","contributors":{"authors":[{"text":"Palumbo, Matthew D.","contributorId":146265,"corporation":false,"usgs":false,"family":"Palumbo","given":"Matthew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":566913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vilella, Francisco fvilella@usgs.gov","contributorId":4255,"corporation":false,"usgs":true,"family":"Vilella","given":"Francisco","email":"fvilella@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":564762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Strickland, Bronson K.","contributorId":146266,"corporation":false,"usgs":false,"family":"Strickland","given":"Bronson","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":566914,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Guiming","contributorId":146267,"corporation":false,"usgs":false,"family":"Wang","given":"Guiming","affiliations":[],"preferred":false,"id":566915,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Godwin, Dave","contributorId":146268,"corporation":false,"usgs":false,"family":"Godwin","given":"Dave","email":"","affiliations":[],"preferred":false,"id":566916,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70121943,"text":"70121943 - 2014 - Development and characterization of 16 polymorphic microsatellite loci for the Alaska blackfish (Esociformes: Dallia pectoralis)","interactions":[],"lastModifiedDate":"2018-08-20T18:07:03","indexId":"70121943","displayToPublicDate":"2014-06-01T11:41:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1325,"text":"Conservation Genetics Resources","active":true,"publicationSubtype":{"id":10}},"title":"Development and characterization of 16 polymorphic microsatellite loci for the Alaska blackfish (Esociformes: Dallia pectoralis)","docAbstract":"Blackfishes (Esociformes: Esocidae: Dallia), small fishes with relictual distributions, are unique in being the only primary freshwater fish genus endemic to Beringia. Although the number of species of Dallia is debated, disjunct populations and distinct mitochondrial divisions that predate the end of the last glacial maximum are apparent. We developed sixteen polymorphic microsatellites from the Alaska blackfish (Dallia pectoralis) to study genetic diversity in Dallia. Genotypes from two populations, Denali (n = 31) and Bethel (n = 35), demonstrated the usefulness of the loci for population-level investigation. Observed and expected heterozygosity averaged 18.6 and 19.8 % in Denali and 61.1 and 63.7 % in Bethel. Number of alleles at each locus averaged 3.50 in Denali and 9.63 in Bethel. The observed signature of variability and structuring between populations is consistent with mitochondrial data.
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Archaeological data and traditional cultural use provide tools for resolving these issues. Although the painted turtle (Chrysemys picta) has a transcontinental range in the United States, populations in the Desert Southwest are scattered and isolated. This pattern may be related to the fragmentation of a more continuous distribution as a result of climate change after the Pleistocene, or translocation by Native Americans who used turtles for food and ceremonial purposes. Because of these conflicting or potentially confounded possibilities, the distribution and status of C. picta as a native species in the state of Arizona has been questioned in the herpetological literature. We present evidence of a population that once occurred in the vicinity of Winslow, Arizona, far from current remnant populations on the upper Little Colorado River. Members of the Native American Hopi tribe are known to have hunted turtles for ceremonial purposes in this area as far back as AD 1290 and possibly earlier. Remains of C. picta are known from several pueblos in the vicinity including Homol'ovi, Awatovi, and Walpi. Given the great age of records for C. picta in Arizona and the concordance of its fragmented and isolated distribution with other reptiles in the region, we conclude that painted turtles are part of the native fauna of Arizona.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Copeia","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The American Society of Ichthyologists and Herpetologists","doi":"10.1643/CH-13-076","usgsCitation":"Lovich, J.E., LaRue, C.T., Drost, C.A., and Arundel, T., 2014, Traditional cultural use as a tool for inferring biogeography and provenance: a case study involving painted turtles (Chrysemys picta) and Hopi Native American culture in Arizona, USA: Copeia, v. 2014, no. 2, p. 215-220, https://doi.org/10.1643/CH-13-076.","productDescription":"6 p.","startPage":"215","endPage":"220","numberOfPages":"6","ipdsId":"IP-052540","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":289042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":289035,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1643/CH-13-076"}],"country":"United States","state":"Arizona;Utah","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.3554,32.6275 ], [ -113.3554,37.5376 ], [ -108.3311,37.5376 ], [ -108.3311,32.6275 ], [ -113.3554,32.6275 ] ] ] } } ] }","volume":"2014","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53abef88e4b0dad35f8e8ccc","contributors":{"authors":[{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":495303,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaRue, Charles T.","contributorId":87460,"corporation":false,"usgs":true,"family":"LaRue","given":"Charles","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":495306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drost, Charles A. 0000-0002-4792-7095 charles_drost@usgs.gov","orcid":"https://orcid.org/0000-0002-4792-7095","contributorId":3151,"corporation":false,"usgs":true,"family":"Drost","given":"Charles","email":"charles_drost@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":495304,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arundel, Terence R.","contributorId":11080,"corporation":false,"usgs":true,"family":"Arundel","given":"Terence R.","affiliations":[],"preferred":false,"id":495305,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70155811,"text":"70155811 - 2014 - Annual crop type classification of the U.S. Great Plains for 2000 to 2011","interactions":[],"lastModifiedDate":"2017-01-18T11:34:03","indexId":"70155811","displayToPublicDate":"2014-06-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Annual crop type classification of the U.S. Great Plains for 2000 to 2011","docAbstract":"The purpose of this study was to increase the spatial and temporal availability of crop classification data. In this study, nearly 16.2 million crop observation points were used in the training of the US Great Plains classification tree crop type model (CTM). Each observation point was further defined by weekly Normalized Difference Vegetation Index, annual climate, and a number of other biogeophysical environmental characteristics. This study accounted for the most prevalent crop types in the region, including, corn, soybeans, winter wheat, spring wheat, cotton, sorghum, and alfalfa. Annual CTM crop maps of the US Great Plains were created for 2000 to 2011 at a spatial resolution of 250 meters. The CTM achieved an 87 percent classification success rate on 1.8 million observation points that were withheld from model training. Product validation was performed on greater than 15,000 county records with a coefficient of determination of R2 = 0.76.
","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.80.6.537-549","usgsCitation":"Howard, D., and Wylie, B.K., 2014, Annual crop type classification of the U.S. Great Plains for 2000 to 2011: Photogrammetric Engineering and Remote Sensing, v. 6, p. 537-549, https://doi.org/10.14358/PERS.80.6.537-549.","productDescription":"12 p.","startPage":"537","endPage":"549","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-048833","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473143,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.80.6.537-549","text":"Publisher Index Page"},{"id":306937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Plains","volume":"6","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d5a8ade4b0518e3546a4ac","contributors":{"authors":[{"text":"Howard, Daniel M. 0000-0002-7563-7538 dhoward@usgs.gov","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":139585,"corporation":false,"usgs":true,"family":"Howard","given":"Daniel M.","email":"dhoward@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":566419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","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":566420,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70133416,"text":"70133416 - 2014 - Ecological change on California's Channel Islands from the Pleistocene to the Anthropocene","interactions":[],"lastModifiedDate":"2014-11-21T11:26:52","indexId":"70133416","displayToPublicDate":"2014-06-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Ecological change on California's Channel Islands from the Pleistocene to the Anthropocene","docAbstract":"Historical ecology is becoming an important focus in conservation biology and offers a promising tool to help guide ecosystem management. Here, we integrate data from multiple disciplines to illuminate the past, present, and future of biodiversity on California's Channel Islands, an archipelago that has undergone a wide range of land-use and ecological changes. Our analysis spans approximately 20,000 years, from before human occupation and through Native American hunter–gatherers, commercial ranchers and fishers, the US military, and other land managers. We demonstrate how long-term, interdisciplinary research provides insight into conservation decisions, such as setting ecosystem restoration goals, preserving rare and endemic taxa, and reducing the impacts of climate change on natural and cultural resources. We illustrate the importance of historical perspectives for understanding modern patterns and ecological change and present an approach that can be applied generally in conservation management planning.
","language":"English","publisher":"American Institute of Biological Sciences","doi":"10.1093/biosci/biu094","usgsCitation":"Rick, T.C., Sillett, T., Ghalambor, C.K., Hofman, C.A., Ralls, K., Anderson, R., Boser, C.L., Braje, T.J., Cayan, D.R., Chesser, R., Collins, P.W., Erlandson, J.M., Faulkner, K.R., Fleischer, R.C., Funk, W.C., Galipeau, R., Huston, A., King, J., Laughrin, L.L., Maldonado, J., McEachern, K., Muhs, D.R., Newsome, S.D., Reeder-Myers, L., Still, C., and Morrison, S.A., 2014, Ecological change on California's Channel Islands from the Pleistocene to the Anthropocene: BioScience, https://doi.org/10.1093/biosci/biu094.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052751","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472972,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biu094","text":"Publisher Index Page"},{"id":296130,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Channel Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.50354003906249,\n 32.77341935497515\n ],\n [\n -120.50354003906249,\n 34.098159345215535\n ],\n [\n -118.29528808593751,\n 34.098159345215535\n ],\n [\n -118.29528808593751,\n 32.77341935497515\n ],\n [\n -120.50354003906249,\n 32.77341935497515\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2014-07-11","publicationStatus":"PW","scienceBaseUri":"546c7606e4b0f4a3478a611c","contributors":{"authors":[{"text":"Rick, Torben C.","contributorId":127440,"corporation":false,"usgs":false,"family":"Rick","given":"Torben","email":"","middleInitial":"C.","affiliations":[{"id":6997,"text":"Department of Anthropology, Smithsonian Institution National Museum of Natural History (NMNH)","active":true,"usgs":false}],"preferred":false,"id":525162,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sillett, T. 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Using the stony coral Lophelia pertusa as a model organism with the potential for wide larval dispersal, we investigated how the global ocean conveyor drove an unprecedented post-glacial range expansion in Earth׳s largest biome, the deep sea. We compiled a unique ocean-scale dataset of published radiocarbon and uranium-series dates of fossil corals, the sedimentary protactinium–thorium record of Atlantic meridional overturning circulation (AMOC) strength, authigenic neodymium and lead isotopic ratios of circulation pathways, and coral biogeography, and integrated new Bayesian estimates of historic gene flow. Our compilation shows how the export of Southern Ocean and Mediterranean waters after the Younger Dryas 11.6 kyr ago simultaneously triggered two dispersal events in the western and eastern Atlantic respectively. Each pathway injected larvae from refugia into ocean currents powered by a re-invigorated AMOC that led to the fastest postglacial range expansion ever recorded, covering 7500 km in under 400 years. In addition to its role in modulating global climate, our study illuminates how the ocean conveyor creates broad geographic ranges that lower extinction risk in the deep sea.
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This study utilized multiple tracers to improve conceptual and numerical models of groundwater flow in the Middle San Pedro Basin in southeastern Arizona (USA) by determining recharge areas, compartmentalization of water sources, flowpaths and residence times. Ninety-five groundwater and surface-water samples were analyzed for major ion chemistry (water type and Ca/Sr ratios) and stable (18O, 2H, 13C) and radiogenic (3H, 14C) isotopes, and resulting data were used in conjunction with hydrogeologic information (e.g. hydraulic head and hydrostratigraphy). Results show that recent recharge (<60 years) has occurred within mountain systems along the basin margins and in shallow floodplain aquifers adjacent to the San Pedro River. Groundwater in the lower basin fill aquifer (semi confined) was recharged at high elevation in the fractured bedrock and has been extensively modified by water-rock reactions (increasing F and Sr, decreasing 14C) over long timescales (up to 35,000 years BP). Distinct solute and isotope geochemistries between the lower and upper basin fill aquifers show the importance of a clay confining unit on groundwater flow in the basin, which minimizes vertical groundwater movement.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-013-1090-0","usgsCitation":"Hopkins, C.B., McIntosh, J.C., Eastoe, C., Dickinson, J.E., and Meixner, T., 2014, Evaluation of the importance of clay confining units on groundwaterflow in alluvial basins using solute and isotope tracers: the case of Middle San Pedro Basin in southeastern Arizona (USA): Hydrogeology Journal, v. 22, no. 4, p. 829-849, https://doi.org/10.1007/s10040-013-1090-0.","productDescription":"21 p.","startPage":"829","endPage":"849","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051843","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":314312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Middle San Pedro Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.27526855468749,\n 31.49191979634118\n ],\n [\n -110.27526855468749,\n 31.93351676190369\n ],\n [\n -109.6710205078125,\n 31.93351676190369\n ],\n [\n -109.6710205078125,\n 31.49191979634118\n ],\n [\n -110.27526855468749,\n 31.49191979634118\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-01-18","publicationStatus":"PW","scienceBaseUri":"5698d4c9e4b0fbd3f7fa4c32","contributors":{"authors":[{"text":"Hopkins, Candice B. 0000-0003-3207-7267 chopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-3207-7267","contributorId":1379,"corporation":false,"usgs":true,"family":"Hopkins","given":"Candice","email":"chopkins@usgs.gov","middleInitial":"B.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":582106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McIntosh, Jennifer C.","contributorId":139870,"corporation":false,"usgs":false,"family":"McIntosh","given":"Jennifer","email":"","middleInitial":"C.","affiliations":[{"id":13301,"text":"Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona","active":true,"usgs":false}],"preferred":false,"id":582108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eastoe, Chris","contributorId":150558,"corporation":false,"usgs":false,"family":"Eastoe","given":"Chris","email":"","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":582109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":582107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meixner, Thomas","contributorId":22653,"corporation":false,"usgs":false,"family":"Meixner","given":"Thomas","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":582110,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155205,"text":"70155205 - 2014 - Water quality of potential reference lakes in the Arkansas Valley and Ouachita Mountain ecoregions, Arkansas","interactions":[],"lastModifiedDate":"2015-08-05T10:00:15","indexId":"70155205","displayToPublicDate":"2014-06-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Water quality of potential reference lakes in the Arkansas Valley and Ouachita Mountain ecoregions, Arkansas","docAbstract":"This report describes a study to identify reference lakes in two lake classifications common to parts of two level III ecoregions in western Arkansas—the Arkansas Valley and Ouachita Mountains. Fifty-two lakes were considered. A screening process that relied on land-use data was followed by reconnaissance water-quality sampling, and two lakes from each ecoregion were selected for intensive water-quality sampling. Our data suggest that Spring Lake is a suitable reference lake for the Arkansas Valley and that Hot Springs Lake is a suitable reference lake for the Ouachita Mountains. Concentrations for five nutrient constituents—orthophosphorus, total phosphorus, total kjeldahl nitrogen, total nitrogen, and total organic carbon—were lower at Spring Lake on all nine sampling occasions and transparency measurements at Spring Lake were significantly deeper than measurements at Cove Lake. For the Ouachita Mountains ecoregion, water quality at Hot Springs Lake slightly exceeded that of Lake Winona. The most apparent water-quality differences for the two lakes were related to transparency and total organic carbon concentrations, which were deeper and lower at Hot Springs Lake, respectively. Our results indicate that when nutrient concentrations are low, transparency may be more valuable for differentiating between lake water quality than chemical constituents that have been useful for distinguishing between water-quality conditions in mesotrophic and eutrophic settings. For example, in this oligotrophic setting, concentrations for chlorophyll a can be less than 5 μg/L and diurnal variability that is typically associated with dissolved oxygen in more productive settings was not evident.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-014-3657-1","usgsCitation":"Justus, B., and Meredith, B.J., 2014, Water quality of potential reference lakes in the Arkansas Valley and Ouachita Mountain ecoregions, Arkansas: Environmental Monitoring and Assessment, v. 186, no. 6, p. 3785-3800, https://doi.org/10.1007/s10661-014-3657-1.","productDescription":"16 p.","startPage":"3785","endPage":"3800","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053314","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":306422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Arkansas Valley; Ouachita Mountain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.47143554687499,\n 34.052659421375964\n ],\n [\n -93.85620117187499,\n 34.07086232376631\n ],\n [\n -93.109130859375,\n 34.08906131584996\n ],\n [\n -92.52685546875,\n 34.45221847282654\n ],\n [\n -91.92260742187499,\n 35.074964853989556\n ],\n [\n -91.40625,\n 35.7019167328534\n ],\n [\n -94.493408203125,\n 35.755428369259626\n ],\n [\n -94.4384765625,\n 35.27253175660236\n ],\n [\n -94.47143554687499,\n 34.052659421375964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"186","issue":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2014-02-15","publicationStatus":"PW","scienceBaseUri":"55c333b1e4b033ef52106aaa","contributors":{"authors":[{"text":"Justus, B. G. 0000-0002-3458-9656 bjustus@usgs.gov","orcid":"https://orcid.org/0000-0002-3458-9656","contributorId":2052,"corporation":false,"usgs":true,"family":"Justus","given":"B. G.","email":"bjustus@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":565068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meredith, Bradley J. bmeredith@usgs.gov","contributorId":5515,"corporation":false,"usgs":true,"family":"Meredith","given":"Bradley","email":"bmeredith@usgs.gov","middleInitial":"J.","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":565069,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70158658,"text":"70158658 - 2014 - Assessing effects of variation in global climate data sets on spatial predictions from climate envelope models","interactions":[],"lastModifiedDate":"2016-07-17T23:46:39","indexId":"70158658","displayToPublicDate":"2014-06-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Assessing effects of variation in global climate data sets on spatial predictions from climate envelope models","docAbstract":"Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/072012-JFWM-056","usgsCitation":"Romanach, S.S., Watling, J.I., Fletcher, R.J., Speroterra, C., Bucklin, D.N., Brandt, L., Pearlstine, L.G., Escribano, Y., and Mazzotti, F., 2014, Assessing effects of variation in global climate data sets on spatial predictions from climate envelope models: Journal of Fish and Wildlife Management, v. 5, no. 1, p. 14-25, https://doi.org/10.3996/072012-JFWM-056.","productDescription":"12 p.","startPage":"14","endPage":"25","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-027374","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":472969,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/072012-jfwm-056","text":"Publisher Index Page"},{"id":309526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":309494,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.3996/072012-JFWM-056"}],"volume":"5","issue":"1","publishingServiceCenter":{"id":7,"text":"Ft. Lauderdale PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-01","publicationStatus":"PW","scienceBaseUri":"560faab2e4b0ba4884c5eea7","contributors":{"authors":[{"text":"Romanach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":140419,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","email":"sromanach@usgs.gov","middleInitial":"S.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":576377,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watling, James I.","contributorId":10352,"corporation":false,"usgs":true,"family":"Watling","given":"James","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":576444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fletcher, Robert J. Jr.","contributorId":41294,"corporation":false,"usgs":true,"family":"Fletcher","given":"Robert","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":576445,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Speroterra, Carolina","contributorId":34451,"corporation":false,"usgs":true,"family":"Speroterra","given":"Carolina","affiliations":[],"preferred":false,"id":576446,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bucklin, David N.","contributorId":44812,"corporation":false,"usgs":true,"family":"Bucklin","given":"David","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":576447,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brandt, Laura A.","contributorId":23089,"corporation":false,"usgs":true,"family":"Brandt","given":"Laura A.","affiliations":[],"preferred":false,"id":576448,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pearlstine, Leonard G.","contributorId":34751,"corporation":false,"usgs":false,"family":"Pearlstine","given":"Leonard","email":"","middleInitial":"G.","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":576449,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Escribano, Yesenia","contributorId":149009,"corporation":false,"usgs":false,"family":"Escribano","given":"Yesenia","email":"","affiliations":[],"preferred":false,"id":576450,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mazzotti, Frank J.","contributorId":90236,"corporation":false,"usgs":true,"family":"Mazzotti","given":"Frank J.","affiliations":[],"preferred":false,"id":576451,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70133233,"text":"70133233 - 2014 - Adverse outcome pathway and risks of anticoagulant rodenticides to predatory wildlife","interactions":[],"lastModifiedDate":"2018-09-04T16:39:31","indexId":"70133233","displayToPublicDate":"2014-06-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Adverse outcome pathway and risks of anticoagulant rodenticides to predatory wildlife","docAbstract":"Despite a long history of successful use, routine application of some anticoagulant rodenticides (ARs) may be at a crossroad due to new regulatory guidelines intended to mitigate risk. An adverse outcome pathway for ARs was developed to identify information gaps and end points to assess the effectiveness of regulations. This framework describes chemical properties of ARs, established macromolecular interactions by inhibition of vitamin K epoxide reductase, cellular responses including altered clotting factor processing and coagulopathy, organ level effects such as hemorrhage, organism responses with linkages to reduced fitness and mortality, and potential consequences to predator populations. Risk assessments have led to restrictions affecting use of some second-generation ARs (SGARs) in North America. While the European regulatory community highlighted significant or unacceptable risk of ARs to nontarget wildlife, use of SGARs in most EU member states remains authorized due to public health concerns and the absence of safe alternatives. For purposes of conservation and restoration of island habitats, SGARs remain a mainstay for eradication of invasive species. There are significant data gaps related to exposure pathways, comparative species sensitivity, consequences of sublethal effects, potential hazards of greater AR residues in genetically resistant prey, effects of low-level exposure to multiple rodenticides, and quantitative data on the magnitude of nontarget wildlife mortality.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/es501740n","usgsCitation":"Rattner, B.A., Lazarus, R.S., Elliott, J., Shore, R.F., and van den Brink, N., 2014, Adverse outcome pathway and risks of anticoagulant rodenticides to predatory wildlife: Environmental Science & Technology, v. 48, no. 15, p. 8433-8445, https://doi.org/10.1021/es501740n.","productDescription":"13 p.","startPage":"8433","endPage":"8445","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056122","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":499911,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research.wur.nl/en/publications/adverse-outcome-pathway-and-risks-of-anticoagulant-rodenticides-t","text":"External Repository"},{"id":296044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"15","noUsgsAuthors":false,"publicationDate":"2014-07-09","publicationStatus":"PW","scienceBaseUri":"5465d62be4b04d4b7dbd6539","contributors":{"authors":[{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":524917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lazarus, Rebecca S. 0000-0003-1731-6469 rlazarus@usgs.gov","orcid":"https://orcid.org/0000-0003-1731-6469","contributorId":5594,"corporation":false,"usgs":true,"family":"Lazarus","given":"Rebecca","email":"rlazarus@usgs.gov","middleInitial":"S.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":524918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, John E.","contributorId":127368,"corporation":false,"usgs":false,"family":"Elliott","given":"John E.","affiliations":[{"id":6779,"text":"Environment Canada, Burlington, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":524919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shore, Richard F.","contributorId":127369,"corporation":false,"usgs":false,"family":"Shore","given":"Richard","email":"","middleInitial":"F.","affiliations":[{"id":6919,"text":"Natural Environment Research Council, UK","active":true,"usgs":false}],"preferred":false,"id":524920,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van den Brink, Nico","contributorId":127370,"corporation":false,"usgs":false,"family":"van den Brink","given":"Nico","affiliations":[{"id":6920,"text":"Wageningen University, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":524921,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70146208,"text":"70146208 - 2014 - Forcing functions governing salt transport processes in coastal navigation canals and connectivity to surrounding marshes in South Louisiana using Houma Navigation Canal as a surrogate","interactions":[],"lastModifiedDate":"2015-12-07T15:04:15","indexId":"70146208","displayToPublicDate":"2014-06-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Forcing functions governing salt transport processes in coastal navigation canals and connectivity to surrounding marshes in South Louisiana using Houma Navigation Canal as a surrogate","docAbstract":"Understanding how circulation and mixing processes in coastal navigation canals influence the exchange of salt between marshes and coastal ocean, and how those processes are modulated by external physical processes, is critical to anticipating effects of future actions and circumstance. Examples of such circumstances include deepening the channel, placement of locks in the channel, changes in freshwater discharge down the channel, changes in outer continental shelf (OCS) vessel traffic volume, and sea level rise. The study builds on previous BOEM-funded studies by investigating salt flux variability through the Houma Navigation Canal (HNC). It examines how external physical factors, such as buoyancy forcing and mixing from tidal stirring and OCS vessel wakes, influence dispersive and advective fluxes through the HNC and the impact of this salt flux on salinity in nearby marshes. This study quantifies salt transport processes and salinity variability in the HNC and surrounding Terrebonne marshes. Data collected for this study include time-series data of salinity and velocity in the HNC, monthly salinity-depth profiles along the length of the channel, hourly vertical profiles of velocity and salinity over multiple tidal cycles, and salinity time series data at three locations in the surrounding marshes along a transect of increasing distance from the HNC. Two modes of vertical current structure were identified. The first mode, making up 90% of the total flow field variability, strongly resembled a barotropic current structure and was coherent with alongshelf wind stress over the coastal Gulf of Mexico. The second mode was indicative of gravitational circulation and was linked to variability in tidal stirring and the longitudinal salinity gradients along the channel’s length. Diffusive process were dominant drivers of upestuary salt transport, except during periods of minimal tidal stirring when gravitational circulation became more important. Salinity in the surrounding marshes was much more responsive to salinity variations in the HNC than it was to variations in the lower Terrebonne marshes, suggesting that the HNC is the primary conduit for saltwater intrusion to the middle Terrebonne marshes. Finally, salt transport to the middle Terrebonne marshes directly associated with vessel wakes was negligible.
","language":"English","publisher":"Bureau of Ocean Energy Management, Department of the Interior","publisherLocation":"New Orleans, LA","usgsCitation":"Snedden, G., 2014, Forcing functions governing salt transport processes in coastal navigation canals and connectivity to surrounding marshes in South Louisiana using Houma Navigation Canal as a surrogate, v. BOEM 2014-607, xxi, 64 p.","productDescription":"xxi, 64 p.","startPage":"1","endPage":"64","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045516","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":312022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":299660,"type":{"id":15,"text":"Index Page"},"url":"https://www.data.boem.gov/PI/PDFImages/ESPIS/5/5411.pdf"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.86242675781249,\n 29.173747044774984\n ],\n [\n -90.86242675781249,\n 29.57942881484495\n ],\n [\n -90.60012817382812,\n 29.57942881484495\n ],\n [\n -90.60012817382812,\n 29.173747044774984\n ],\n [\n -90.86242675781249,\n 29.173747044774984\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"BOEM 2014-607","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5666bbd7e4b06a3ea36c8b1f","contributors":{"authors":[{"text":"Snedden, Gregg 0000-0001-7821-3709 sneddeng@usgs.gov","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":140235,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","email":"sneddeng@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":544813,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}