The Piceance and Yellow Creek watersheds in Rio Blanco County, Colorado, are known to contain important energy resources (oil shale and natural gas) and mineral resources (nahcolite). The primary sources of fresh groundwater in the Piceance and Yellow Creek watersheds are bedrock aquifers in the Uinta and Green River Formations. The aquifers are divided into an upper and lower aquifer separated by a regionally extensive semiconfining layer. These aquifers provide water to streams and springs in the watersheds and are an important resource to people living and working in the area. Development of energy and mineral resources has the potential to affect the quality of groundwater in several ways. The Bureau of Land Management and the U.S. Geological Survey began groundwater monitoring in 2010 to characterize the groundwater quality and water-level elevations of shallow bedrock aquifers in the Piceance and Yellow Creek watersheds. The purpose of this report is to present ground-water chemistry and water-level elevations collected during 2013–16. Comparisons are made to data that were collected from the bedrock aquifers from 2010 to 2012 to identify the potential for changes in water quality and water-level elevations.
Appreciable changes in water-level elevations and hydraulic gradient were observed in early April 2015 in two wells completed in the upper and lower aquifers. The hydraulic gradient between the two wells was consistently downward from the upper aquifer to the lower aquifer during 2010–15; however, in early April 2015, the gradient changed from downward to upward between the two aquifers. Overall, water-level elevations declined by about 14 and 11 feet in the upper and lower aquifers, respectively, from 2013 to 2016. Previously published data estimated groundwater ages at 1,200 years old in the upper aquifer and 9,600 years old in the lower aquifer. These groundwater ages indicate that ground-water was recharged over thousands of years. With such long periods of time for aquifer recharge, declines in water-level elevation over short time steps (a few months) have important implications for sustainable management of this resource. Solution mining activities or drilling for oil and natural gas in the area could be related to the changes observed in water-level elevations in these wells; however, further investigation would be needed to evaluate causation.
Changes in major-ion chemistry were evaluated in the bedrock aquifer using time series plots of select major-ion data from 2010 to 2016. Major-ion chemistry was variable for a single well from 2010 to 2016 where alkalinity and sulfate were the most variable constituents. One possible explanation for the observed changes in major-ion chemistry may be that the sample depth for that well no longer represents the most appreciable flow in the borehole. On a larger scale, potential changes in flow within the borehole may indicate changes in the regional flow system. Methane and volatile organic compound concentrations were evaluated using a similar approach to that of major ions and had similar findings. Methane concentrations in wells sampled from 2010 to 2016 were generally constant. The only exception was observed at a single well where the range of methane concentrations was from 57.4 (2010) to 4.02 milligrams per liter (2013). This is the same well where changes in water-level elevation, hydraulic gradient, and major-ion chemistry were observed, providing multiple lines of evidence to indicate change in the bedrock aquifers. Sampling of a well located in an area with little energy development but where faults or fractures could provide a path for the migration of fluids indicate mixing of groundwater between the upper and lower aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185142","collaboration":"Prepared in cooperation with the Bureau of Land Management, White River Field Office","usgsCitation":"Thomas, J.C., and McMahon, P.B., 2018, Groundwater chemistry and water-level elevations in bedrock aquifers of the Piceance and Yellow Creek watersheds, Rio Blanco County, Colorado, 2013–16: U.S. Geological Survey Scientific Investigations Report 2018–5142, 26 p., https://doi.org/10.3133/sir20185142.","productDescription":"v, 26 p.","onlineOnly":"Y","ipdsId":"IP-093390","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":359632,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5142/coverthb.jpg"},{"id":359633,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5142/sir20185142.pdf","text":"Report","size":"13.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5142"}],"country":"United States","state":"Colorado","county":"Rio Blanco County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.75,\n 39.5\n ],\n [\n -107.75,\n 39.5\n ],\n [\n -107.75,\n 40.25\n ],\n [\n -108.75,\n 40.25\n ],\n [\n -108.75,\n 39.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
Safe drinking water at the point-of-use (tapwater, TW) is a United States public health priority. Multiple lines of evidence were used to evaluate potential human health concerns of 482 organics and 19 inorganics in TW from 13 (7 public supply, 6 private well self-supply) home and 12 (public supply) workplace locations in 11 states. Only uranium (61.9 μg L–1, private well) exceeded a National Primary Drinking Water Regulation maximum contaminant level (MCL: 30 μg L–1). Lead was detected in 23 samples (MCL goal: zero). Seventy-five organics were detected at least once, with median detections of 5 and 17 compounds in self-supply and public supply samples, respectively (corresponding maxima: 12 and 29). Disinfection byproducts predominated in public supply samples, comprising 21% of all detected and 6 of the 10 most frequently detected. Chemicals designed to be bioactive (26 pesticides, 10 pharmaceuticals) comprised 48% of detected organics. Site-specific cumulative exposure–activity ratios (∑EAR) were calculated for the 36 detected organics with ToxCast data. Because these detections are fractional indicators of a largely uncharacterized contaminant space, ∑EAR in excess of 0.001 and 0.01 in 74 and 26% of public supply samples, respectively, provide an argument for prioritized assessment of cumulative effects to vulnerable populations from trace-level TW exposures.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.8b04622","usgsCitation":"Bradley, P.M., Kolpin, D.W., Romanok, K.M., Smalling, K.L., Focazio, M.J., Brown, J.B., Cardon, M.C., Carpenter, K.D., Corsi, S., DeCicco, L.A., Dietze, J.E., Evans, N., Furlong, E.T., Givens, C., Gray, J.L., Griffin, D.W., Higgins, C.P., Hladik, M., Iwanowicz, L., Journey, C.A., Kuivila, K., Masoner, J.R., McDonough, C.A., Meyer, M.T., Orlando, J.L., Strynar, M.J., Weis, C., and Wilson, V.S., 2018, Reconnaissance of mixed organic and inorganic chemicals in private and public supply tapwaters at selected residential and workplace sites in the United States: Environmental Science & Technology, v. 52, no. 23, p. 13972-13985, https://doi.org/10.1021/acs.est.8b04622.","productDescription":"14 p.","startPage":"13972","endPage":"13985","ipdsId":"IP-094503","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water 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efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753232,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Givens, Carrie E. 0000-0003-2543-9610","orcid":"https://orcid.org/0000-0003-2543-9610","contributorId":205657,"corporation":false,"usgs":true,"family":"Givens","given":"Carrie E.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753233,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Gray, James L. 0000-0002-0807-5635 jlgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":1253,"corporation":false,"usgs":true,"family":"Gray","given":"James","email":"jlgray@usgs.gov","middleInitial":"L.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":753234,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Griffin, Dale W. 0000-0003-1719-5812 dgriffin@usgs.gov","orcid":"https://orcid.org/0000-0003-1719-5812","contributorId":2178,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale","email":"dgriffin@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science 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","email":"liwanowicz@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":753238,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":753239,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Kuivila, Kathryn 0000-0001-7940-489X kkuivila@usgs.gov","orcid":"https://orcid.org/0000-0001-7940-489X","contributorId":1367,"corporation":false,"usgs":true,"family":"Kuivila","given":"Kathryn ","email":"kkuivila@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":753240,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753241,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"McDonough, Carrie A. 0000-0001-5152-8495","orcid":"https://orcid.org/0000-0001-5152-8495","contributorId":205664,"corporation":false,"usgs":false,"family":"McDonough","given":"Carrie","email":"","middleInitial":"A.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":753242,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Meyer, Michael T. 0000-0001-6006-7985 mmeyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":866,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael","email":"mmeyer@usgs.gov","middleInitial":"T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":753243,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Orlando, James L. 0000-0002-0099-7221 jorlando@usgs.gov","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":190788,"corporation":false,"usgs":true,"family":"Orlando","given":"James","email":"jorlando@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753244,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Strynar, Mark J. 0000-0003-3472-7921","orcid":"https://orcid.org/0000-0003-3472-7921","contributorId":205666,"corporation":false,"usgs":false,"family":"Strynar","given":"Mark","email":"","middleInitial":"J.","affiliations":[{"id":36773,"text":"USEPA NERL","active":true,"usgs":false}],"preferred":false,"id":753246,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Weis, Christopher P.","contributorId":210216,"corporation":false,"usgs":false,"family":"Weis","given":"Christopher P.","affiliations":[{"id":35644,"text":"National Institute of Health","active":true,"usgs":false}],"preferred":false,"id":753247,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Wilson, Vickie S. 0000-0003-1661-8481","orcid":"https://orcid.org/0000-0003-1661-8481","contributorId":184092,"corporation":false,"usgs":false,"family":"Wilson","given":"Vickie","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":753248,"contributorType":{"id":1,"text":"Authors"},"rank":28}]}} ,{"id":70200919,"text":"pp1824AA - 2018 - Geology and assessment of undiscovered oil and gas resources of the Long Strait Basin Province, 2008","interactions":[{"subject":{"id":70200919,"text":"pp1824AA - 2018 - Geology and assessment of undiscovered oil and gas resources of the Long Strait Basin Province, 2008","indexId":"pp1824AA","publicationYear":"2018","noYear":false,"chapter":"AA","displayTitle":"Geology and Assessment of Undiscovered Oil and Gas Resources of the Long Strait Basin Province, 2008","title":"Geology and assessment of undiscovered oil and gas resources of the Long Strait Basin Province, 2008"},"predicate":"IS_PART_OF","object":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"id":1}],"isPartOf":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"lastModifiedDate":"2024-06-26T14:29:35.392881","indexId":"pp1824AA","displayToPublicDate":"2018-11-20T13:39:41","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1824","chapter":"AA","displayTitle":"Geology and Assessment of Undiscovered Oil and Gas Resources of the Long Strait Basin Province, 2008","title":"Geology and assessment of undiscovered oil and gas resources of the Long Strait Basin Province, 2008","docAbstract":"The Long Strait Basin is both a stand alone petroleum province and an assessment unit (AU) that lies offshore in the East Siberian Sea north of Chukotka and south of Wrangel Island. This basin is known only on the basis of gravity data and a single proprietary seismic line. In the absence of more specific data, its position and regional setting suggest that it may have petroleum geologic characteristics similar to the nearby Hope Basin.
Because the geology and petroleum potential of the Long Strait Basin are so poorly known, only a single AU was defined for this study area. An overall probability of ~0.08 (8 percent) of at least one petroleum accumulation larger than 50 million barrels of oil equivalent was determined on the basis of estimated probabilities of the occurrence of petroleum source, adequate reservoir, trap and seal, and favorable timing. Because this probability falls below the 10 percent probability cutoff used in the U.S. Geological Survey’s Circum-Arctic Resource Appraisal, no quantitative assessment of sizes and numbers of petroleum accumulations was conducted for this AU.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824AA","usgsCitation":"Bird, K.J., Houseknecht, D.W., and Pitman, J.K., 2018, Geology and assessment of undiscovered oil and gas resources of the Long Strait Basin Province, 2008, chap. AA of Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 7 p., https://doi.org/10.3133/pp1824AA.","productDescription":"Report: vi, 7 p.; Appendix","onlineOnly":"Y","ipdsId":"IP-050996","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":359574,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/aa/pp1824aa_appendix1.xls","text":"Appendix 1","size":"45 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"PP 1824 Chapter AA Appendix 1","linkHelpText":"- Input Data for the Long Strait Basin Assessment Unit"},{"id":359571,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/aa/pp1824aa.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter AA"},{"id":359570,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/aa/coverthb.jpg"}],"otherGeospatial":"Long Strait Basin Province","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936
The U.S. Geological Survey collected continuous water-temperature data in select tributaries of the lowermost 80 kilometers (50 miles) of the Willamette River in northwestern Oregon, during summers 2016 and 2017. Point measurements of water temperature and water quality (dissolved oxygen, specific conductance, and pH) also were collected at multiple locations and depths within the river and in the lower reaches of three major tributaries (Clackamas and Molalla Rivers, and Johnson Creek). These datasets were collected to identify potential locations of cold-water refuges for sensitive fish species, and to characterize daily, seasonal, and spatial variability in water conditions. These datasets may be useful for local municipalities that are required to identify cold-water refuges (as defined in State of Oregon water-quality standards) and determine approaches for protecting and enhancing these features as part of their Willamette River water-temperature Total Maximum Daily Load implementation plans. This report documents the data collection methods, provides summary graphs and maps of the water-temperature data, and outlines steps for accessing the data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181184","collaboration":"Prepared in cooperation with the City of Lake Oswego, City of Wilsonville, Meyer Memorial Trust, and Benton Soil and Water Conservation District","usgsCitation":"Mangano, J.F., Piatt, D.R., Jones, K.L, and Rounds, S.A., 2018, Water temperature in tributaries, off-channel features, and main channel of the lower Willamette River, northwestern Oregon, summers 2016 and 2017: U.S. Geological Survey Open-File Report 2018-1184, 33 p., https://doi.org/10.3133/ofr20181184.","productDescription":"iv, 33 p.","onlineOnly":"Y","ipdsId":"IP-099746","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":359616,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1184/ofr20181184.pdf","text":"Report","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1184"},{"id":359615,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1184/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Lower Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.85736083984375,\n 45.268121280142886\n ],\n [\n -122.57995605468749,\n 45.268121280142886\n ],\n [\n -122.57995605468749,\n 45.66108710567762\n ],\n [\n -122.85736083984375,\n 45.66108710567762\n ],\n [\n -122.85736083984375,\n 45.268121280142886\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Remote-sensing-based maps of tidal marshes, both of their extents and carbon stocks, will play a key role in conducting greenhouse gas (GHG) inventories.
The U.N. Environment Programme World Conservation Monitoring Centre has produced a new Global Distribution of Salt Marsh dataset that estimates global salt marsh area at 5.5 Mha.
A Tier 1–2 GHG Inventory of U.S. Coastal Wetlands has been developed using the NOAA Coastal-Change Analysis Program Landsat-based land cover maps as a primary dataset.
180Successful mapping of tidal marsh biomass with optical satellite images provides opportunity to improve GHG Inventories.
Further work is needed to map tidal marsh salinity gradients, the extent of tidal vs. non-tidal marshes, methane emissions, and high-resolution elevation.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"A blue carbon primer: The state of coastal wetland carbon science, practice and policy","language":"English","publisher":"CRC Press","doi":"10.1201/9780429435362-14","usgsCitation":"Byrd, K.B., Mcowen, C., Weatherdon, L., Holmquist, J., and Crooks, S., 2018, Status of tidal marsh mapping for blue carbon inventories, chap. of A blue carbon primer: The state of coastal wetland carbon science, practice and policy, 17 p., https://doi.org/10.1201/9780429435362-14.","productDescription":"17 p.","ipdsId":"IP-079453","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":359982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c0a4357e4b0815414d2812e","contributors":{"authors":[{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":753197,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mcowen, Chris","contributorId":211096,"corporation":false,"usgs":false,"family":"Mcowen","given":"Chris","email":"","affiliations":[{"id":38181,"text":"U.N. Environment Programme World Conservation Monitoring Programme","active":true,"usgs":false}],"preferred":false,"id":753198,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weatherdon, Lauren","contributorId":211097,"corporation":false,"usgs":false,"family":"Weatherdon","given":"Lauren","affiliations":[{"id":38181,"text":"U.N. Environment Programme World Conservation Monitoring Programme","active":true,"usgs":false}],"preferred":false,"id":753199,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holmquist, James","contributorId":204126,"corporation":false,"usgs":false,"family":"Holmquist","given":"James","affiliations":[{"id":36858,"text":"Smithsonian","active":true,"usgs":false}],"preferred":false,"id":753200,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crooks, Stephen","contributorId":211098,"corporation":false,"usgs":false,"family":"Crooks","given":"Stephen","affiliations":[{"id":38182,"text":"Silvestrum Climate Associates","active":true,"usgs":false}],"preferred":false,"id":753201,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70201206,"text":"70201206 - 2018 - The effects of tropical cyclone-generated deposition on the sustainability of the Pearl River marsh, Louisiana: The importance of the geologic framework","interactions":[],"lastModifiedDate":"2025-05-14T13:38:56.767259","indexId":"70201206","displayToPublicDate":"2018-11-20T10:59:34","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"The effects of tropical cyclone-generated deposition on the sustainability of the Pearl River marsh, Louisiana: The importance of the geologic framework","docAbstract":"Shoreline retreat is a tremendously important issue along the coast of the northern Gulf of Mexico, especially in Louisiana. Although this marine transgression results from a variety of causes, the crucial factor is the difference between marsh surface elevation and rising sea levels. In most cases, the primary cause of a marsh's inability to keep up with sea level is the lack of input of inorganic material. Although tropical cyclones provide an important source of such sediment, little effort has been made to determine the point of origin of the deposited material. In this study we use sedimentary, geochemical and biogeochemical data to identify the bed of the Pearl River and/or Lake Borgne as the source of a ~5 cm thick clastic layer deposited on the surface of the Pearl River marsh on the Louisiana/Mississippi border. Radiochemical chronologies and sedimentary evidence indicate that this layer was associated with the passage of Hurricane Katrina in 2005. As this material would otherwise have been lost to the system, this deposition indicates a net gain to marsh surface elevation. Accretion rates, determined from 137Cs and 14C profiles and the use of the Katrina layer as a stratigraphic marker, indicate that short-term (~50 years) rates are as much as an order of magnitude higher than the long- term (1000s of years) rates. We suggest that the marsh's geologic setting in an incised river valley with steep vertical constraints and a large fluvial discharge, promotes rapid accretion rates, with rates accelerating as the sea moves inland, due to extended hydroperiods and the input of clastic material from both the marine and terrestrial sides. These rates are especially large when compared to accretion occurring in the more common open marshes fringing the Gulf that lack fluvial input. The difference is particularly large when related to marsh recovery/regrowth following the deposition of thick hurricane-generated clastic layers. Given the number of similar incised river valleys along the Gulf Coast, we believe that understanding the processes controlling marsh accretion in such environments is essential in evaluating marsh sustainability on a regional basis.
","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2018.00179","usgsCitation":"McCloskey, T.A., Smith, C.G., Liu, K., and Nelson, P.R., 2018, The effects of tropical cyclone-generated deposition on the sustainability of the Pearl River marsh, Louisiana: The importance of the geologic framework: Frontiers in Ecology and Evolution, v. 6, 179; 21 p.; Data Release, https://doi.org/10.3389/fevo.2018.00179.","productDescription":"179; 21 p.; Data Release","ipdsId":"IP-097886","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":359978,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":460808,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2018.00179","text":"Publisher Index Page"},{"id":437677,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y2R3LV","text":"USGS data release","linkHelpText":"Sedimentary data from the lower Pearl River, Louisiana, USA"}],"country":"United States","state":"Louisiana","otherGeospatial":"Pearl River Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.77133862607873,\n 30.180430652787265\n ],\n [\n -89.77133862607873,\n 29.961815885432074\n ],\n [\n -89.43518813692441,\n 29.961815885432074\n ],\n [\n -89.43518813692441,\n 30.180430652787265\n ],\n [\n -89.77133862607873,\n 30.180430652787265\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-20","publicationStatus":"PW","scienceBaseUri":"5c0a4357e4b0815414d28130","contributors":{"authors":[{"text":"McCloskey, Terrence A. 0000-0003-3979-3821 tmccloskey@usgs.gov","orcid":"https://orcid.org/0000-0003-3979-3821","contributorId":200684,"corporation":false,"usgs":true,"family":"McCloskey","given":"Terrence","email":"tmccloskey@usgs.gov","middleInitial":"A.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753218,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Kam-Biu","contributorId":209677,"corporation":false,"usgs":false,"family":"Liu","given":"Kam-Biu","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":753219,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Paul R.","contributorId":194023,"corporation":false,"usgs":false,"family":"Nelson","given":"Paul","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":753220,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203072,"text":"70203072 - 2018 - Energy-rich mesopelagic fishes revealed as a critical prey resource for a deep-diving predator using quantitative fatty acid signature analysis","interactions":[],"lastModifiedDate":"2019-04-17T10:05:12","indexId":"70203072","displayToPublicDate":"2018-11-20T10:04:52","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Energy-rich mesopelagic fishes revealed as a critical prey resource for a deep-diving predator using quantitative fatty acid signature analysis","docAbstract":"Understanding the diet of deep-diving predators can provide essential insight to the trophic structure of the mesopelagic ecosystem. Comprehensive population-level diet estimates are exceptionally difficult to obtain for elusive marine predators due to the logistical challenges involved in observing their feeding behavior and collecting samples for traditional stomach content or fecal analyses. We used quantitative fatty acid signature analysis (QFASA) to estimate the diet composition of a wide-ranging mesopelagic predator, the northern elephant seal (Mirounga angustirostris), across five years. To implement QFASA, we first compiled a library of prey fatty acid (FA) profiles from the mesopelagic eastern North Pacific. Given the scarcity of a priori diet data for northern elephant seals, our prey library was necessarily large to encompass the range of potential prey in their foraging habitat. However, statistical constraints limit the number of prey species that can be included in the prey library to the number of dietary FAs in the analysis. Exceeding that limit could produce non-unique diet estimates (i.e., multiple diet estimates fit the data equally well). Consequently, we developed a novel ad-hoc method to identify which prey were unlikely to contribute to diet and could, therefore, be excluded from the final QFASA model. The model results suggest that seals predominantly consumed small mesopelagic fishes, including myctophids (lanternfishes) and bathylagids (deep sea smelts), while non-migrating mesopelagic squids comprised a third of their diet, substantially less than suggested by previous studies. Our results revealed that mesopelagic fishes, particularly energy-rich myctophids, were a critical prey resource, refuting the long-held view that elephant seals are squid specialists.
","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2018.00430","usgsCitation":"Goetsch, C., Conners, M.G., Budge, S.M., Mitani, Y., Walker, W.A., Bromaghin, J.F., Simmons, S.E., Reichmuth, C., and Costa, D.P., 2018, Energy-rich mesopelagic fishes revealed as a critical prey resource for a deep-diving predator using quantitative fatty acid signature analysis: Frontiers in Marine Science, v. 5, no. 430, p. 1-19, https://doi.org/10.3389/fmars.2018.00430.","productDescription":"19 p.","startPage":"1","endPage":"19","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":468239,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2018.00430","text":"Publisher Index Page"},{"id":362999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"430","noUsgsAuthors":false,"publicationDate":"2018-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Goetsch, Chandra","contributorId":214868,"corporation":false,"usgs":false,"family":"Goetsch","given":"Chandra","email":"","affiliations":[],"preferred":false,"id":761039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conners, Melinda G. 0000-0003-0572-0026","orcid":"https://orcid.org/0000-0003-0572-0026","contributorId":214869,"corporation":false,"usgs":false,"family":"Conners","given":"Melinda","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":761040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Budge, Suzanne M.","contributorId":92168,"corporation":false,"usgs":false,"family":"Budge","given":"Suzanne","email":"","middleInitial":"M.","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":761041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mitani, Yoko","contributorId":214870,"corporation":false,"usgs":false,"family":"Mitani","given":"Yoko","email":"","affiliations":[],"preferred":false,"id":761042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walker, William A","contributorId":140360,"corporation":false,"usgs":false,"family":"Walker","given":"William","email":"","middleInitial":"A","affiliations":[{"id":13471,"text":"NMML","active":true,"usgs":false}],"preferred":false,"id":761043,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":761044,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Simmons, Samantha E.","contributorId":156320,"corporation":false,"usgs":false,"family":"Simmons","given":"Samantha","email":"","middleInitial":"E.","affiliations":[{"id":20313,"text":"Marine Mammal Commission","active":true,"usgs":false}],"preferred":false,"id":761045,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Reichmuth, Colleen","contributorId":214871,"corporation":false,"usgs":false,"family":"Reichmuth","given":"Colleen","email":"","affiliations":[],"preferred":false,"id":761046,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Costa, Daniel P.","contributorId":141212,"corporation":false,"usgs":false,"family":"Costa","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":761047,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70263620,"text":"70263620 - 2018 - Revisiting earthquakes in the Los Angeles, California, basin during the early instrumental period: Evidence for an association with oil production","interactions":[],"lastModifiedDate":"2025-02-18T16:17:04.256137","indexId":"70263620","displayToPublicDate":"2018-11-19T10:12:12","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Revisiting earthquakes in the Los Angeles, California, basin during the early instrumental period: Evidence for an association with oil production","docAbstract":"A total of seven independent ML ≥ 4.0 earthquakes occurred in the Los Angeles, California, basin, during the early instrumental period between 1932 and 1952, the largest of which was the 1933 Long Beach earthquake. Revising available macroseismic and instrumental data for a total of 6 4.0 ≤ ML ≤ 5.1 events between 1938 and 1944, we conclude that early instrumental locations can be grossly inconsistent with detailed macroseismic data. We use available macroseismic data to revisit event locations. We further present evidence that most if not all of these moderate earthquakes may have been induced by oil production. We quantify the predicted stress change associated with production from eight oil fields in the southwestern Los Angeles basin and show that frictional failure would have been encouraged beneath and at the periphery of high-volume fields, with stress changes upward of 0.1 MPa at 5-km depth. The results suggest that if earthquakes are induced by stress changes associated with production, the magnitudes of events might tend to be limited by the limited spatial extent of lobes of increased Coulomb failure stress. It further appears that the advent of fluid injection recovery methods (water-flooding) around 1960 mitigated induced earthquake risk considerably.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2017JB014616","usgsCitation":"Hough, S.E., and Bilham, R., 2018, Revisiting earthquakes in the Los Angeles, California, basin during the early instrumental period: Evidence for an association with oil production: JGR Solid Earth, v. 123, no. 12, p. 10684-10705, https://doi.org/10.1029/2017JB014616.","productDescription":"22 p.","startPage":"10684","endPage":"10705","ipdsId":"IP-088079","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":489939,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017jb014616","text":"Publisher Index Page"},{"id":482167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Los Angeles basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.6,\n 34\n ],\n [\n -118.6,\n 33.5\n ],\n [\n -118,\n 33.5\n ],\n [\n -118,\n 34\n ],\n [\n -118.6,\n 34\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"123","issue":"12","noUsgsAuthors":false,"publicationDate":"2018-12-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bilham, Roger","contributorId":225117,"corporation":false,"usgs":false,"family":"Bilham","given":"Roger","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":927595,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216308,"text":"70216308 - 2018 - Landscape drivers and social dynamics shaping microbial contamination risk in three Maya communities in southern Belize, Central America","interactions":[],"lastModifiedDate":"2020-11-11T14:31:12.681462","indexId":"70216308","displayToPublicDate":"2018-11-17T08:18:48","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Landscape drivers and social dynamics shaping microbial contamination risk in three Maya communities in southern Belize, Central America","docAbstract":"The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 11 projects funded in fiscal year 2017, outlining their goals, activities, and outputs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181154","usgsCitation":"Hsu, L., Allstadt, K.E., Bell, T.M., Boydston, E.E., Erickson, R.A., Everette, A.L., Lentz, E., Peters, J., Reichert, B.E., Nagorsen, S., Sherba, J.T., Signell, R.P., Wiltermuth, M.T., and Young, J.A., 2018, Community for Data Integration fiscal year 2017 funded project report: U.S. Geological Survey Open-File Report 2018–1154, 15 p., https://doi.org/10.3133/ofr20181154.","productDescription":"iv, 15 p.","onlineOnly":"Y","ipdsId":"IP-099013","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":359452,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1154/ofr20181154.pdf","text":"Report","size":"6.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1154"},{"id":359451,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1154/coverthb.jpg"}],"contact":"Director, Science Analytics and Synthesis
U.S. Geological Survey
108 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The geologic map of the northern half of the Lake Walcott 30ʹ×60ʹ quadrangle shows the volcanic geology of the southern part of the Craters of the Moon lava field, the complex geologic features of the Holocene Kings Bowl and Wapi lava fields, and the southern part of the Great Rift volcanic rift zone. The long extent and distribution of skylights in lava-tube systems of the Horse Butte and Wapi Park lava fields are depicted on this map. 40Ar/39Ar and K/Ar age determinations give detail to the Holocene, late Pleistocene, and late middle Pleistocene volcanic lava fields in this quadrangle. Most of the younger basalt eruptions (less than 150 thousand years [ka]) have occurred along the Great Rift volcanic rift zone, but two of the younger lava fields are located in the western part of the quadrangle. Kimama Butte, a shield volcano, is 87±11 ka, and Shale Butte is dated at 11±6 ka. Paleomagnetic studies have shown that the Horse Butte-Inferno Chasm eruptive fissure system has at least five paleomagnetic-correlative lava fields, the Claasen vent complex consists of at least seven correlative lava fields, and the Streifling-Flat Top vent complex includes at least four correlative lava fields.
This map provides geologic, geochronologic, and paleomagnetic data for Holocene lava fields along the southern part of the Great Rift, and for late Pleistocene and late middle Pleistocene lava fields in the central and western parts of the quadrangle. These data can contribute to wise management and preservation of the Craters of the Moon National Monument and for broad-scale understanding of the basaltic-volcanic evolution of the eastern Snake River Plain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3405","collaboration":"Prepared in cooperation with the National Park Service and the Bureau of Land Management","usgsCitation":"Kuntz, M.A., Champion, D.E., Turrin, B.R., Gans, P.B., Covington, H.R., and VanSistine, D.P., 2018, Geologic map of the north half of the Lake Walcott 30'×60' quadrangle, Idaho: U.S. Geological Survey Scientific Investigations Report 3405, pamphlet 25 p., scale 1:100,000, https://doi.org/10.3133/sim3405.","productDescription":"Report: v, 25 p.; Sheet: 49.75 x 34.00 inches; Read Me; Data Release","onlineOnly":"Y","ipdsId":"IP-084554","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":358860,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3405/sim3405_sheet_georeferenced.pdf","text":"Map","size":"75.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3405 Hillshaded Map"},{"id":358861,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3405/sim3405_Readme.txt","text":"Read Me","size":"8.00 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3405 Read Me"},{"id":358862,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VQ30VZ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data Release for Geologic Map of the north half of the Lake Walcott 30' x 60' Quadrangle, Idaho"},{"id":359523,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3405/sim3405_pamphlet.pdf","text":"Report","size":"5.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3405 Pamphlet"},{"id":358856,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3405/coverthb2.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114,\n 42.75\n ],\n [\n -113,\n 42.75\n ],\n [\n -113,\n 43\n ],\n [\n -114,\n 43\n ],\n [\n -114,\n 42.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
In 2016, the U.S. Geological Survey, in cooperation with the Ohio Water Development Authority, investigated the hydrogeologic setting, chemical and isotopic characteristics, and origin of methane in groundwater of Ohio. Understanding the occurrence and distribution of methane in groundwater is important in terms of public safety because methane in water wells can pose a risk of explosion. In addition, documenting the chemical and isotopic characteristics of methane in groundwater can make an important contribution to future stray gas investigations.
Water samples were collected from 15 domestic water wells known to produce methane, which were in 12 counties in diverse parts of Ohio. The wells were 75–345 feet deep and tapped a range of aquifer types, including glacial deposits and bedrock of Upper Ordovician, Upper Devonian, Lower Mississippian, and Pennsylvanian ages. Although the hydrogeologic settings were varied, there was a broad similarity among the well sites in that the bedrock was predominantly shale and the glacial deposits were predominantly clay.
The wells were sampled for dissolved inorganic constituents; dissolved organic carbon; methane and other dissolved gases; stable isotopes (carbon, hydrogen, and oxygen) of methane, water, and dissolved inorganic carbon; and carbon-14 of methane. Gas composition and stable isotopes of methane were used to differentiate thermogenic and microbial methane. The degree of fractionation of hydrogen and carbon isotopes was used to evaluate the pathway of microbial methanogenesis (carbon dioxide [CO2] reduction or acetate fermentation) and the effects of secondary processes such as oxidation, mixing, and migration. The concentration of carbon-14 of methane was used to evaluate the relative age of the carbon source.
The quality of water from the 15 wells differed greatly; water types ranged from CaMgHCO3 to NaCl, and total dissolved solids concentrations ranged from 318 to 2,940 milligrams per liter (mg/L). Methane concentrations ranged from 1.2 to 120 mg/L. Of the 15 samples, 12 had methane concentrations greater than 28 mg/L, the level that can pose a risk of explosion.
Of the 15 samples, 12 had chemical and isotopic characteristics or \"signatures\" consistent with microbial methane formed by CO2 reduction. CO2 reduction is commonly associated with microbial degradation of organic matter in anaerobic aquifers and with the formation of microbial shale gas and coalbed methane along margins of sedimentary basins. Two of 15 samples were interpreted as having a component of thermogenic methane based on the δ13C of methane (−50.96 and −47.74 parts per thousand [per mil]) and gas dryness (28 and 5). One of 15 samples (from the shallowest well) had chemical and isotopic characteristics consistent with methane oxidation by sulfate reduction based on light δ13C of dissolved inorganic carbon (−31.6 per mil) and evidence of sulfate reduction in terms of the odor and appearance of the water.
For the 12 samples interpreted as microbial methane formed by CO2 reduction, the δ13C of methane varied from −75 to −56 per mil. Multiple samples from the same aquifer demonstrated a general trend of increasing δ13C of methane with depth. Samples with lighter δ13C of methane (−75 to −62 per mil) were from shallower wells (or wells with shallow open intervals), and the isotopic signature of the water was consistent with modern or postglacial groundwater recharge. Three samples with heavier δ13C of methane (−61 to −56 per mil) were from deeper wells or more confined aquifers where the isotopic signature of water was consistent with older (glacial) recharge. In addition, δ13C of dissolved inorganic carbon was enriched (+12 to +18.9 per mil), and carbon-14 of methane was consistent with carbon associated with Paleozoic bedrock or older glacial deposits. These observations are generally consistent with increased Rayleigh-type fractionation at greater depths; however, other interpretations are possible. Isotopic signatures can be ambiguous, especially in areas with complex geologic histories that include multiple episodes of migration, mixing, and (or) oxidation.
Many of the wells were in proximity to multiple potential natural and anthropogenic pathways of methane migration; however, it is not possible to determine if the methane in any of the wells is related to human activities based on the chemical and isotopic data collected for this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185097","collaboration":"Prepared in cooperation with the Ohio Water Development Authority","usgsCitation":"Thomas, M.A., 2018, Chemical and isotopic characteristics of methane in groundwater of Ohio, 2016: U.S. Geological Survey Scientific Investigations Report 2018–5097, 42 p., https://doi.org/10.3133/sir20185097.","productDescription":"vi, 42 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-095132","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":359469,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5097/sir20185097.pdf","text":"Report","size":"4.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5097"},{"id":359468,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5097/coverthb2.jpg"}],"country":"United 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\"}}]}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Boulevard Ste. 100
Columbus, OH 43229-1737
Deterministic dynamical modeling of future climate conditions and associated hazards, such as flooding, can be computationally-expensive if century-long time-series of waves, sea level variations, and overland flow patterns are simulated. To alleviate some of the computational costs, local impacts of individual coastal storms can be explored by first identifying particular events or scenarios of interest and dynamically modeling those events in detail. In this study, an efficient approach to selecting storm events for subsequent deterministic detailed modeling of coastal flooding is presented. The approach identifies locally relevant scenarios derived from regional datasets spanning long time-periods and covering large geographic areas. This is done by identifying storm events from global climate models using a robust, yet computationally simple approach for calculating total water level proxies at the shore, assuming a linear superposition of the important processes contributing to the overall total water level. Clustering of the total water level time-series is used to define coherent coastal cells where similar return period water level extrema occur in response to region-wide storms. Results show that the more severe but rare coastal flood events (e.g., the 100-year (yr) event) typically occur from the same storm across the region, but that a number of different storms are responsible for the less severe but more frequent local extreme water levels (e.g., the 1-yr event). This new ‘storm selection’ approach is applied to the Southern California Bight, a region of varying shoreline orientations that is subject to wave refraction across complex bathymetry, and shadowing, focusing, diffraction, and dissipation of wave energy by islands. Results indicate that wave runup dominates total water level extremes at this study site, highlighting the importance of downscaling global-scale models to nearshore waves when seeking accurate projections of local coastal hazards in response to climate change.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2018.08.003","usgsCitation":"Erikson, L.H., Espejo, A., Barnard, P., Katherine A. Serafin, Hegermiller, C., O'Neill, A., Ruggerio, P., Limber, P.W., and Mendez, F.J., 2018, Identification of storm events and contiguous coastal sections for deterministic modeling of extreme coastal flood events in response to climate change: Coastal Engineering, v. 140, p. 316-330, https://doi.org/10.1016/j.coastaleng.2018.08.003.","productDescription":"15 p.","startPage":"316","endPage":"330","ipdsId":"IP-077289","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468243,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.coastaleng.2018.08.003","text":"External Repository"},{"id":366001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Southern California Bight","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.2451171875,\n 32.63937487360669\n ],\n [\n -116.5869140625,\n 32.63937487360669\n ],\n [\n -116.5869140625,\n 35.10193405724606\n ],\n [\n -121.2451171875,\n 35.10193405724606\n ],\n [\n -121.2451171875,\n 32.63937487360669\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"140","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":767253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Espejo, Antonio","contributorId":217673,"corporation":false,"usgs":false,"family":"Espejo","given":"Antonio","email":"","affiliations":[],"preferred":false,"id":767254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":767255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Katherine A. Serafin","contributorId":187534,"corporation":false,"usgs":false,"family":"Katherine A. Serafin","affiliations":[],"preferred":false,"id":767256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hegermiller, Christie 0000-0002-6383-7508 chegermiller@usgs.gov","orcid":"https://orcid.org/0000-0002-6383-7508","contributorId":149010,"corporation":false,"usgs":true,"family":"Hegermiller","given":"Christie","email":"chegermiller@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":767257,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O'Neill, Andrea C. 0000-0003-1656-4372 aoneill@usgs.gov","orcid":"https://orcid.org/0000-0003-1656-4372","contributorId":5351,"corporation":false,"usgs":true,"family":"O'Neill","given":"Andrea C.","email":"aoneill@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":767258,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ruggerio, Peter","contributorId":67403,"corporation":false,"usgs":true,"family":"Ruggerio","given":"Peter","email":"","affiliations":[],"preferred":false,"id":767259,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Limber, Patrick W. 0000-0002-8207-3750 plimber@usgs.gov","orcid":"https://orcid.org/0000-0002-8207-3750","contributorId":196794,"corporation":false,"usgs":true,"family":"Limber","given":"Patrick","email":"plimber@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":767260,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mendez, Fernando J.","contributorId":140322,"corporation":false,"usgs":false,"family":"Mendez","given":"Fernando","email":"","middleInitial":"J.","affiliations":[{"id":13456,"text":"IH Cantrabria","active":true,"usgs":false}],"preferred":false,"id":767261,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70200699,"text":"70200699 - 2018 - Subsurface controls on the development of the Cape Fear Slide Complex, central US Atlantic Margin","interactions":[],"lastModifiedDate":"2019-10-09T08:37:04","indexId":"70200699","displayToPublicDate":"2018-11-16T13:02:32","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5011,"text":"Geological Society of London Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"Subsurface controls on the development of the Cape Fear Slide Complex, central US Atlantic Margin","docAbstract":"The Cape Fear Slide is one of the largest (>25 000 km3) submarine slope failure complexes on the US Atlantic margin. Here we use a combination of new high-resolution multichannel seismic data (MCS) from the National Science Foundation Geodynamic Processes at Rifting and Subducting Margins (NSF GeoPRISMS) Community Seismic Experiment and legacy industry MCS to derive detailed stratigraphy of this slide and constrain the conditions that lead to slope instability. Limited outer-shelf and upper-slope accommodation space during the Neogene, combined with lowstand fluvial inputs and northwards Gulf Stream sediment transport, appears to have contributed to thick Miocene and Pliocene deposits that onlapped the lower slope. This resulted in burial of an upper-slope bypass zone developed from earlier erosional truncation of Paleogene strata. These deposits created a broad ramp that allowed accumulation of thick Quaternary strata across a low-gradient (<3.5°) upper slope. Upslope of one of the larger headwalls, undulating Quaternary strata appear to downlap onto a buried failure plane. Many of the nested headwalls of the upper-slope portion of slide complex are underlain by deformed strata, which may be the result of fluid migration associated with localized subsidence from salt migration. These new data and observations suggest that antecedent margin physiography, sediment loading and substrate fluid flow were key factors in preconditioning the Cape Fear slope for failure.
","language":"English","publisher":"Geological Society of London","doi":"10.1144/SP477.17","usgsCitation":"Hill, J.C., Brothers, D., Hornbach, M.J., Sawyer, D.E., Shillington, D.J., and Becel, A., 2018, Subsurface controls on the development of the Cape Fear Slide Complex, central US Atlantic Margin: Geological Society of London Special Publications, v. 477, p. 169-182, https://doi.org/10.1144/SP477.17.","productDescription":"14 p.","startPage":"169","endPage":"182","ipdsId":"IP-089531","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":359515,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"477","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-28","publicationStatus":"PW","scienceBaseUri":"5befe5bae4b045bfcadf7f2a","contributors":{"authors":[{"text":"Hill, Jenna C. 0000-0002-7475-357X","orcid":"https://orcid.org/0000-0002-7475-357X","contributorId":21987,"corporation":false,"usgs":true,"family":"Hill","given":"Jenna","email":"","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":750155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Daniel S. 0000-0001-7702-157X","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":210199,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":750156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hornbach, Matthew J.","contributorId":210200,"corporation":false,"usgs":false,"family":"Hornbach","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":750157,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sawyer, Derek E.","contributorId":210201,"corporation":false,"usgs":false,"family":"Sawyer","given":"Derek","email":"","middleInitial":"E.","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":750158,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shillington, Donna J.","contributorId":210202,"corporation":false,"usgs":false,"family":"Shillington","given":"Donna","email":"","middleInitial":"J.","affiliations":[{"id":38091,"text":"Lamont Doherty Earth Observatory, Columbia University","active":true,"usgs":false}],"preferred":false,"id":750159,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Becel, Anne","contributorId":210203,"corporation":false,"usgs":false,"family":"Becel","given":"Anne","email":"","affiliations":[{"id":38091,"text":"Lamont Doherty Earth Observatory, Columbia University","active":true,"usgs":false}],"preferred":false,"id":750160,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70200934,"text":"70200934 - 2018 - The influence of seep habitats on sediment macrofaunal biodiversity and functional traits","interactions":[],"lastModifiedDate":"2018-12-05T14:05:19","indexId":"70200934","displayToPublicDate":"2018-11-16T11:21:28","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1370,"text":"Deep-Sea Research Part I: Oceanographic Research Papers","active":true,"publicationSubtype":{"id":10}},"title":"The influence of seep habitats on sediment macrofaunal biodiversity and functional traits","docAbstract":"Chemosynthetic ecosystems in the Gulf of Mexico (GOM) support dense communities of seep megafaunal invertebrates that rely on endosymbiotic bacteria for nutrition. Distinct infaunal communities are associated with the biogenic habitats created by seep biota, where habitat heterogeneity and sediment geochemistry influence local macrofaunal community structure. Here we examine the community structure and function of seep infaunal communities in the GOM in relation to environmental drivers and estimated proximity to seeps. We modeled seep distribution within 3 major seep fields (AC601, GC852, and AT340), and examined the influence of proximity to seep and associated sediment environment on infaunal community structure and function. To model seep habitat distribution, we used known seep occurrence data from ROV and towed camera images, terrain variables derived from high resolution multibeam bathymetry (gridded to 3 m resolution), and a maximum entropy (Maxent) approach. Model performance was high, with mean area under the curve for each habitat ranging from 0.851 for mussel to 0.908 for tubeworm habitat, with the models highly influenced by terrain rugosity. Replicate sediment cores were collected from the three sites in 2007 and processed for macrofauna and environmental characteristics. A majority of the taxa (86%) occurred within 16 m of modeled seep habitat and increased distance from modeled seeps was generally associated with lower calculated seep index coupled with decreased macrofaunal densities. Distance-based linear regression indicated that patterns in macrofaunal communities were driven by proximity to modeled seep habitat and profile curvature, a metric for the shape of the maximum slope. Similarly, variance in infaunal functional traits was best explained by proximity to seep, but also sediment C:N, reflecting the relative influence of sediment chemistry, including organic content, on infaunal communities. Results suggest that northern GOM seep infaunal community assemblages and their function are structured by factors that influence food availability and habitat heterogeneity. Given the abundance of seeps in the GOM and in the world’s oceans, this study supports the premise that the sphere of influence of seeps is spatially extensive.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr.2018.10.004","usgsCitation":"Demopoulos, A.W., Bourque, J.R., Durkin, A., and Cordes, E.E., 2018, The influence of seep habitats on sediment macrofaunal biodiversity and functional traits: Deep-Sea Research Part I: Oceanographic Research Papers, v. 142, p. 77-93, https://doi.org/10.1016/j.dsr.2018.10.004.","productDescription":"17 p.","startPage":"77","endPage":"93","ipdsId":"IP-092914","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468244,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.dsr.2018.10.004","text":"Publisher Index Page"},{"id":437683,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FB524M","text":"USGS data release","linkHelpText":"The influence of hydrocarbon seeps on sediment macrofaunal biodiversity and functional traits"},{"id":359513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","volume":"142","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5befe5bae4b045bfcadf7f2c","contributors":{"authors":[{"text":"Demopoulos, Amanda W. J. 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":206536,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"","middleInitial":"W. J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":751380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bourque, Jill R. 0000-0003-3809-2601 jbourque@usgs.gov","orcid":"https://orcid.org/0000-0003-3809-2601","contributorId":5452,"corporation":false,"usgs":true,"family":"Bourque","given":"Jill","email":"jbourque@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":751381,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Durkin, Alanna","contributorId":210654,"corporation":false,"usgs":false,"family":"Durkin","given":"Alanna","email":"","affiliations":[{"id":12547,"text":"Temple University","active":true,"usgs":false}],"preferred":false,"id":751382,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cordes, Erik E.","contributorId":37623,"corporation":false,"usgs":false,"family":"Cordes","given":"Erik","email":"","middleInitial":"E.","affiliations":[{"id":16710,"text":"Temple University, Department of Biology","active":true,"usgs":false}],"preferred":false,"id":751383,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204947,"text":"70204947 - 2018 - Integrated observations and informatics improve understanding of changing marine ecosystems","interactions":[],"lastModifiedDate":"2019-08-26T10:55:19","indexId":"70204947","displayToPublicDate":"2018-11-16T10:45:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Integrated observations and informatics improve understanding of changing marine ecosystems","docAbstract":"Marine ecosystems have numerous benefits for human societies around the world and many policy initiatives now seek to maintain the health of these ecosystems. To enable wise decisions, up to date and accurate information on marine species and the state of the environment they live in is required. Moreover, this information needs to be openly accessible to build indicators and conduct timely assessments that decision makers can use. The questions and problems being addressed demand global-scale investigations, transdisciplinary science, and mechanisms to integrate and distribute data that otherwise would appear to be disparate. Essential Ocean Variables (EOVs) and marine Essential Biodiversity Variables (EBVs), conceptualized by the Global Ocean Observing System (GOOS) and the Marine Biodiversity Observation Network (MBON), respectively, guide observation of the ocean. Additionally, significant progress has been made to coordinate efforts between existing programs, such as the GOOS, MBON, and Ocean Biogeographic Information System collaboration agreement. Globally and nationally relevant indicators and assessments require increased sharing of data and analytical methods, sustained long-term and large-scale observations, and resources to dedicated to these tasks. We propose a vision and key tenets as a guiding framework for building a global integrated system for understanding marine biological diversity and processes to address policy and resource management needs. This framework includes: using EOVs and EBVs and implementing the guiding principles of Findable, Accessible, Interoperable, Reusable (FAIR) data and action ecology. In doing so, we can encourage relevant, rapid, and integrative scientific advancement that can be implemented by decision makers to maintain marine ecosystem health.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2018.00428","usgsCitation":"Benson, A.L., Brooks, C.M., Canonico, G., Duffy, J.E., Muller-Karger, F., Sosik, H.M., Miloslavich, P., and Klein, E., 2018, Integrated observations and informatics improve understanding of changing marine ecosystems: Frontiers in Marine Science, v. 5, 428, 8 p., https://doi.org/10.3389/fmars.2018.00428.","productDescription":"428, 8 p.","ipdsId":"IP-100471","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":468245,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2018.00428","text":"Publisher Index Page"},{"id":366906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2018-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Abigail L. 0000-0002-4391-107X albenson@usgs.gov","orcid":"https://orcid.org/0000-0002-4391-107X","contributorId":4562,"corporation":false,"usgs":true,"family":"Benson","given":"Abigail","email":"albenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":769213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, Cassandra M.","contributorId":218423,"corporation":false,"usgs":false,"family":"Brooks","given":"Cassandra","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":769214,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Canonico, Gabrielle","contributorId":217563,"corporation":false,"usgs":false,"family":"Canonico","given":"Gabrielle","email":"","affiliations":[{"id":39659,"text":"National Oceanographic and Atmospheric Administration, US Integrated Ocean Observing System, Silver Spring, MD, USA","active":true,"usgs":false}],"preferred":false,"id":769215,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duffy, J. Emmett","contributorId":78186,"corporation":false,"usgs":true,"family":"Duffy","given":"J.","email":"","middleInitial":"Emmett","affiliations":[],"preferred":false,"id":769216,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Muller-Karger, Frank","contributorId":218424,"corporation":false,"usgs":false,"family":"Muller-Karger","given":"Frank","affiliations":[],"preferred":false,"id":769217,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sosik, Heidi M.","contributorId":218425,"corporation":false,"usgs":false,"family":"Sosik","given":"Heidi","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":769218,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miloslavich, Patricia","contributorId":206627,"corporation":false,"usgs":false,"family":"Miloslavich","given":"Patricia","email":"","affiliations":[{"id":37357,"text":"University of Tasmania, Hobart, Tasmania, Australia","active":true,"usgs":false}],"preferred":false,"id":769219,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Klein, Eduardo","contributorId":206675,"corporation":false,"usgs":false,"family":"Klein","given":"Eduardo","email":"","affiliations":[],"preferred":false,"id":769220,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202341,"text":"70202341 - 2018 - Do we know how much fluvial sediment reaches the sea? Decreased river monitoring of U.S. coastal rivers","interactions":[],"lastModifiedDate":"2019-02-22T16:53:40","indexId":"70202341","displayToPublicDate":"2018-11-15T16:53:35","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Do we know how much fluvial sediment reaches the sea? Decreased river monitoring of U.S. coastal rivers","docAbstract":"Given the present and future changing climate and human changes to land use and river control, river sediment fluxes to coastal systems are changing and will continue to change in the future. To delineate these changes and their effects, it is increasingly important to document the fluxes of river-borne sediment discharged to the sea. Unfortunately, broad-scale river sediment monitoring programs established more than 50 years ago in the U.S. have diminished substantially and now focus principally on the largest rivers and estuaries. Unless addressed, these data gaps will provide significant challenges in addressing fundamental scientific and management questions about the effects of climate change and sea-level rise in our estuaries and on our coasts.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13276","usgsCitation":"Warrick, J.A., and Milliman, J.D., 2018, Do we know how much fluvial sediment reaches the sea? Decreased river monitoring of U.S. coastal rivers: Hydrological Processes, v. 32, no. 23, p. 3561-3567, https://doi.org/10.1002/hyp.13276.","productDescription":"7 p.","startPage":"3561","endPage":"3567","ipdsId":"IP-092050","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468247,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.13276","text":"Publisher Index Page"},{"id":361482,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"23","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milliman, John D.","contributorId":213518,"corporation":false,"usgs":false,"family":"Milliman","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":38770,"text":"College of William and Mary, Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":757912,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70200816,"text":"fs20183061 - 2018 - Unmanned aerial systems capabilities of the U.S. Geological Survey Woods Hole Coastal and Marine Science Center","interactions":[],"lastModifiedDate":"2018-11-20T11:18:54","indexId":"fs20183061","displayToPublicDate":"2018-11-15T14:30:00","publicationYear":"2018","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":"2018-3061","displayTitle":"Unmanned Aerial Systems Capabilities of the U.S. Geological Survey Woods Hole Coastal and Marine Science Center","title":"Unmanned aerial systems capabilities of the U.S. Geological Survey Woods Hole Coastal and Marine Science Center","docAbstract":"Unmanned aerial system (UAS) technology provides a rapid and low-cost solution for mapping coastal environments and assessing short- and long-term changes. The interdisciplinary nature of the data collected and the breadth of applications make UAS technology applicable to multiple scientific investigations. The Aerial Imaging and Mapping (AIM) group at the U.S. Geological Survey (USGS) Woods Hole Coastal and Marine Science Center provides UAS services to scientists to advance the science mission of the Coastal-Marine Hazards and Resources Program. Scientists at the Woods Hole Coastal and Marine Science Center use UASs to acquire imagery of coastal and wetland environments, which is then used to produce detailed topographic and visual reflectance datasets. UAS technology supports the work of geologists, engineers, physical scientists, geographers, and geochemists who study coastal erosion, sediment transport, storm impacts, habitats, biomass, and marsh stability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183061","usgsCitation":"Brosnahan, S., and Sherwood, C., 2018, Unmanned aerial systems capabilities of the U.S. Geological Survey Woods Hole Coastal and Marine Science Center: U.S. Geological Survey Fact Sheet 2018–3061, 2 p., https://doi.org/10.3133/fs20183061.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-098218","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":359425,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3061/fs20183061.pdf","text":"Report","size":"926 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3061"},{"id":359424,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3061/coverthb.jpg"}],"contact":"Woods Hole Coastal and Marine Science Center
Aerial Imaging and Mapping Group
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384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
To improve flood-frequency estimates at rural streams in Mississippi, annual exceedance probability flows at gaged streams and regional regression equations used to estimate annual exceedance probability flows for ungaged streams were developed by using current geospatial data, new analytical methods, and annual peak-flow data through the 2013 water year. The regional regression equations were derived from statistical analyses of peak-flow data and basin characteristics for 281 streamgages and incorporated a newly developed study-specific skew coefficient at streamgages located in five subregional watersheds (Middle Tennessee-Elk, Mobile-Tombigbee, Lower Mississippi-Big Black, Pearl, and Pascagoula) in Mississippi. Three flood regions—A, B, and C—were identified based on residuals from the regional regression analyses and contain sites with similar basin characteristics. Analysis was not conducted for the fourth flood region, the Mississippi Alluvial Plain, because of insufficient long-term streamflow data and poorly defined basin characteristics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185148","collaboration":"Prepared in cooperation with the Mississippi Department of Transportation","usgsCitation":"Anderson, B.T., 2018, Flood frequency of rural streams in Mississippi, 2013: U.S. Geological Survey Scientific Investigations Report 2018–5148, 12 p., https://doi.org/10.3133/sir20185148. 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U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, Tennessee 37211
Forest ecosystems will face direct and indirect impacts from a changing climate over the 21st century. This assessment evaluates the vulnerability of forest ecosystems across the New England region (Connecticut, Maine, Massachusetts, New Hampshire, northern New York, Rhode Island, and Vermont) under a range of future climates. We synthesized and summarized information on the contemporary landscape, provided information on past climate trends, and described a range of projected future climates. This information was used to parameterize and run multiple vegetation impact models, which provided a range of potential vegetative responses to climate. Finally, we brought these results before a multidisciplinary panel of scientists and natural resource professionals familiar with the forests of this region to assess ecosystem vulnerability through a formal consensus-based expert elicitation process. Observed trends in climate over the historical record from 1901 through 2011 show that the mean annual temperature has increased across the region by 2.4 °F, with even greater warming during winter. Precipitation patterns also changed during this time, with a slight trend toward greater annual precipitation and a substantial increase in extreme precipitation events. Projected climate trends using downscaled global climate model data indicate a potential increase in mean annual temperature of 3 to 8 °F for the assessment area by 2100. Projections for precipitation indicate an increase in fall and winter precipitation, and spring and summer precipitation projections vary by scenario. We identified potential impacts on forests by incorporating these future climate projections into three forest impact models (DISTRIB, LINKAGES, and LANDIS PRO). Model projections suggest that many northern and boreal species, including balsam fir, red spruce, and black spruce, may fare worse under future conditions, but other species may benefit from projected changes in climate. Published literature on climate impacts related to wildfire, invasive species, and forest pests and diseases also contributed to the overall determination of climate change vulnerability. We assessed vulnerability for eight forest communities in the assessment area. The assessment was conducted through a formal elicitation process with 20 scientists and resource managers from across the area, who considered vulnerability in terms of the potential impacts and the adaptive capacity for an individual community. Montane spruce-fir, low-elevation spruce-fir, and lowland mixed conifer forests were determined to be the most vulnerable communities. Central hardwoods, transition hardwoods, and pitch pine-scrub oak forests were perceived as having lower vulnerability to projected changes in climate. These projected changes in climate and the associated impacts and vulnerabilities will have important implications for economically valuable timber species, forest-dependent animals and plants, recreation, and long-term natural resource planning.
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While home range data for juvenile sea turtles exists, few studies have examined spatial overlap of multiple species in foraging habitat. Using satellite tracking technology, we define home ranges for juveniles of 3 sea turtle species (loggerhead, Kemp’s ridley, and green; n = 21) captured at 2 adjacent foraging sites in the northern Gulf of Mexico. In these areas, green turtles are known to be primarily herbivorous, whereas Kemp’s ridley turtles forage predominately on crabs, and loggerhead turtles on various hard-shelled benthic invertebrates. No differences in home range size or characteristics, such as water depth and distance to shore, were observed among species, although fine-scale foraging patches were not examined in this study. A high degree of overlap in habitat-use among all 3 species was documented in summer at both sites. Seasonal movements, triggered by colder winter temperatures, were documented and appeared to differ among species, with Kemp’s ridley and loggerhead turtles leaving bays, and green turtles overwintering inside bays. By identifying shared habitat-use by juvenile sea turtles, we have created a foundation for further fine-scale studies on resource partitioning that will aid in habitat management and conservation of these threatened and endangered species.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps12748","usgsCitation":"Lamont, M.M., and Iverson, A., 2018, Shared habitat use by juveniles of three sea turtle species: Marine Ecology Progress Series, v. 606, p. 187-200, https://doi.org/10.3354/meps12748.","productDescription":"14 p.","startPage":"187","endPage":"200","ipdsId":"IP-098002","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":360185,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"606","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c122c55e4b034bf6a8569df","contributors":{"authors":[{"text":"Lamont, Margaret M. 0000-0001-7520-6669 mlamont@usgs.gov","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":4525,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"mlamont@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":753832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iverson, Autumn R. 0000-0002-8353-6745","orcid":"https://orcid.org/0000-0002-8353-6745","contributorId":173555,"corporation":false,"usgs":false,"family":"Iverson","given":"Autumn R.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":753833,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70200902,"text":"70200902 - 2018 - Two-event lode-ore deposition at Butte, USA: 40Ar/39Ar and U-Pb documentation of Ag-Au-polymetallic lodes overprinted by younger stockwork Cu-Mo ores and penecontemporaneous Cu lodes","interactions":[],"lastModifiedDate":"2018-11-14T15:13:05","indexId":"70200902","displayToPublicDate":"2018-11-14T15:12:47","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Two-event lode-ore deposition at Butte, USA: 40Ar/39Ar and U-Pb documentation of Ag-Au-polymetallic lodes overprinted by younger stockwork Cu-Mo ores and penecontemporaneous Cu lodes","docAbstract":"The ore-genesis model for world-class deposits of the Butte mining district, Montana, USA, is deep pre-Main Stage porphyry Cu-Mo and overlying Main Stage Ag-Zn-Cu zoned-lode deposits, both of which formed from hydrothermal fluids driven by minor volumes of rhyolitic magma. The lode-specific model is that hydrothermal processes diminished in intensity outward from district center along lode veins, synchronously forming metal zones. The accepted models are controverted by new geologic and multi-method geochronologic studies.
The new data reveal the following sequence of events: (1) Thermal study of country rock indicates that the 76.9-Ma Butte Granite cooled to 350–400 °C by 4 m.y. after emplacement. (2) Five quartz porphyry rhyolite dikes were emplaced at 67–65 Ma and another at 60 Ma (SHRIMP U-Pb) into the cooled Butte Granite without resetting 40Ar/39Ar ages in country rock. (3) Fifty-eight white mica and K-feldspar samples from alteration envelopes adjacent to Ag-Au-polymetallic lodes in outer parts of the district, Zn-rich lodes in intermediate parts, and Cu-rich lodes in the district center yield 40Ar/39Ar ages of 73–70 Ma for Ag-rich lodes, 65–64 Ma for Cu-rich lodes, and complex age spectra of 69–65 Ma for Zn-rich lodes.
The data show that Ag-Au-polymetallic lodes occupied cross-district fractures by about 73 Ma, forming the greater Butte mining district. At 67–65 Ma, minor quartz porphyry dikes were emplaced into central and eastern parts of the rejuvenated fracture system but without evidence of related cupola or volcanic rocks or of thermal disturbance in the country rock. At 64.5 Ma, overlapping hydrothermal cells formed two stockwork Cu-Mo domes in deep parts of the fracture system. At 65–64 Ma and closely related to late-stage stockwork Cu-Mo activity, a penecontemporaneous hydrothermal pulse formed a high-sulfidation hydrothermal plume that (1) utilized the large re-opened fractures to cannibalize and remobilize Cu from autologous, stockwork, and older Ag-Au-polymetallic lodes, (2) deposited the rich, high-sulfidation Cu lodes, and (3) mobilized metals from early Ag-Au-polymetallic veins in middle parts of the district, transported the metals outward and redeposited them, enriching early veins, especially in the intermediate Zn plus Cu areas.
Metals zones in lodes of the Butte district are the result of an intensely focused, Cu-rich hydrothermal plume that variably reworked the center of significantly larger, 10 m.y. older, Ag-Au-polymetallic lodes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2018.05.018","usgsCitation":"Lund, K., McAleer, R., Aleinikoff, J.N., Cosca, M.A., and Kunk, M.J., 2018, Two-event lode-ore deposition at Butte, USA: 40Ar/39Ar and U-Pb documentation of Ag-Au-polymetallic lodes overprinted by younger stockwork Cu-Mo ores and penecontemporaneous Cu lodes: Ore Geology Reviews, v. 102, p. 666-700, https://doi.org/10.1016/j.oregeorev.2018.05.018.","productDescription":"35 p.","startPage":"666","endPage":"700","ipdsId":"IP-087572","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":359430,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","city":"Butte","volume":"102","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bed4270e4b0b3fc5cf91c70","contributors":{"authors":[{"text":"Lund, Karen 0000-0002-4249-3582 klund@usgs.gov","orcid":"https://orcid.org/0000-0002-4249-3582","contributorId":1235,"corporation":false,"usgs":true,"family":"Lund","given":"Karen","email":"klund@usgs.gov","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":5301,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan J.","email":"rmcaleer@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":751254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aleinikoff, John N. 0000-0003-3494-6841 jaleinikoff@usgs.gov","orcid":"https://orcid.org/0000-0003-3494-6841","contributorId":1478,"corporation":false,"usgs":true,"family":"Aleinikoff","given":"John","email":"jaleinikoff@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cosca, Michael A. 0000-0002-0600-7663 mcosca@usgs.gov","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":1000,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","email":"mcosca@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":751256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kunk, Michael J. 0000-0003-4424-7825 mkunk@usgs.gov","orcid":"https://orcid.org/0000-0003-4424-7825","contributorId":200968,"corporation":false,"usgs":true,"family":"Kunk","given":"Michael","email":"mkunk@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":751257,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200903,"text":"70200903 - 2018 - Multi-scale effects of land cover and urbanization on the habitat suitability of an endangered toad","interactions":[],"lastModifiedDate":"2018-11-14T15:08:37","indexId":"70200903","displayToPublicDate":"2018-11-14T15:08:33","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale effects of land cover and urbanization on the habitat suitability of an endangered toad","docAbstract":"Habitat degradation, entwined with land cover change, is a major driver of biodiversity loss. Effects of land cover change on species can be direct (when habitat is converted to alternative land cover types) or indirect (when land outside of the species habitat is altered). Hydrologic and ecological connections between terrestrial and aquatic systems are well understood, exemplifying how spatially disparate land cover conditions may influence aquatic habitats, but are rarely examined. We sought to quantify relative effects of land cover at two different but interacting scales on habitat suitability for the endangered arroyo toad (Anaxyrus californicus). Based on an existing distribution model for the arroyo toad and available land cover data, we estimated effects of land cover along streams and within entire watersheds on habitat suitability using structural equation modeling. Relationships between land cover and habitat suitability differed between scales, and broader, watershed-scale conditions influenced land cover along the embedded stream networks. We found anthropogenic development and forest cover at the watershed-scale negatively impacted habitat suitability, but development along stream networks was positively associated with suitability. The positive association between development along streams and habitat suitability may be attributable to increased spatial heterogeneity along urbanized streams, or related factors including policies designed to conserve riparian habitats amidst development. These findings show arroyo toad habitat is influenced by land cover across multiple scales, and can inform conservation of the species. Furthermore, our methodology can help elucidate similar dynamics with other taxa, particularly those reliant on both terrestrial and aquatic environments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.10.032","usgsCitation":"Treglia, M.L., Landon, A.C., Fisher, R.N., Kyle, G., and Fitzgerald, L.A., 2018, Multi-scale effects of land cover and urbanization on the habitat suitability of an endangered toad: Biological Conservation, v. 228, p. 310-318, https://doi.org/10.1016/j.biocon.2018.10.032.","productDescription":"9 p.","startPage":"310","endPage":"318","ipdsId":"IP-094043","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":359429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"228","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bed4270e4b0b3fc5cf91c72","contributors":{"authors":[{"text":"Treglia, Michael L.","contributorId":145921,"corporation":false,"usgs":false,"family":"Treglia","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":16299,"text":"Dep't Wildlife and Fisheries, Texas A&M U, College Station, Texas","active":true,"usgs":false}],"preferred":false,"id":751170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landon, Adam C","contributorId":210605,"corporation":false,"usgs":false,"family":"Landon","given":"Adam","email":"","middleInitial":"C","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":751171,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":751169,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kyle, Gerard","contributorId":210606,"corporation":false,"usgs":false,"family":"Kyle","given":"Gerard","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":751172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitzgerald, Lee A.","contributorId":141035,"corporation":false,"usgs":false,"family":"Fitzgerald","given":"Lee","email":"","middleInitial":"A.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":751173,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199886,"text":"ofr20181157 - 2018 - Monitoring framework for evaluating hydrogeomorphic and vegetation responses to environmental flows in the Middle Fork Willamette, McKenzie, and Santiam River Basins, Oregon","interactions":[],"lastModifiedDate":"2018-11-15T16:13:39","indexId":"ofr20181157","displayToPublicDate":"2018-11-14T13:43:02","publicationYear":"2018","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":"2018-1157","displayTitle":"Monitoring Framework for Evaluating Hydrogeomorphic and Vegetation Responses to Environmental Flows in the Middle Fork Willamette, McKenzie, and Santiam River Basins, Oregon","title":"Monitoring framework for evaluating hydrogeomorphic and vegetation responses to environmental flows in the Middle Fork Willamette, McKenzie, and Santiam River Basins, Oregon","docAbstract":"This report summarizes a framework for monitoring hydrogeomorphic and vegetation responses to environmental flows in support of the Willamette Sustainable Rivers Program (SRP). The SRP is a partnership between The Nature Conservancy (TNC) and U.S. Army Corps of Engineers (USACE) to provide ecologically sustainable flows downstream of dams while still meeting human needs and congressionally authorized purposes. TNC, USACE, and U.S. Geological Survey (USGS) developed this framework specifically for the spawning reaches and lower, alluvial reaches of the Middle Fork Willamette, McKenzie, North Santiam, South Santiam, and main-stem Santiam Rivers. This monitoring framework links stakeholder-defined ecological goals and environmental flow recommendations with measurable objectives and monitoring activities to assess whether those objectives are achieved. Monitoring activities are described for distinct spatial scales (reaches, zones, and sites), which are coupled with appropriate measurement frequency (monthly to decadal or following specific flow conditions). Initial monitoring efforts could focus on developing baseline datasets for tracking future changes and developing robust relationships between flow and hydrogeomorphic and vegetation processes. These relationships would support stakeholders in developing refined environmental flow recommendations that could be efficiently evaluated in the future using continuous discharge records and strategic field-based monitoring.
Environmental flow recommendations were developed to achieve certain hydraulic targets (generally defined through water-surface elevation and inundation extent) to support critical habitats for native species at different times of the year. Additionally, flow recommendations were created to support geomorphic processes that create and sustain important riparian and aquatic habitats. The spatial extent, depth, timing, duration, and frequency of inundation extents can be monitored using a combination of water-level loggers, crest-stage gages, surveys, and mapping from aerial photographs or satellite images. Changes in channel morphology (such as increases in gravel bars, side channels or channel width) can be evaluated through repeat mapping of aerial photographs or lidar and carried, and repeat surveys of channel-bed elevations could document patterns of incision or aggradation. Changes in bed texture (such as fining or coarsening) could focus on spawning habitats for spring Chinook salmon (Oncorhynchus tshawytscha). Deposition of fine-grained sediment in floodplain channels could be evaluated with deposition pads, repeat surveys, or lidar.
Environmental flow recommendations also were developed to promote various stages of floodplain forest succession, with a focus on black cottonwood (Populus trichocarpa) because its life history is tightly coupled with floodplain hydrology and disturbance processes. Monitoring approaches for vegetation include strategies for tracking all phases of stand recruitment, establishment, and succession for black cottonwood. Potential recruitment sites can be identified by mapping unvegetated gravel bars from aerial photographs or lidar. Reach-scale patterns of stand recruitment and early succession can be monitored at the reach scale by mapping seral stages of floodplain vegetation from aerial photographs and lidar at the decadal scale. These monitoring approaches also could identify areas of stand recruitment or floodplain recycling. Site-scale monitoring of black cottonwood recruitment and establishment could focus on vegetation plots situated along floodplain transects within laterally dynamic monitoring zones to track seedling establishment or stem exclusion and early seral succession. Reach-scale landcover mapping from aerial photographs and lidar would complement site-scale observations and aid in characterizing overall status and condition of floodplain forests, which could be related to streamflows and hydrogeomorphic processes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181157","collaboration":"Prepared in cooperation with The Nature Conservancy and the U.S. Army Corps of Engineers","usgsCitation":"Wallick, J.R., Bach, L.B., Keith, M.K., Olson, M., Mangano, J.F., and Jones, K.L., 2018, Monitoring framework for evaluating hydrogeomorphic and vegetation responses to environmental flows in the Middle Fork Willamette, McKenzie, and Santiam River Basins, Oregon: U.S. Geological Survey Open-File Report 2018–1157, 66 p.,\nhttps://doi.org/10.3133/ofr20181157.","productDescription":"vi, 66 p.","onlineOnly":"Y","ipdsId":"IP-090522 ","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":359441,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1157/ofr20181157.pdf","text":"Report","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1157"},{"id":359440,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1157/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Middle Fork Willamette, McKenzie, and Santiam River Basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.33,\n 43.8333\n ],\n [\n -122.1667,\n 43.8333\n ],\n [\n -122.1667,\n 45\n ],\n [\n -123.33,\n 45\n ],\n [\n -123.33,\n 43.8333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Large carnivores are imperiled globally, and characteristics making them vulnerable to extinction (e.g., low densities and expansive ranges) also make it difficult to estimate demographic parameters needed for management. Here we develop an integrated population model to analyze capture-recapture, radiotelemetry, and count data for the Chukchi Sea subpopulation of polar bears (Ursus maritimus), 2008–2016. Our model addressed several challenges in capture-recapture studies for polar bears by including a multievent structure reflecting location and life history states, while accommodating state uncertainty. Female breeding probability was 0.83 (95% credible interval [CRI] = 0.71–0.90), with litter sizes of 2.18 (95% CRI = 1.71–2.82) for age-zero and 1.61 (95% CRI = 1.46–1.80) for age-one cubs. Total adult survival was 0.90 (95% CRI = 0.86–0.92) for females and 0.89 (95% CRI = 0.83–0.93) for males. Spring on-ice densities west of Alaska were 0.0030 bears/km2 (95% CRI = 0.0016–0.0060), similar to 1980s-era density estimates although methodological differences complicate comparison. Abundance of the Chukchi Sea subpopulation, derived by extrapolating density from the study area using a spatially-explicit habitat metric, was 2,937 bears (95% CRI = 1,552–5,944). Our findings are consistent with other lines of evidence suggesting the Chukchi Sea subpopulation has been productive in recent years, although it is uncertain how long this will continue given sea-ice loss due to climate change.
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