We used microsatellites and mtDNA sequences to examine the mixed effects of geophysical, habitat, and contemporary urban barriers on the genetics of threatened Alameda Striped Racers (Coluber lateralis euryxanthus), a species with close ties to declining coastal scrub and chaparral habitat in the eastern San Francisco Bay area of California. We used cluster assignments to characterize population genetic structuring with respect to land management units and approximate Bayesian analysis to rank the ability of five alternative evolutionary hypotheses to explain the inferred structure. Then, we estimated rates of contemporary and historical migration among the major clusters and measured the fit of different historical migration models to better understand the formation of the current population structure. Our results reveal a ring-like pattern of historical connectivity around the Tri-Valley area of the East Bay (i.e., San Ramon, Amador, and Livermore valleys), with clusters largely corresponding to different management units. We found no evidence of continuous gene flow throughout the ring, however, and that the main gap in continuity is centered across the Livermore Valley. Historical migration models support higher rates of gene flow away from the terminal ends of the ring on the north and south sides of the Valley, compared with rates into those areas from western sites that border the interior San Francisco Bay. We attribute the break in ring-like connectivity to the presence of unsuitable habitat within the Livermore Valley that has been reinforced by 20th century urbanization, and the asymmetry in gene flow rates to spatial constraints on movement and east–west environmental gradients influenced by the proximity of the San Francisco Bay.
","language":"English","publisher":"The Herpetologists' League","doi":"10.1655/Herpetologica-D-15-00046.1","usgsCitation":"Richmond, J.Q., Wood, D.A., Swaim, K., Fisher, R.N., and Vandergast, A.G., 2016, Historical habitat barriers prevent ring-like genetic continuity throughout the distribution of threatened Alameda Striped Racers (Coluber lateralis euryxanthus): Herpetologica, v. 72, no. 3, p. 202-213, https://doi.org/10.1655/Herpetologica-D-15-00046.1.","productDescription":"12 p.","startPage":"202","endPage":"213","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066471","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":324669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Tri-Valley area of the East Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.40280151367188,\n 37.80218877920469\n ],\n [\n -122.20916748046876,\n 37.54457732085582\n ],\n [\n -122.04299926757812,\n 37.42034463389752\n ],\n [\n -121.96746826171875,\n 37.47594794878128\n ],\n [\n -122.20367431640624,\n 37.779398571318765\n ],\n [\n -122.40280151367188,\n 37.80218877920469\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"72","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5776349de4b07dd077c829c3","contributors":{"authors":[{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":641399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Dustin A. 0000-0002-7668-9911 dawood@usgs.gov","orcid":"https://orcid.org/0000-0002-7668-9911","contributorId":4179,"corporation":false,"usgs":true,"family":"Wood","given":"Dustin","email":"dawood@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":641400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swaim, Karen","contributorId":172600,"corporation":false,"usgs":false,"family":"Swaim","given":"Karen","affiliations":[{"id":27065,"text":"Swaim Biological Inc, Livermore, CA","active":true,"usgs":false}],"preferred":false,"id":641401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":641402,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vandergast, Amy G. 0000-0002-7835-6571 avandergast@usgs.gov","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":3963,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"avandergast@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":641403,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174047,"text":"70174047 - 2016 - Understanding the hydrologic impacts of wastewater treatment plant discharge to shallow groundwater: Before and after plant shutdown","interactions":[],"lastModifiedDate":"2018-08-07T12:41:40","indexId":"70174047","displayToPublicDate":"2016-06-30T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5112,"text":"Environmental Science: Water Research & Technology","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the hydrologic impacts of wastewater treatment plant discharge to shallow groundwater: Before and after plant shutdown","docAbstract":"Effluent-impacted surface water has the potential to transport not only water, but wastewater-derived contaminants to shallow groundwater systems. To better understand the effects of effluent discharge on in-stream and near-stream hydrologic conditions in wastewater-impacted systems, water-level changes were monitored in hyporheic-zone and shallow-groundwater piezometers in a reach of Fourmile Creek adjacent to and downstream of the Ankeny (Iowa, USA) wastewater treatment plant (WWTP). Water-level changes were monitored from approximately 1.5 months before to 0.5 months after WWTP closure. Diurnal patterns in WWTP discharge were closely mirrored in stream and shallow-groundwater levels immediately upstream and up to 3 km downstream of the outfall, indicating that such discharge was the primary control on water levels before shutdown. The hydrologic response to WWTP shutdown was immediately observed throughout the study reach, verifying the far-reaching hydraulic connectivity and associated contaminant transport risk. The movement of WWTP effluent into alluvial aquifers has implications for potential WWTP-derived contamination of shallow groundwater far removed from the WWTP outfall.
","language":"English","publisher":"The Royal Society of Chemistry","doi":"10.1039/c6ew00128a","usgsCitation":"Hubbard, L.E., Keefe, S.H., Kolpin, D.W., Barber, L.B., Duris, J.W., Hutchinson, K.J., and Bradley, P.M., 2016, Understanding the hydrologic impacts of wastewater treatment plant discharge to shallow groundwater: Before and after plant shutdown: Environmental Science: Water Research & Technology, v. 2, p. 864-874, https://doi.org/10.1039/c6ew00128a.","productDescription":"11 p.","startPage":"864","endPage":"874","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073598","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":438604,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RF5S3P","text":"USGS data release","linkHelpText":"Precipitation, surface-water discharge, and groundwater elevation data for Fourmile Creek, Ankeny, Iowa, USA during October 1, 2013 to November 30, 2013"},{"id":324665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Fourmile Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.7408447265625,\n 41.4684573556768\n ],\n [\n -93.7408447265625,\n 41.75184866809371\n ],\n [\n -93.43185424804688,\n 41.75184866809371\n ],\n [\n -93.43185424804688,\n 41.4684573556768\n ],\n [\n -93.7408447265625,\n 41.4684573556768\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5776349ee4b07dd077c829d9","contributors":{"authors":[{"text":"Hubbard, Laura E. 0000-0003-3813-1500 lhubbard@usgs.gov","orcid":"https://orcid.org/0000-0003-3813-1500","contributorId":4221,"corporation":false,"usgs":true,"family":"Hubbard","given":"Laura","email":"lhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keefe, Steffanie H. 0000-0002-3805-6101 shkeefe@usgs.gov","orcid":"https://orcid.org/0000-0002-3805-6101","contributorId":2843,"corporation":false,"usgs":true,"family":"Keefe","given":"Steffanie","email":"shkeefe@usgs.gov","middleInitial":"H.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":640683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":640685,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duris, Joseph W. 0000-0002-8669-8109 jwduris@usgs.gov","orcid":"https://orcid.org/0000-0002-8669-8109","contributorId":172426,"corporation":false,"usgs":true,"family":"Duris","given":"Joseph","email":"jwduris@usgs.gov","middleInitial":"W.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":640686,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hutchinson, Kasey J. khutchin@usgs.gov","contributorId":4223,"corporation":false,"usgs":true,"family":"Hutchinson","given":"Kasey","email":"khutchin@usgs.gov","middleInitial":"J.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640687,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640688,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70173837,"text":"sir20165086 - 2016 - Three-dimensional visualization maps of suspended-sediment concentrations during placement of dredged material in 21st Avenue West Channel Embayment, Duluth-Superior Harbor, Duluth, Minnesota, 2015","interactions":[],"lastModifiedDate":"2016-07-01T11:38:06","indexId":"sir20165086","displayToPublicDate":"2016-06-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5086","title":"Three-dimensional visualization maps of suspended-sediment concentrations during placement of dredged material in 21st Avenue West Channel Embayment, Duluth-Superior Harbor, Duluth, Minnesota, 2015","docAbstract":"Excess sediment in rivers and estuaries poses serious environmental and economic challenges. The U.S. Army Corps of Engineers (USACE) routinely dredges sediment in Federal navigation channels to maintain commercial shipping operations. The USACE initiated a 3-year pilot project in 2013 to use navigation channel dredged material to aid in restoration of shoreline habitat in the 21st Avenue West Channel Embayment of the Duluth-Superior Harbor. Placing dredged material in the 21st Avenue West Channel Embayment supports the restoration of shallow bay aquatic habitat aiding in the delisting of the St. Louis River Estuary Area of Concern.
The U.S. Geological Survey, in cooperation with the USACE, collected turbidity and suspended-sediment concentrations (SSCs) in 2014 and 2015 to measure the horizontal and vertical distribution of SSCs during placement operations of dredged materials. These data were collected to help the USACE evaluate the use of several best management practices, including various dredge material placement techniques and a silt curtain, to mitigate the dispersion of suspended sediment.
Three-dimensional visualization maps are a valuable tool for assessing the spatial displacement of SSCs. Data collection was designed to coincide with four dredged placement configurations that included periods with and without a silt curtain as well as before and after placement of dredged materials. Approximately 230 SSC samples and corresponding turbidity values collected in 2014 and 2015 were used to develop a simple linear regression model between SSC and turbidity. Using the simple linear regression model, SSCs were estimated for approximately 3,000 turbidity values at approximately 100 sampling sites in the 21st Avenue West Channel Embayment of the Duluth-Superior Harbor. The estimated SSCs served as input for development of 12 three-dimensional visualization maps.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165086","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Groten, J.T., Ellison, C.A., and Mahoney, M.H., 2016, Three-dimensional visualization maps of suspended-sediment concentrations during placement of dredged material in 21st Avenue West Channel Embayment, Duluth-Superior Harbor, Duluth, Minnesota, 2015: U.S. Geological Survey Scientific Investigations Report 2016–5086, 26 p., https://dx.doi.org/10.3133/sir20165086.","productDescription":"Report: vi, 26 p.; Appendix Tables: 1-1 through 1-4","startPage":"1","endPage":"26","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069759","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":324664,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5086/sir20165086_appendix1.xlsx","text":"Appendix Tables 1–1 through 1–4","size":"277 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5086 Appendix Tables"},{"id":324663,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5086/sir20165086.pdf","text":"Report","size":"8.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5086"},{"id":324662,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5086/coverthb.jpg"}],"country":"United States","state":"Minnesota","city":"Duluth","otherGeospatial":"Duluth-Superior Harbor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.12679862976073,\n 46.75162347434115\n ],\n [\n -92.12679862976073,\n 46.76626466624822\n ],\n [\n -92.10474014282227,\n 46.76626466624822\n ],\n [\n -92.10474014282227,\n 46.75162347434115\n ],\n [\n -92.12679862976073,\n 46.75162347434115\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
In 2015, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, drilled and constructed boreholes TAN-2271 and TAN-2272 for stratigraphic framework analyses and long-term groundwater monitoring of the eastern Snake River Plain aquifer at the Idaho National Laboratory in southeast Idaho. Borehole TAN-2271 initially was cored to collect continuous geologic data, and then re-drilled to complete construction as a monitor well. Borehole TAN-2272 was partially cored between 210 and 282 feet (ft) below land surface (BLS) then drilled and constructed as a monitor well. Boreholes TAN-2271 and TAN-2272 are separated by about 63 ft and have similar geologic layers and hydrologic characteristics based on geologic, geophysical, and aquifer test data collected. The final construction for boreholes TAN-2271 and TAN-2272 required 10-inch (in.) diameter carbon-steel well casing and 9.9-in. diameter open-hole completion below the casing to total depths of 282 and 287 ft BLS, respectively. Depth to water is measured near 228 ft BLS in both boreholes. Following construction and data collection, temporary submersible pumps and water-level access lines were placed to allow for aquifer testing, for collecting periodic water samples, and for measuring water levels.
Borehole TAN-2271 was cored continuously, starting at the first basalt contact (about 33 ft BLS) to a depth of 284 ft BLS. Excluding surface sediment, recovery of basalt and sediment core at borehole TAN-2271 was better than 98 percent. Based on visual inspection of core and geophysical data, material examined from 33 to 211ft BLS primarily consists of two massive basalt flows that are about 78 and 50 ft in thickness and three sediment layers near 122, 197, and 201 ft BLS. Between 211 and 284 ft BLS, geophysical data and core material suggest a high occurrence of fractured and vesicular basalt. For the section of aquifer tested, there are two primary fractured aquifer intervals: the first between 235 and 255 ft BLS and the second between 272 and 282 ft BLS. Basalt texture for borehole TAN-2271 generally was described as aphanitic, phaneritic, and porphyritic. Sediment layers, starting near 122 ft BLS, generally were composed of fine-grained sand and silt with a lesser amount of clay. Basalt flows generally ranged in thickness from 2 to 78 ft and varied from highly fractured to dense with high to low vesiculation. Geophysical data and limited core material collected from TAN-2272 show similar lithologic sequences to those reported for TAN-2271.
Geophysical and borehole video logs were collected during certain stages of the drilling and construction process at boreholes TAN-2271 and TAN-2272. Geophysical logs were examined synergistically with available core material to confirm geologic and hydrologic similarities and suggest possible fractured network interconnection between boreholes TAN-2271 and TAN-2272. Natural gamma log measurements were used to assess the completeness of the vapor port lines behind 10-in. diameter well casing. Electromagnetic flow meter results were used to identify downward flow conditions that exist for boreholes TAN-2271 and TAN-2272. Furthermore, gyroscopic deviation measurements were used to measure horizontal and vertical displacement at all depths in boreholes TAN-2271 and TAN-2272.
After borehole construction was completed, single‑well aquifer tests were done within wells TAN-2271 and TAN‑2272 to provide estimates of transmissivity and hydraulic conductivity. The transmissivity and hydraulic conductivity were estimated for the pumping well and observation well during the aquifer tests conducted on August 25 and August 27, 2015. Estimates for transmissivity range from 4.1 . 103 feet squared per day (ft2/d) to 8.1 . 103 ft2/d; estimates for hydraulic conductivity range from 5.8 to 11.5 feet per day (ft/d). Both TAN-2271 and TAN‑2272 show sustained pumping rates of about 30 gallons per minute (gal/min) with measured drawdown in the pumping well of 1.96 ft and 1.14 ft, respectively. The transmissivity estimates for wells tested were within the range of values determined from previous aquifer tests in other wells near Test Area North.
Groundwater samples were collected from both wells and were analyzed for cations, anions, metals, nutrients, volatile organic compounds, stable isotopes, and radionuclides. Groundwater samples for most of the inorganic constituents showed similar water chemistry in both wells. Groundwater samples for strontium-90, trichloroethene, and vinyl chloride exceeded maximum contaminant levels for public drinking water supplies in one or both wells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165088","collaboration":"DOE/ID-22239Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
Mercury (Hg) analyses were conducted on samples of sport fish and water collected from selected sampling sites in Brownlee Reservoir and the Boise and Snake Rivers to meet National Pollution Discharge and Elimination System (NPDES) permit requirements for the City of Boise, Idaho, between 2013 and 2015. City of Boise personnel collected water samples from six sites between October and November 2013 and 2015, with one site sampled in 2014. Total Hg concentrations in unfiltered water samples ranged from 0.48 to 8.8 nanograms per liter (ng/L), with the highest value in Brownlee Reservoir in 2013. All Hg concentrations in water samples were less than the U.S. Environmental Protection Agency (USEPA) Hg chronic aquatic life criterion of 12 ng/L.
The USEPA recommended a water-quality criterion of 0.30 milligrams per kilogram (mg/kg) methylmercury (MeHg) expressed as a fish-tissue residue value (wet-weight MeHg in fish tissue). The Idaho Department of Environmental Quality adopted the USEPA’s fish-tissue criterion and established a reasonable potential to exceed (RPTE) threshold 20 percent lower than the criterion or greater than 0.24 mg/kg Hg based on an average concentration of 10 fish from a receiving waterbody. NPDES permitted discharge to waters with fish having Hg concentrations exceeding 0.24 mg/kg are said to have a reasonable potential to exceed the water-quality criterion and thus are subject to additional permit obligations, such as requirements for increased monitoring and the development of a Hg minimization plan. The Idaho Fish Consumption Advisory Program (IFCAP) issues fish advisories to protect general and sensitive populations of fish consumers and has developed an action level of 0.22 mg/kg Hg in fish tissue. Fish consumption advisories are water body- and species-specific and are used to advise allowable fish consumption from specific water bodies. The geometric mean Hg concentration of 10 fish of a single species collected from a single water body (lake or stream) in Idaho is compared to the action level to determine if a fish consumption advisory should be issued.
The U.S. Geological Survey collected and analyzed individual fillets of mountain whitefish (Prosopium williamsoni), rainbow trout (Oncorhynchus mykiss), smallmouth bass (Micropterus dolomieu), and channel catfish (Ictalurus punctatus) for Hg. The 2013 average Hg concentration for small mouth bass (0.32 mg/kg) collected at Brownlee Reservoir and for channel catfish (0.33 mg/kg) collected at the Boise River mouth, exceeded the Idaho water quality criterion (>0.3 mg/kg), the Hg RPTE threshold (>0.24 mg/kg), and the IFCAP action level (>0.22 mg/kg). Average Hg concentrations in fish collected in 2014 or 2015 did not exceed evaluation criteria for any of the species assessed.
Selenium (Se) analysis was conducted on one composite fish tissue sample per site to assess general concentrations and to provide information for future risk assessments. Composite concentrations of Se in fish tissue collected between 2013 and 2015 ranged from 0.07 and 0.49 mg/kg wet weight with the highest concentration collected from smallmouth bass from the Snake River near Murphy, and the lowest from mountain whitefish from the Boise River at Eckert Road.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161098","collaboration":"Prepared in cooperation with the City of Boise, Idaho","usgsCitation":"Williams, M.L., and MacCoy, D.E., 2016, Mercury concentrations in water and mercury and selenium concentrations in fish from Brownlee Reservoir and selected sites in the Boise and Snake Rivers, Idaho and Oregon, 2013–15: U.S. Geological Survey Open-File Report 2016–1098, 29 p., https://dx.doi.org/10.3133/ofr20161098.","productDescription":"iv, 38p.","startPage":"1","endPage":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070289","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":324695,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1098/ofr20161098.pdf","text":"Report","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1098"},{"id":324694,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1098/coverthb.jpg"}],"country":"United States","state":"Idaho","city":"Boise","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.6912841796875,\n 43.07089421067248\n ],\n [\n -116.6912841796875,\n 44.004669106432225\n ],\n [\n -115.58990478515625,\n 44.004669106432225\n ],\n [\n -115.58990478515625,\n 43.07089421067248\n ],\n [\n -116.6912841796875,\n 43.07089421067248\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
The effects of urbanization on annual maximum peak discharges in northeastern Illinois and nearby areas from 1945 to 2009 were analyzed with a two-step longitudinal-quantile linear regression approach. The peak discharges were then adjusted to 2010 land-use conditions. The explanatory variables used were daily precipitation at the time of the peak discharge event and a housing density-based measure of developed land use. The effect of the implementation of stormwater detention was assessed indirectly. Peak discharge records affected by the construction of large reservoirs that affect channel routing were identified and were split into segments at the time of completion of the reservoir. Longitudinal regressions of the peak discharge records on linear and logarithmic transformations of the selected measures of urbanization and precipitation were tested, and the best fitting model was selected for quantile regression and adjustment of the peak discharges.
\nBecause the uncertainties of streamgage-by-streamgage regressions of peak discharges as a function of urbanization are so large, a regional urbanization response was computed. Streamgages used in this study fit the following two criteria: (1) drainage area is at most 200 square miles and, (2) at least 10 consecutive years of peak discharge record are available. In the first step of the regression analysis, linear longitudinal regression models with fixed intercepts estimated for each segment of the peak discharge records were computed. The segment intercepts were then subtracted from the discharge records to homogenize the discharge dataset across the segments in preparation for the quantile regression analysis. From the quantile regression analysis, the effect of urbanization on peak discharge varies strongly with the exceedance probability of the peak discharge event; coefficients monotonically increase from 0.340 to 0.969 over exceedance probabilities from 0.002 to 0.99. The regression analyses yield estimates of the population-wide effect of the explanatory variables on the dependent variables as a function of exceedance probability. These estimates are similar to the coefficients of the regional regression relations in USGS regional flood-frequency studies such as those implemented in the Web application StreamStats; although in the longitudinal analysis used in this study, it is the temporal not the spatial (between-streamgage) variations that are taken into account.
\nThe observed and adjusted values for each streamgage are tabulated. To illustrate the overall effect of the adjustments, differences in the mean, standard deviation, and skewness of the log-transformed observed and urbanization-adjusted peak discharge series by streamgage are computed. For almost every streamgage where an adjustment was applied (no increase in urbanization was reported for a few streamgages), the mean increased and the standard deviation decreased; the effect on skewness values was more variable but usually they increased. Significant positive peak discharge trends were common in the observed values, occurring at 27.3 percent of streamgages at a p-value of 0.05 according to a Kendall’s tau correlation test; in the adjusted values, the incidence of such trends was reduced to 7.0 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165049","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers—Chicago District, the Illinois Center for Transportation, the Illinois Department of Transportation, and the Federal Highway Administration","usgsCitation":"Over, T.M., Saito, R.J., and Soong, D.T., 2016, Adjusting annual maximum peak discharges at selected stations in northeastern Illinois for changes in land-use conditions: U.S. Geological Survey Scientific Investigations Report 2016–5049, 33 p., https://dx.doi.org/10.3133/sir20165049.","productDescription":"Report: viii, 33 p.; Tables; Spatial Data","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-050378","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":324541,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2016/5049/sir20165049_Theobald_tifs.zip","text":"1940–2030 Housing Density Data","size":"1.04 GB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016–5049 Spatial Data"},{"id":324540,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5049/sir20165049_tables.xlsx","text":"Tables 1, 3, 4, and 7","size":"375 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5049 Tables"},{"id":324534,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5049/coverthb.jpg"},{"id":324535,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5049/sir20165049.pdf","text":"Report","size":"4.89 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5049"}],"country":"United States","state":"Illinois","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"Polygon\",\n 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U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
Though characterization of, and understanding determinants of, social structure in bats is increasing, little is known about how bat social groups respond to disturbance resulting in roost loss. Given that many species of bats roost in ephemeral or transitory resources such as plants, it is clear that bat social groups can tolerate some level of roost loss. Understanding responses of bat social groups to roost loss can provide insight into social structure that have applied conservation use. Herein, we review the existing literature on the effects of disturbance on bat social groups, and present a parameterizable agent-based model that can be used to explore the relationships among roost dynamics, population dynamics, and social behavior.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Sociality in bats","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-38953-0_13","usgsCitation":"Silvis, A., Abaid, N., Ford, W., and Britzke, E.R., 2016, Responses of bat social groups to roost loss: More questions than answers, chap. of Sociality in bats, p. 261-280, https://doi.org/10.1007/978-3-319-38953-0_13.","productDescription":"20 p.","startPage":"261","endPage":"280","ipdsId":"IP-066788","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-08","publicationStatus":"PW","scienceBaseUri":"59099aaee4b0fc4e449157ee","contributors":{"editors":[{"text":"Ortega, Jorge","contributorId":191697,"corporation":false,"usgs":false,"family":"Ortega","given":"Jorge","email":"","affiliations":[],"preferred":false,"id":693882,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Silvis, Alexander","contributorId":171585,"corporation":false,"usgs":false,"family":"Silvis","given":"Alexander","email":"","affiliations":[{"id":26923,"text":"Virginia Polytechnic Institute, Blacksburg, VA","active":true,"usgs":false}],"preferred":false,"id":693879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abaid, Nicole","contributorId":171663,"corporation":false,"usgs":false,"family":"Abaid","given":"Nicole","email":"","affiliations":[],"preferred":false,"id":693880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":693147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Britzke, Eric R.","contributorId":8327,"corporation":false,"usgs":true,"family":"Britzke","given":"Eric","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":693881,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189318,"text":"70189318 - 2016 - Using macroinvertebrate assemblages and multiple stressors to infer urban stream system condition: A case study in the central US","interactions":[],"lastModifiedDate":"2018-03-26T14:34:33","indexId":"70189318","displayToPublicDate":"2016-06-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3669,"text":"Urban Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Using macroinvertebrate assemblages and multiple stressors to infer urban stream system condition: A case study in the central US","docAbstract":"Characterizing the impacts of hydrologic alterations, pollutants, and habitat degradation on macroinvertebrate species assemblages is of critical value for managers wishing to categorize stream ecosystem condition. A combination of approaches including trait-based metrics and traditional bioassessments provides greater information, particularly in anthropogenic stream ecosystems where traditional approaches can be confounded by variously interacting land use impacts. Macroinvertebrates were collected from two rural and three urban nested study sites in central Missouri, USA during the spring and fall seasons of 2011. Land use responses of conventional taxonomic and trait-based metrics were compared to streamflow indices, physical habitat metrics, and water quality indices. Results show that biotic index was significantly different (p < 0.05) between sites with differences detected in 54 % of trait-based metrics. The most consistent response to urbanization was observed in size metrics, with significantly (p < 0.05) fewer small bodied organisms. Increases in fine streambed sediment, decreased submerged woody rootmats, significantly higher winter Chloride concentrations, and decreased mean suspended sediment particle size in lower urban stream reaches also influenced macroinvertebrate assemblages. Riffle habitats in urban reaches contained 21 % more (p = 0.03) multivoltine organisms, which was positively correlated to the magnitude of peak flows (r2 = 0.91, p = 0.012) suggesting that high flow events may serve as a disturbance in those areas. Results support the use of macroinvertebrate assemblages and multiple stressors to characterize urban stream system condition and highlight the need to better understand the complex interactions of trait-based metrics and anthropogenic aquatic ecosystem stressors.
","language":"English","publisher":"Springer","doi":"10.1007/s11252-016-0534-4","usgsCitation":"Nichols, J.W., Hubbart, J.A., and Poulton, B.C., 2016, Using macroinvertebrate assemblages and multiple stressors to infer urban stream system condition: A case study in the central US: Urban Ecosystems, v. 19, no. 2, p. 679-704, https://doi.org/10.1007/s11252-016-0534-4.","productDescription":"26 p. ","startPage":"679","endPage":"704","ipdsId":"IP-081283","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":343550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri ","otherGeospatial":"Hinkson Creek Watershed ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.43450164794922,\n 38.872859384572244\n ],\n [\n -92.43450164794922,\n 39.00637903337455\n ],\n [\n -92.22335815429688,\n 39.00637903337455\n ],\n [\n -92.22335815429688,\n 38.872859384572244\n ],\n [\n -92.43450164794922,\n 38.872859384572244\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-03","publicationStatus":"PW","scienceBaseUri":"5965b31ee4b0d1f9f05b380a","contributors":{"authors":[{"text":"Nichols, John W.","contributorId":175334,"corporation":false,"usgs":false,"family":"Nichols","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":704134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hubbart, Jason A.","contributorId":194439,"corporation":false,"usgs":false,"family":"Hubbart","given":"Jason","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":704135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poulton, Barry C. 0000-0002-7219-4911 bpoulton@usgs.gov","orcid":"https://orcid.org/0000-0002-7219-4911","contributorId":2421,"corporation":false,"usgs":true,"family":"Poulton","given":"Barry","email":"bpoulton@usgs.gov","middleInitial":"C.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":704133,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188909,"text":"70188909 - 2016 - Induced earthquake magnitudes are as large as (statistically) expected","interactions":[],"lastModifiedDate":"2017-06-27T13:42:44","indexId":"70188909","displayToPublicDate":"2016-06-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Induced earthquake magnitudes are as large as (statistically) expected","docAbstract":"A major question for the hazard posed by injection-induced seismicity is how large induced earthquakes can be. Are their maximum magnitudes determined by injection parameters or by tectonics? Deterministic limits on induced earthquake magnitudes have been proposed based on the size of the reservoir or the volume of fluid injected. However, if induced earthquakes occur on tectonic faults oriented favorably with respect to the tectonic stress field, then they may be limited only by the regional tectonics and connectivity of the fault network. In this study, we show that the largest magnitudes observed at fluid injection sites are consistent with the sampling statistics of the Gutenberg-Richter distribution for tectonic earthquakes, assuming no upper magnitude bound. The data pass three specific tests: (1) the largest observed earthquake at each site scales with the log of the total number of induced earthquakes, (2) the order of occurrence of the largest event is random within the induced sequence, and (3) the injected volume controls the total number of earthquakes rather than the total seismic moment. All three tests point to an injection control on earthquake nucleation but a tectonic control on earthquake magnitude. Given that the largest observed earthquakes are exactly as large as expected from the sampling statistics, we should not conclude that these are the largest earthquakes possible. Instead, the results imply that induced earthquake magnitudes should be treated with the same maximum magnitude bound that is currently used to treat seismic hazard from tectonic earthquakes.","language":"English","publisher":"AGU Publications","doi":"10.1002/2016JB012818","collaboration":"Page, Morgan T.; Weiser, Deborah; Goebel, Thomas; Hosseini, S. Mehran;","usgsCitation":"van der Elst, N., Page, M.T., Weiser, D.A., Goebel, T., and Hosseini, S.M., 2016, Induced earthquake magnitudes are as large as (statistically) expected: Journal of Geophysical Research B: Solid Earth, v. 121, no. 6, p. 4575-4590, https://doi.org/10.1002/2016JB012818.","productDescription":"16 p. ","startPage":"4575","endPage":"4590","ipdsId":"IP-070705","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":342982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Earth","volume":"121","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-30","publicationStatus":"PW","scienceBaseUri":"59536ea8e4b062508e3c7a7d","contributors":{"authors":[{"text":"van der Elst, Nicholas 0000-0002-3812-1153 nvanderelst@usgs.gov","orcid":"https://orcid.org/0000-0002-3812-1153","contributorId":147858,"corporation":false,"usgs":true,"family":"van der Elst","given":"Nicholas","email":"nvanderelst@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":701073,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":701119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weiser, Deborah A.","contributorId":193625,"corporation":false,"usgs":false,"family":"Weiser","given":"Deborah","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":701120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goebel, Thomas","contributorId":43982,"corporation":false,"usgs":true,"family":"Goebel","given":"Thomas","affiliations":[],"preferred":false,"id":701121,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hosseini, S. Mehran","contributorId":193626,"corporation":false,"usgs":false,"family":"Hosseini","given":"S.","email":"","middleInitial":"Mehran","affiliations":[],"preferred":false,"id":701122,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168828,"text":"70168828 - 2016 - Predicting the stability of endangered stonecats in the LaPlatte River, Vermont","interactions":[],"lastModifiedDate":"2022-11-02T15:02:18.422065","indexId":"70168828","displayToPublicDate":"2016-06-29T17:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the stability of endangered stonecats in the LaPlatte River, Vermont","docAbstract":"Stonecats Noturus flavus in Vermont conform to a rare distribution pattern (as designated by Rabinowitz 1981) because their known distribution within the state is limited to the LaPlatte and Missisquoi rivers. We focused on Stonecats in the LaPlatte River to predict the stability of the population. During 2012–2014, we captured Stonecats via backpack electrofishing; fish were PIT-tagged (>90 mm TL) and marked with visible implant elastomer. Among the 1,671 Stonecats that were captured, 1,252 were PIT-tagged. Only 156 (12%) of the PIT-tagged fish were recaptured, and only 22 of those individuals were recaptured more than once. The Pradel model in Program MARK was used to estimate apparent survival (Φ) and seniority, which were used to derive the rate of population change (λ) for the Stonecat encounter histories we studied. We examined a total of 64 models in our candidate set, with the following covariates: TL at first capture, maximum temperature, season, maximum discharge, and area sampled. Survival estimates were highest in the spring (range of daily Φ = 0.9993–0.9995) and increased with greater TL at first capture. We also estimated increases in capture probability with increasing area sampled. We derived an annual λ of 0.9794, which indicates a slightly decreasing population. However, our λ estimate contained uncertainty that was likely increased due to the low recapture rates. Additional years of data could increase the accuracy of the λ estimate. In the meantime, we have provided insight into Stonecat population parameters that were otherwise unknown.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/00028487.2016.1167779","usgsCitation":"Puchala, E.A., Parrish, D.L., and Donovan, T., 2016, Predicting the stability of endangered stonecats in the LaPlatte River, Vermont: Transactions of the American Fisheries Society, v. 145, no. 4, p. 903-912, https://doi.org/10.1080/00028487.2016.1167779.","productDescription":"10 p.","startPage":"903","endPage":"912","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069044","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":324657,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"LaPlatte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.21598052978516,\n 44.3795759047351\n ],\n [\n -73.21340560913086,\n 44.37564968766977\n ],\n [\n -73.21134567260742,\n 44.37123237879009\n ],\n [\n -73.21443557739258,\n 44.367305602292426\n ],\n [\n -73.20653915405273,\n 44.36632386703344\n ],\n [\n -73.20430755615234,\n 44.36632386703344\n ],\n [\n -73.20138931274414,\n 44.36546483518457\n ],\n [\n -73.19538116455078,\n 44.36202858181481\n ],\n [\n -73.1964111328125,\n 44.35859212688665\n ],\n [\n -73.19023132324219,\n 44.35834665810766\n ],\n [\n -73.18611145019531,\n 44.3587148608905\n ],\n [\n -73.17838668823242,\n 44.3587148608905\n ],\n [\n -73.17684173583984,\n 44.35662834786087\n ],\n [\n -73.17581176757812,\n 44.35159586369938\n ],\n [\n -73.17649841308594,\n 44.34791328441686\n ],\n [\n -73.17684173583984,\n 44.343984944818594\n ],\n [\n -73.17340850830078,\n 44.343248351836074\n ],\n [\n -73.17014694213867,\n 44.34435323783919\n ],\n [\n -73.16225051879883,\n 44.34300281878521\n ],\n [\n -73.15950393676758,\n 44.34337111797587\n ],\n [\n -73.15023422241211,\n 44.344476001665214\n ],\n [\n -73.14525604248047,\n 44.34435323783919\n ],\n [\n -73.14250946044922,\n 44.34288005187414\n ],\n [\n -73.1224250793457,\n 44.337478053272804\n ],\n [\n -73.1198501586914,\n 44.33477686732845\n ],\n [\n -73.12105178833008,\n 44.331216023015294\n ],\n [\n -73.125,\n 44.328882938821394\n ],\n [\n -73.13203811645508,\n 44.32851454862283\n ],\n [\n -73.14422607421875,\n 44.332689502057086\n ],\n [\n -73.15229415893555,\n 44.332689502057086\n ],\n [\n -73.16413879394531,\n 44.33158439624637\n ],\n [\n -73.17255020141602,\n 44.3329350782982\n ],\n [\n -73.18525314331055,\n 44.33465408319267\n ],\n [\n -73.18902969360352,\n 44.338337495433734\n ],\n [\n -73.18937301635742,\n 44.34668570657191\n ],\n [\n -73.18937301635742,\n 44.35049111420936\n ],\n [\n -73.20602416992188,\n 44.35257784576407\n ],\n [\n -73.20791244506836,\n 44.35797845301104\n ],\n [\n -73.21512222290038,\n 44.358837594637265\n ],\n [\n -73.22233200073242,\n 44.3584693926257\n ],\n [\n -73.22593688964844,\n 44.36092402899763\n ],\n [\n -73.22559356689453,\n 44.36914631155484\n ],\n [\n -73.22628021240234,\n 44.37270485210456\n ],\n [\n -73.22851181030273,\n 44.37614047920012\n ],\n [\n -73.2297134399414,\n 44.37982128456053\n ],\n [\n -73.23022842407227,\n 44.38313381155159\n ],\n [\n -73.22851181030273,\n 44.38583276904476\n ],\n [\n -73.22507858276367,\n 44.38656882676517\n ],\n [\n -73.22319030761719,\n 44.38693685215458\n ],\n [\n -73.21701049804688,\n 44.38436062583777\n ],\n [\n -73.21598052978516,\n 44.3795759047351\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-29","publicationStatus":"PW","scienceBaseUri":"5774e34ae4b07dd077c5fcda","contributors":{"authors":[{"text":"Puchala, Elizabeth A.","contributorId":38862,"corporation":false,"usgs":true,"family":"Puchala","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":641374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":621877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donovan, Therese M. tdonovan@usgs.gov","contributorId":2653,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese M.","email":"tdonovan@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":641375,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70156604,"text":"70156604 - 2016 - Misapplied survey data and model uncertainty result in incorrect conclusions about the role of predation on alewife population dynamics in Lake Huron: a comment on He et al. (2015)","interactions":[],"lastModifiedDate":"2016-06-29T16:02:13","indexId":"70156604","displayToPublicDate":"2016-06-29T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Misapplied survey data and model uncertainty result in incorrect conclusions about the role of predation on alewife population dynamics in Lake Huron: a comment on He et al. (2015)","docAbstract":"Drastic recent and ongoing changes to fish populations and food webs in the Great Lakes have been well-described (Riley et al. 2008; Barbiero et al. 2009; Nalepa et al. 2009; Fahnenstiel et al. 2010;Evans et al. 2011; Gobin et al. 2015), and uncertainty regarding their potential effects on fisheries has caused concern among scientists and fishery managers (e.g., Dettmers et al. 2012). In particular, the relative importance of “bottom-up” (e.g., lower trophic level changes) versus “top-down” (e.g., predation) factors to fish community changes in the Great Lakes have been widely debated (e.g.,Barbiero et al. 2011; Eshenroder and Lantry 2012; Bunnell et al. 2014). In Lake Huron, recent ecosystem changes have been particularly profound, and populations of alewife (Alosa pseudoharengus), an offshore pelagic prey fish, collapsed in 2003 and have yet to recover (Riley et al. 2008, 2014). He et al. (2015) recently used a series of linked ecological models to assess the role of predation in the dynamics of the offshore prey fish community in Lake Huron. While we believe that they provide a novel method for combining bioenergetics and stock assessment modeling, we question the validity of their conclusions because of the misapplication of survey data and the lack of critical interpretation of their modeling efforts. Here we describe how He et al. (2015) have misapplied bottom trawl data from Lake Huron, and we provide examples of how this has resulted in erroneous conclusions regarding the importance of predation to the population dynamics and collapse of alewife in Lake Huron.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2015-0237","usgsCitation":"Riley, S.C., and Dunlop, E.S., 2016, Misapplied survey data and model uncertainty result in incorrect conclusions about the role of predation on alewife population dynamics in Lake Huron: a comment on He et al. (2015): Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 5, p. 860-864, https://doi.org/10.1139/cjfas-2015-0237.","productDescription":"5 p.","startPage":"860","endPage":"864","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065429","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":488468,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2015-0237","text":"Publisher Index Page"},{"id":324654,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774e346e4b07dd077c5fcb3","contributors":{"authors":[{"text":"Riley, Stephen C. 0000-0002-8968-8416 sriley@usgs.gov","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":2661,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen","email":"sriley@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":569644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunlop, Erin S.","contributorId":146961,"corporation":false,"usgs":false,"family":"Dunlop","given":"Erin","email":"","middleInitial":"S.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":569645,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169891,"text":"70169891 - 2016 - Saharan dust nutrients promote Vibrio bloom formation in marine surface waters","interactions":[],"lastModifiedDate":"2018-08-08T10:24:20","indexId":"70169891","displayToPublicDate":"2016-06-29T16:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Saharan dust nutrients promote Vibrio bloom formation in marine surface waters","title":"Saharan dust nutrients promote Vibrio bloom formation in marine surface waters","docAbstract":"Vibrio is a ubiquitous genus of marine bacteria, typically comprising a small fraction of the total microbial community in surface waters, but capable of becoming a dominant taxon in response to poorly characterized factors. Iron (Fe), often restricted by limited bioavailability and low external supply, is an essential micronutrient that can limit Vibrio growth. Vibrio species have robust metabolic capabilities and an array of Fe-acquisition mechanisms, and are able to respond rapidly to nutrient influx, yet Vibrio response to environmental pulses of Fe remains uncharacterized. Here we examined the population growth of Vibrioafter natural and simulated pulses of atmospherically transported Saharan dust, an important and episodic source of Fe to tropical marine waters. As a model for opportunistic bacterial heterotrophs, we demonstrated that Vibrio proliferate in response to a broad range of dust-Fe additions at rapid timescales. Within 24 h of exposure, strains of Vibrio cholerae and Vibrio alginolyticus were able to directly use Saharan dust–Fe to support rapid growth. These findings were also confirmed with in situ field studies; arrival of Saharan dust in the Caribbean and subtropical Atlantic coincided with high levels of dissolved Fe, followed by up to a 30-fold increase of culturable Vibrio over background levels within 24 h. The relative abundance of Vibrio increased from ∼1 to ∼20% of the total microbial community. This study, to our knowledge, is the first to describe Vibrio response to Saharan dust nutrients, having implications at the intersection of marine ecology, Fe biogeochemistry, and both human and environmental health.
","language":"English","publisher":"PNAS","doi":"10.1073/pnas.1518080113","usgsCitation":"Westrich, J.R., Ebling, A.M., Landing, W.M., Joyner, J.L., Kemp, K.M., Griffin, D.W., and Lipp, E.K., 2016, Saharan dust nutrients promote Vibrio bloom formation in marine surface waters: Proceedings of the National Academy of Sciences of the United States of America, v. 113, no. 21, p. 5964-5969, https://doi.org/10.1073/pnas.1518080113.","productDescription":"6 p.","startPage":"5964","endPage":"5969","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067140","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470806,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1073/pnas.1518080113","text":"External Repository"},{"id":324647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"21","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"5774e34ee4b07dd077c5fcef","contributors":{"authors":[{"text":"Westrich, Jason R.","contributorId":168327,"corporation":false,"usgs":false,"family":"Westrich","given":"Jason","email":"","middleInitial":"R.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":625484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ebling, Alina M.","contributorId":168328,"corporation":false,"usgs":false,"family":"Ebling","given":"Alina","email":"","middleInitial":"M.","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":625485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landing, William M.","contributorId":151019,"corporation":false,"usgs":false,"family":"Landing","given":"William","email":"","middleInitial":"M.","affiliations":[{"id":18104,"text":"Florida State University, Tallahassee","active":true,"usgs":false}],"preferred":false,"id":625488,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Joyner, Jessica L.","contributorId":168329,"corporation":false,"usgs":false,"family":"Joyner","given":"Jessica","email":"","middleInitial":"L.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":625486,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kemp, Keri M.","contributorId":168330,"corporation":false,"usgs":false,"family":"Kemp","given":"Keri","email":"","middleInitial":"M.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":625487,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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 Center","active":true,"usgs":true}],"preferred":true,"id":625483,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lipp, Erin K.","contributorId":73823,"corporation":false,"usgs":true,"family":"Lipp","given":"Erin","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":625489,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70169334,"text":"70169334 - 2016 - Modeled historical land use and land cover for the conterminous United States","interactions":[],"lastModifiedDate":"2018-03-08T12:52:07","indexId":"70169334","displayToPublicDate":"2016-06-29T16:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2367,"text":"Journal of Land Use Science","active":true,"publicationSubtype":{"id":10}},"title":"Modeled historical land use and land cover for the conterminous United States","docAbstract":"Animal movements can determine the population dynamics of wildlife. We used telemetry data to provide insight into the causes and consequences of local and long-distance movements of multiple age classes of conservation-reliant golden eagles (Aquila chrysaetos) in the foothills and mountains near Tehachapi, California. We estimated size and habitat-related correlates of 324 monthly 95 % home ranges and 317 monthly 50 % core areas for 25 birds moving locally over 2.5 years. We also calculated daily, hourly, and total distances traveled for the five of these birds that engaged in long-distance movements. Mean (±SD) monthly home-range size was 253.6 ± 429.4 km2 and core-area size was 26.4 ± 49.7 km2. Consistent with expectations, space used by pre-adults increased with age and was season-dependent but, unexpectedly, was not sex-dependent. For all ages and sexes, home ranges and core areas were dominated by both forest & woodland and shrubland & grassland habitat types. When moving long distances, eagles traveled up to 1588.4 km (1-way) in a season at highly variable speeds (63.7 ± 69.0 km/day and 5.2 ± 10.4 km/h) that were dependent on time of day. Patterns of long-distance movements by eagles were determined by age, yet these movements had characteristics of more than one previously described movement category (migration, dispersal, etc.). Our results provide a context for differentiating among types of movement behaviors and their population-level consequences and, thus, have implications for management and conservation of golden eagle populations.
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Multiple stressors including the risk of decadal-scale drought, the effects of current and predicted global warming, and continued anthropogenic pressures threaten aquatic habitats in the southwest and cienegas are recognized as important sites for conservation and restoration efforts. However, cienegas present a challenge to satellite-imagery based analysis due to their small size and mixed surface cover of open water, exposed soils, and vegetation. We created time series of five well-known vegetation indices using annual Landsat Thematic Mapper (TM) images retrieved during the April–June dry season, from 1984 to 2011 to map landscape-level distribution of wetlands and monitor the temporal dynamics of individual sites. Indices included the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Infrared Index (NDII). One topographic index, the Topographic Wetness Index (TWI), was analyzed to examine the utility of topography in mapping distribution of cienegas. Our results indicate that the NDII, calculated using Landsat TM band 5, outperforms the other indices at differentiating cienegas from riparian and upland sites, and was the best means to analyze change. As such, it offers a critical baseline for future studies that seek to extend the analysis of cienegas to other regions and time scales, and has broader applicability to the remote sensing of wetland features in arid landscapes.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/15324982.2016.1170076","usgsCitation":"Wilson, N.R., Norman, L.M., Villarreal, M.L., Gass, L., Tiller, R., and Salywon, A., 2016, Comparison of remote sensing indices for monitoring of desert cienegas: Arid Land Research and Management, v. 30, no. 4, p. 460-478, https://doi.org/10.1080/15324982.2016.1170076.","productDescription":"19 p.","startPage":"460","endPage":"478","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068692","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470807,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/15324982.2016.1170076","text":"Publisher Index Page"},{"id":324640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Cienega Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.5667495727539,\n 31.894319802510566\n ],\n [\n -110.5667495727539,\n 31.970512683093744\n ],\n [\n -110.5063247680664,\n 31.970512683093744\n ],\n [\n -110.5063247680664,\n 31.894319802510566\n ],\n [\n -110.5667495727539,\n 31.894319802510566\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-18","publicationStatus":"PW","scienceBaseUri":"5774e32fe4b07dd077c5fbff","contributors":{"authors":[{"text":"Wilson, Natalie R. 0000-0001-5145-1221 nrwilson@usgs.gov","orcid":"https://orcid.org/0000-0001-5145-1221","contributorId":5770,"corporation":false,"usgs":true,"family":"Wilson","given":"Natalie","email":"nrwilson@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":629791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":629792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":629793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gass, Leila 0000-0002-3436-262X lgass@usgs.gov","orcid":"https://orcid.org/0000-0002-3436-262X","contributorId":3770,"corporation":false,"usgs":true,"family":"Gass","given":"Leila","email":"lgass@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":629794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tiller, Ron","contributorId":169496,"corporation":false,"usgs":false,"family":"Tiller","given":"Ron","email":"","affiliations":[{"id":25532,"text":"Arizona Department of Transportation, Environmental Planning Group","active":true,"usgs":false}],"preferred":false,"id":629795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Salywon, Andrew","contributorId":169497,"corporation":false,"usgs":false,"family":"Salywon","given":"Andrew","email":"","affiliations":[{"id":25533,"text":"Desert Botanical Garden","active":true,"usgs":false}],"preferred":false,"id":629796,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70170970,"text":"70170970 - 2016 - Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US","interactions":[],"lastModifiedDate":"2017-01-17T19:16:04","indexId":"70170970","displayToPublicDate":"2016-06-29T15:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2035,"text":"International Journal of Digital Earth","active":true,"publicationSubtype":{"id":10}},"title":"Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US","docAbstract":"Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/17538947.2016.1158876","usgsCitation":"Schleeweis, K., Goward, S.N., Huang, C., Dwyer, J.L., Dungan, J.L., Lindsey, M.A., Michaelis, A., Rishmawi, K., and Masek, J.G., 2016, Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US: International Journal of Digital Earth, v. 9, no. 10, p. 963-980, https://doi.org/10.1080/17538947.2016.1158876.","productDescription":"18 p.","startPage":"963","endPage":"980","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073476","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":324639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-20","publicationStatus":"PW","scienceBaseUri":"5774e34fe4b07dd077c5fcf9","contributors":{"authors":[{"text":"Schleeweis, Karen","contributorId":169308,"corporation":false,"usgs":false,"family":"Schleeweis","given":"Karen","email":"","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":629277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goward, Samuel N.","contributorId":44459,"corporation":false,"usgs":true,"family":"Goward","given":"Samuel","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":629278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huang, Chengquan","contributorId":25378,"corporation":false,"usgs":true,"family":"Huang","given":"Chengquan","affiliations":[],"preferred":false,"id":629279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dwyer, John L. 0000-0002-8281-0896 dwyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-0896","contributorId":3481,"corporation":false,"usgs":true,"family":"Dwyer","given":"John","email":"dwyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":629276,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dungan, Jennifer L.","contributorId":172579,"corporation":false,"usgs":false,"family":"Dungan","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":641329,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lindsey, Mary A.","contributorId":169309,"corporation":false,"usgs":false,"family":"Lindsey","given":"Mary","email":"","middleInitial":"A.","affiliations":[{"id":25467,"text":"Climate Program Office, NOAA","active":true,"usgs":false}],"preferred":false,"id":629280,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Michaelis, Andrew","contributorId":169311,"corporation":false,"usgs":false,"family":"Michaelis","given":"Andrew","email":"","affiliations":[{"id":25468,"text":"University Corporation Monterey Bay / NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":629282,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rishmawi, Khaldoun","contributorId":169310,"corporation":false,"usgs":false,"family":"Rishmawi","given":"Khaldoun","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":629281,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Masek, Jeffery G.","contributorId":87438,"corporation":false,"usgs":true,"family":"Masek","given":"Jeffery","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":629283,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70171123,"text":"70171123 - 2016 - Assessing the relationship between groundwater nitrate and animal feeding operations in Iowa (USA)","interactions":[],"lastModifiedDate":"2016-08-12T09:55:23","indexId":"70171123","displayToPublicDate":"2016-06-29T15:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the relationship between groundwater nitrate and animal feeding operations in Iowa (USA)","docAbstract":"Nitrate-nitrogen is a common contaminant of drinking water in many agricultural areas of the United States of America (USA). Ingested nitrate from contaminated drinking water has been linked to an increased risk of several cancers, specific birth defects, and other diseases. In this research, we assessed the relationship between animal feeding operations (AFOs) and groundwater nitrate in private wells in Iowa. We characterized AFOs by swine and total animal units and type (open, confined, or mixed), and we evaluated the number and spatial intensities of AFOs in proximity to private wells. The types of AFO indicate the extent to which a facility is enclosed by a roof. Using linear regression models, we found significant positive associations between the total number of AFOs within 2 km of a well (p trend < 0.001), number of open AFOs within 5 km of a well (p trend < 0.001), and number of mixed AFOs within 30 km of a well (p trend < 0.001) and the log nitrate concentration. Additionally, we found significant increases in log nitrate in the top quartiles for AFO spatial intensity, open AFO spatial intensity, and mixed AFO spatial intensity compared to the bottom quartile (0.171 log(mg/L), 0.319 log(mg/L), and 0.541 log(mg/L), respectively; all p < 0.001). We also explored the spatial distribution of nitrate-nitrogen in drinking wells and found significant spatial clustering of high-nitrate wells (> 5 mg/L) compared with low-nitrate (≤ 5 mg/L) wells (p = 0.001). A generalized additive model for high-nitrate status identified statistically significant areas of risk for high levels of nitrate. Adjustment for some AFO predictor variables explained a portion of the elevated nitrate risk. These results support a relationship between animal feeding operations and groundwater nitrate concentrations and differences in nitrate loss from confined AFOs vs. open or mixed types.
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,{"id":70173958,"text":"70173958 - 2016 - Isotopically constrained lead sources in fugitive dust from unsurfaced roads in the southeast Missouri mining district","interactions":[],"lastModifiedDate":"2016-10-07T12:56:14","indexId":"70173958","displayToPublicDate":"2016-06-29T15:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Isotopically constrained lead sources in fugitive dust from unsurfaced roads in the southeast Missouri mining district","docAbstract":"The isotopic composition of lead (Pb) in fugitive dust suspended by a vehicle from 13 unsurfaced roads in Missouri was measured to identify the source of Pb within an established long-term mining area. A three end-member model using 207Pb/206Pb and concentration as tracers resulted in fugitive dust samples plotting in the mixing field of well characterized heterogeneous end members. End members selected for this investigation include the 207Pb/206Pb for 1) a Pb-mixture representing mine tailings, 2) aerosol Pb-impacted soils within close proximity to the Buick secondary recycling smelter, and 3) an average of soils, rock cores and drill cuttings representing the background conditions. Aqua regia total concentrations and 207Pb/206Pb of mining area dust suggest that 35.4–84.3% of the source Pb in dust is associated with the mine tailings mixture, 9.1–52.7% is associated with the smelter mixture, and 0–21.6% is associated with background materials. Isotope ratios varied minimally within the operational phases of sequential extraction suggesting that mixing of all three Pb mixtures occurs throughout. Labile forms of Pb were attributed to all three end members. The extractable carbonate phase had as much as 96.6% of the total concentration associated with mine tailings, 51.8% associated with smelter deposition, and 34.2% with background. The next most labile geochemical phase (Fe + Mn Oxides) showed similar results with as much as 85.3% associated with mine tailings, 56.8% associated with smelter deposition, and 4.2% associated with the background soil.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2016.05.070","usgsCitation":"Witt, E.C., Pribil, M., Hogan, J.P., and Wronkiewicz, D., 2016, Isotopically constrained lead sources in fugitive dust from unsurfaced roads in the southeast Missouri mining district: Environmental Pollution, v. 216, p. 450-459, https://doi.org/10.1016/j.envpol.2016.05.070.","productDescription":"10 p.","startPage":"450","endPage":"459","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069014","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":324633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.3,\n 37\n ],\n [\n -91.3,\n 38\n ],\n [\n -90.9,\n 38\n ],\n [\n -90.9,\n 37\n ],\n [\n -91.3,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"216","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774e340e4b07dd077c5fc7b","contributors":{"authors":[{"text":"Witt, Emitt C. III 0000-0002-1814-7807 ecwitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7807","contributorId":1612,"corporation":false,"usgs":true,"family":"Witt","given":"Emitt","suffix":"III","email":"ecwitt@usgs.gov","middleInitial":"C.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":639760,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pribil, Michael J. 0000-0003-4859-8673 mpribil@usgs.gov","orcid":"https://orcid.org/0000-0003-4859-8673","contributorId":141158,"corporation":false,"usgs":true,"family":"Pribil","given":"Michael","email":"mpribil@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":639761,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hogan, John P.","contributorId":172153,"corporation":false,"usgs":false,"family":"Hogan","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":26996,"text":"Missouri University of Science & Technology","active":true,"usgs":false}],"preferred":false,"id":639762,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wronkiewicz, David","contributorId":172154,"corporation":false,"usgs":false,"family":"Wronkiewicz","given":"David","email":"","affiliations":[{"id":26996,"text":"Missouri University of Science & Technology","active":true,"usgs":false}],"preferred":false,"id":639763,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169350,"text":"70169350 - 2016 - Prospective earthquake forecasts at the Himalayan Front after the 25 April 2015 M 7.8 Gorkha Mainshock","interactions":[],"lastModifiedDate":"2016-10-05T11:47:44","indexId":"70169350","displayToPublicDate":"2016-06-29T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Prospective earthquake forecasts at the Himalayan Front after the 25 April 2015 M 7.8 Gorkha Mainshock","docAbstract":"When a major earthquake strikes, the resulting devastation can be compounded or even exceeded by the subsequent cascade of triggered seismicity. As the Nepalese recover from the 25 April 2015 shock, knowledge of what comes next is essential. We calculate the redistribution of crustal stresses and implied earthquake probabilities for different periods, from daily to 30 years into the future. An initial forecast was completed before an M 7.3 earthquake struck on 12 May 2015 that enables a preliminary assessment; postforecast seismicity has so far occurred within a zone of fivefold probability gain. Evaluation of the forecast performance, using two months of seismic data, reveals that stress‐based approaches present improved skill in higher‐magnitude triggered seismicity. Our results suggest that considering the total stress field, rather than only the coseismic one, improves the spatial performance of the model based on the estimation of a wide range of potential triggered faults following a mainshock.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220150195","usgsCitation":"Segou, M., and Parsons, T.E., 2016, Prospective earthquake forecasts at the Himalayan Front after the 25 April 2015 M 7.8 Gorkha Mainshock: Seismological Research Letters, v. 87, no. 4, p. 816-825, https://doi.org/10.1785/0220150195.","productDescription":"10 p.","startPage":"816","endPage":"825","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065687","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470810,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://nora.nerc.ac.uk/id/eprint/514329/1/SegouParsons-SRL-2016-NORA-all.pdf","text":"External Repository"},{"id":324624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"87","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-08","publicationStatus":"PW","scienceBaseUri":"5774e33fe4b07dd077c5fc6b","contributors":{"authors":[{"text":"Segou, Margaret","contributorId":140800,"corporation":false,"usgs":false,"family":"Segou","given":"Margaret","email":"","affiliations":[{"id":13572,"text":"Geoscience Azur","active":true,"usgs":false}],"preferred":false,"id":623869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":623868,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70174187,"text":"70174187 - 2016 - Chemical abrasion-SIMS (CA-SIMS) U-Pb dating of zircon from the late Eocene Caetano caldera, Nevada","interactions":[],"lastModifiedDate":"2019-11-14T12:29:22","indexId":"70174187","displayToPublicDate":"2016-06-29T13:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Chemical abrasion-SIMS (CA-SIMS) U-Pb dating of zircon from the late Eocene Caetano caldera, Nevada","docAbstract":"Zircon geochronology is a critical tool for establishing geologic ages and time scales of processes in the Earth's crust. However, for zircons compromised by open system behavior, achieving robust dates can be difficult. Chemical abrasion (CA) is a routine step prior to thermal ionization mass spectrometry (TIMS) dating of zircon to remove radiation-damaged parts of grains that may have experienced open system behavior and loss of radiogenic Pb. While this technique has been shown to improve the accuracy and precision of TIMS dating, its application to high-spatial resolution dating methods, such as secondary ion mass spectrometry (SIMS), is relatively uncommon. In our efforts to U-Pb date zircons from the late Eocene Caetano caldera by SIMS (SHRIMP-RG: sensitive high resolution ion microprobe, reverse geometry), some grains yielded anomalously young U-Pb ages that implicated Pb-loss and motivated us to investigate with a comparative CA and non-CA dating study. We present CA and non-CA 206Pb/238U ages and trace elements determined by SHRIMP-RG for zircons from three Caetano samples (Caetano Tuff, Redrock Canyon porphyry, and a silicic ring-fracture intrusion) and for R33 and TEMORA-2 reference zircons. We find that non-CA Caetano zircons have weighted mean or bimodal U-Pb ages that are 2–4% younger than CA zircons for the same samples. CA Caetano zircons have mean U-Pb ages that are 0.4–0.6 Myr older than the 40Ar/39Ar sanidine eruption age (34.00 ± 0.03 Ma; error-weighted mean, 2σ), whereas non-CA zircons have ages that are 0.7–1.3 Myr younger. U-Pb ages do not correlate with U (~ 100–800 ppm), Th (~ 50–300 ppm) or any other measured zircon trace elements (Y, Hf, REE), and CA and non-CA Caetano zircons define identical trace element ranges. No statistically significant difference in U-Pb age is observed for CA versus non-CA R33 or TEMORA-2 zircons. Optical profiler measurements of ion microprobe pits demonstrate consistent depths of ~ 1.6 μm for CA and non-CA Caetano, R33 and TEMORA-2 zircons, and do not indicate variations in secondary ion sputtering rates due to chemical or structural changes from the CA treatment. Our new data underscore the potential for cryptic Pb-loss to go unrecognized in other geologically young magmatic centers that do not have zircons with high U, statistically discordant isotope ratios, high common Pb, or metamict textures.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2016.06.013","usgsCitation":"Watts, K.E., Coble, M., Vazquez, J.A., Henry, C., Colgan, J.P., and John, D.A., 2016, Chemical abrasion-SIMS (CA-SIMS) U-Pb dating of zircon from the late Eocene Caetano caldera, Nevada: Chemical Geology, v. 439, no. 7, p. 139-151, https://doi.org/10.1016/j.chemgeo.2016.06.013.","productDescription":"13 p.","startPage":"139","endPage":"151","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052891","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":324622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Caetano Tuff, Red Rock Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.55694580078125,\n 35.90406844132011\n ],\n [\n -115.55694580078125,\n 36.38922936340128\n ],\n [\n -115.36056518554686,\n 36.38922936340128\n ],\n [\n -115.36056518554686,\n 35.90406844132011\n ],\n [\n -115.55694580078125,\n 35.90406844132011\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"439","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774e32be4b07dd077c5fbf3","contributors":{"authors":[{"text":"Watts, Kathryn E. 0000-0002-6110-7499 kwatts@usgs.gov","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":5081,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn","email":"kwatts@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":641192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coble, Matthew A.","contributorId":86622,"corporation":false,"usgs":true,"family":"Coble","given":"Matthew A.","affiliations":[],"preferred":false,"id":641194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":641195,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Henry, Christopher D.","contributorId":36556,"corporation":false,"usgs":true,"family":"Henry","given":"Christopher D.","affiliations":[],"preferred":false,"id":641197,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colgan, Joseph P. 0000-0001-6671-1436 jcolgan@usgs.gov","orcid":"https://orcid.org/0000-0001-6671-1436","contributorId":1649,"corporation":false,"usgs":true,"family":"Colgan","given":"Joseph","email":"jcolgan@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":641193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":641196,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70169100,"text":"70169100 - 2016 - Reevaluating geographic variation in life-history traits of a widespread Nearctic amphibian","interactions":[],"lastModifiedDate":"2016-08-12T10:05:07","indexId":"70169100","displayToPublicDate":"2016-06-29T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2515,"text":"Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Reevaluating geographic variation in life-history traits of a widespread Nearctic amphibian","docAbstract":"Animals from cold environments are usually larger than animals from warm environments, which often produce clines in body size. 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We evaluated biological indices compiled from macroinvertebrate and diatom metrics developed primarily for streams to assess their ability to indicate water quality in connected depression wetlands. We collected water-quality and biological samples at 24 connected depressions dominated by water tupelo (Nyssa aquatica) or bald cypress (Taxodium distichum) (water depths = 0.5–1.0 m). Water quality of the least-disturbed connected depressions was characteristic of swamps in the southeastern USA, which tend to have low specific conductance, nutrient concentrations, and pH. We compared 162 macroinvertebrate metrics and 123 diatom metrics with a water-quality disturbance gradient. For most metrics, we evaluated richness, % richness, abundance, and % relative abundance values. Three of the 4 macroinvertebrate metrics that were most beneficial for identifying disturbance in connected depressions decreased along the disturbance gradient even though they normally increase relative to stream disturbance. The negative relationship to disturbance of some taxa (e.g., dipterans, mollusks, and crustaceans) that are considered tolerant in streams suggests that the tolerance scale for some macroinvertebrates can differ markedly between streams and wetlands. Three of the 4 metrics chosen for the diatom index reflected published tolerances or fit the usual perception of metric response to disturbance. Both biological indices may be useful in connected depressions elsewhere in the Mississippi Alluvial Plain Ecoregion and could have application in other wetland types. Given the paradoxical relationship of some macroinvertebrate metrics to dissolved O2 (DO), we suggest that the diatom metrics may be easier to interpret and defend for wetlands with low DO concentrations in least-disturbed conditions.
","language":"English","publisher":"The University of Chicago Press","doi":"10.1086/687605","usgsCitation":"Justus, B., Burge, D., Cobb, J., Marsico, T., and Bouldin, J., 2016, Macroinvertebrate and diatom metrics as indicators of water-quality conditions in connected depression wetlands in the Mississippi Alluvial Plain: Freshwater Science, v. 35, no. 3, p. 1049-1061, https://doi.org/10.1086/687605.","productDescription":"13 p.","startPage":"1049","endPage":"1061","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064764","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":324613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Cache River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92,\n 34.5\n ],\n [\n -92,\n 36.5\n ],\n [\n -90.5,\n 36.5\n ],\n [\n -90.5,\n 34.5\n ],\n [\n -92,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774e344e4b07dd077c5fca8","contributors":{"authors":[{"text":"Justus, Billy bjustus@usgs.gov","contributorId":152446,"corporation":false,"usgs":true,"family":"Justus","given":"Billy","email":"bjustus@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":589403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burge, David","contributorId":152447,"corporation":false,"usgs":false,"family":"Burge","given":"David","affiliations":[{"id":13476,"text":"Arkansas State University, State University, AR","active":true,"usgs":false}],"preferred":false,"id":589404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cobb, Jennifer","contributorId":152448,"corporation":false,"usgs":false,"family":"Cobb","given":"Jennifer","email":"","affiliations":[{"id":13476,"text":"Arkansas State University, State University, AR","active":true,"usgs":false}],"preferred":false,"id":589405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marsico, Travis","contributorId":152449,"corporation":false,"usgs":false,"family":"Marsico","given":"Travis","affiliations":[{"id":13476,"text":"Arkansas State University, State University, AR","active":true,"usgs":false}],"preferred":false,"id":589406,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bouldin, Jennifer","contributorId":152450,"corporation":false,"usgs":false,"family":"Bouldin","given":"Jennifer","email":"","affiliations":[{"id":13476,"text":"Arkansas State University, State University, AR","active":true,"usgs":false}],"preferred":false,"id":589407,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70160648,"text":"70160648 - 2016 - Ground motions at the outermost limits of seismically triggered landslides","interactions":[],"lastModifiedDate":"2016-07-06T16:41:35","indexId":"70160648","displayToPublicDate":"2016-06-29T12:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Ground motions at the outermost limits of seismically triggered landslides","docAbstract":"Over the last few decades, we and our colleagues have conducted field investigations in which we mapped the outermost limits of triggered landslides in four earthquakes: 1987 Whittier Narrows, California (M 5.9), 1987 Superstition Hills, California (M 6.5), 1994 Northridge, California (M 6.7), and 2011 Mineral, Virginia (M 5.8). In an additional two earthquakes, 1976 Guatemala (M 7.5) and 1983 Coalinga, California (M 6.5), we determined limits using high‐resolution aerial‐photographic interpretation in conjunction with more limited ground investigation. Limits in these earthquakes were defined by the locations of the very smallest failures (<1 m3) from the most susceptible slopes that can be identified positively as having been triggered by earthquake shaking. Because we and our colleagues conducted all of these investigations, consistent methodology and criteria were used in determining limits. In the six earthquakes examined, we correlated the outermost landslide limits with peak ground accelerations (PGAs) from ShakeMap models of each earthquake. For the four earthquakes studied by field investigation, the minimum PGA values associated with farthest landslide limits ranged from 0.02g to 0.08g. The range for the two earthquakes investigated using aerial‐photographic interpretations was 0.05–0.11g. Although PGA values at landslide limits depend on several factors, including material strength, topographic amplification, and hydrologic conditions, these values provide an empirically useful lower limiting range of PGA needed to trigger the smallest failures on very susceptible slopes. In a well‐recorded earthquake, this PGA range can be used to identify an outer boundary within which we might expect to find landsliding; in earthquakes that are not well recorded, mapping the outermost landslide limits provides a useful clue about ground‐motion levels at the mapped limits.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120150141","usgsCitation":"Jibson, R.W., and Harp, E.L., 2016, Ground motions at the outermost limits of seismically triggered landslides: Bulletin of the Seismological Society of America, v. 106, no. 2, p. 708-719, https://doi.org/10.1785/0120150141.","productDescription":"12 p.","startPage":"708","endPage":"719","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071276","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":324608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-09","publicationStatus":"PW","scienceBaseUri":"5774e33be4b07dd077c5fc44","contributors":{"authors":[{"text":"Jibson, Randall W. 0000-0003-3399-0875 jibson@usgs.gov","orcid":"https://orcid.org/0000-0003-3399-0875","contributorId":2985,"corporation":false,"usgs":true,"family":"Jibson","given":"Randall","email":"jibson@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":583460,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harp, Edwin L. harp@usgs.gov","contributorId":1290,"corporation":false,"usgs":true,"family":"Harp","given":"Edwin","email":"harp@usgs.gov","middleInitial":"L.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":583461,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169098,"text":"70169098 - 2016 - Distribution of the Sonora Tiger Salamander (Ambystoma mavortium stebbinsi) in Mexico","interactions":[],"lastModifiedDate":"2016-06-29T11:13:15","indexId":"70169098","displayToPublicDate":"2016-06-29T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"title":"Distribution of the Sonora Tiger Salamander (Ambystoma mavortium stebbinsi) in Mexico","docAbstract":"The Sonoran Tiger Salamander (Ambystoma mavortium stebbinsi Lowe, 1954) was listed as federally endangered in the USA in 1997 (USFWS 1997). In the USA, the distribution of A. mavortium stebbinsi is limited to the San Rafael Valley (approximately 567 km2), between the Sierra San Antonio (called the Patagonia Mountains in Arizona) and Huachuca Mountains, and south of the Canelo Hills, Arizona (Fig. 1). The USA listing was triggered by loss of natural wetland habitats, threats from invasive predators, frequent die-offs from disease, introgression with the introduced Barred Tiger Salamander (A. mavortium mavortium), and small range and number of breeding sites that increases susceptibility to stochastic events (USFWS 1997). Small population sizes and limited gene flow have caused inbreeding, which may further reduce population viability and the potential for recovery (Jones et al. 1988; Storfer et al. 2014).
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More recently, a nonnative, invasive variety of Phragmites from Eurasia is rapidly invading wetlands across the continental United States and other parts of North America, where it negatively impacts humans and the environment. U.S. Geological Survey scientists, funded by the Great Lakes Restoration Initiative, are leading innovative efforts to improve management of nonnative Phragmites in the Great Lakes Basin.
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U.S. Geological Survey
1451 Green Rd.
Ann Arbor, MI 48105-2807
http:// http://www.glsc.usgs.gov