Prescribed fire is a widely used forest management tool, yet the long-term effectiveness of prescribed fire in reducing fuels and fire hazards in many vegetation types is not well documented. We assessed the magnitude and duration of reductions in surface fuels and modeled fire hazards in coniferous forests across nine U.S. national parks in California and the Colorado Plateau. We used observations from a prescribed fire effects monitoring program that feature standard forest and surface fuels inventories conducted pre-fire, immediately following an initial (first-entry) prescribed fire and at varying intervals up to >20 years post-fire. A subset of these plots was subjected to prescribed fire again (second-entry) with continued monitoring. Prescribed fire effects were highly variable among plots, but we found on average first-entry fires resulted in a significant post-fire reduction in surface fuels, with litter and duff fuels not returning to pre-fire levels over the length of our observations. Fine and coarse woody fuels often took a decade or longer to return to pre-fire levels. For second-entry fires we found continued fuels reductions, without strong evidence of fuel loads returning to levels observed immediately prior to second-entry fire. Following both first- and second-entry fire there were increases in estimated canopy base heights, along with reductions in estimated canopy bulk density and modeled flame lengths. We did not find evidence of return to pre-fire conditions during our observation intervals for these measures of fire hazard. Our results show that prescribed fire can be a valuable tool to reduce fire hazards and, depending on forest conditions and the measurement used, reductions in fire hazard can last for decades. Second-entry prescribed fire appeared to reinforce the reduction in fuels and fire hazard from first-entry fires.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2016.07.028","usgsCitation":"van Mantgem, P.J., Lalemand, L., Keifer, M., and Kane, J., 2016, Duration of fuels reduction following prescribed fire in coniferous forests of U.S. national parks in California and the Colorado Plateau: Forest Ecology and Management, v. 379, p. 265-272, https://doi.org/10.1016/j.foreco.2016.07.028.","productDescription":"8 p.","startPage":"265","endPage":"272","ipdsId":"IP-075251","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":328155,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"379","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c9431de4b0f2f0cec13571","contributors":{"authors":[{"text":"van Mantgem, Phillip J. 0000-0002-3068-9422 pvanmantgem@usgs.gov","orcid":"https://orcid.org/0000-0002-3068-9422","contributorId":2838,"corporation":false,"usgs":true,"family":"van Mantgem","given":"Phillip","email":"pvanmantgem@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":647729,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lalemand, Laura 0000-0001-8025-5975 llalemand@usgs.gov","orcid":"https://orcid.org/0000-0001-8025-5975","contributorId":174212,"corporation":false,"usgs":true,"family":"Lalemand","given":"Laura","email":"llalemand@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":647730,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keifer, MaryBeth","contributorId":21841,"corporation":false,"usgs":true,"family":"Keifer","given":"MaryBeth","affiliations":[],"preferred":false,"id":647731,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kane, Jeffrey M.","contributorId":35169,"corporation":false,"usgs":true,"family":"Kane","given":"Jeffrey M.","affiliations":[],"preferred":false,"id":647732,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209673,"text":"70209673 - 2016 - Highly conductive horizons in the Mesoproterozoic Belt-Purcell Basin: Sulfidic early basin strata as key markers of Cordilleran shortening and Eocene extension","interactions":[],"lastModifiedDate":"2020-04-21T14:45:32.418007","indexId":"70209673","displayToPublicDate":"2016-09-01T09:45:09","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Highly conductive horizons in the Mesoproterozoic Belt-Purcell Basin: Sulfidic early basin strata as key markers of Cordilleran shortening and Eocene extension","docAbstract":"We investigated the crustal structure of the central Mesoproterozoic Belt Basin in northwestern Montana and northern Idaho using a crustal resistivity section derived from a transect of new short- and long-period magnetotelluric (MT) stations. Two- and three-dimensional resistivity models were generated from these data in combination with data collected previously along three parallel short-period MT profiles and from EarthScope MT stations. The models were interpreted together with coincident deep seismic-reflection data collected during the Consortium for Continental Reflection Profiling (COCORP) program. The upper-crustal portion of the resistivity model correlates well with the mapped surface geology and reveals a three-layer resistivity stratigraphy, best expressed beneath the axis of the Libby syncline. Prominent features in the resistivity models are thick conductive horizons that serve as markers in reconstructing the disrupted basin stratigraphy. The uppermost unit (up to 5 km thick), consisting of all of the Belt Supergroup above the Prichard Formation, is highly resistive (1000–10,000 Ω·m) and has relatively low seismic layer velocities. The intermediate unit (up to 7 km thick) consists of the exposed Prichard Formation and 3+ km of stratigraphy below the deepest stratigraphic exposures of the unit. The intermediate unit has low to moderate resistivity (30–200 Ω·m), relatively high seismic velocities, and high seismic reflectivity, with the latter two characteristics resulting from an abundance of thick syndepositional mafic sills. The lowest unit (5–10 km thick) is nowhere exposed but underlies the intermediate unit and has very high conductivity (4–8 Ω·m) and intermediate seismic velocities. This 17–22-km-thick three-layer stratigraphy is repeated below the Libby syncline, with a base at ~37 km depth. Seismic layer velocities indicate high mantle-like velocities below 37 km beneath the Libby syncline. The continuous high-conductivity layer in the lower repeated section is apparently displaced ~26 km to the east above a low-angle normal fault inferred to be the downdip continuation of the Eocene, east-dipping Purcell Trench detachment fault. Reversal of that and other Eocene displacements reveals a >50-km-thick crustal section at late Paleocene time. Further reversal of apparent thrust displacements of the three-layer stratigraphy along the Lewis, Pinkham, Libby, and Moyie thrusts allows construction of a restored cross section prior to the onset of Cordilleran thrusting in the Jurassic. A total of ~220 km of Jurassic–Paleocene shortening along these faults is indicated. The enhanced conductivity within the lowest (unexposed) Belt stratigraphic unit is primarily attributed to one or more horizons of laminated metallic sulfides; graphite, though not described within the Belt Supergroup, may also contribute to the enhanced conductivity of the lowest stratigraphic unit. A narrow conductive horizon observed within the Prichard Formation in the eastern part of the transect correlates with the stratigraphic position of the world-class Sullivan sedimentary exhalative massive sulfide deposit in southern British Columbia, and it may represent a distal sulfide blanket deposit broadly dispersed across the Belt Basin. By analogy, the thick conductive sub–Prichard Formation unit may represent repeated sulfide depositional events within the early rift history of the basin, potentially driven by hydrothermal fluids released during basaltic underplating of attenuated continental crust.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Belt basin: Window to Mesoproterozoic Earth","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2016.2522(12)","collaboration":"","usgsCitation":"Bedrosian, P.A., and Box, S.E., 2016, Highly conductive horizons in the Mesoproterozoic Belt-Purcell Basin: Sulfidic early basin strata as key markers of Cordilleran shortening and Eocene extension, chap. of Belt basin: Window to Mesoproterozoic Earth, v. 522, p. 305-339, https://doi.org/10.1130/2016.2522(12).","productDescription":"36 p.","startPage":"305","endPage":"339","ipdsId":"IP-058401","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":470598,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/2016.2522(12)","text":"Publisher Index Page"},{"id":374153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, British Columbia, Idaho, Montana, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.14672851562499,\n 45.034714778688624\n ],\n [\n -110.775146484375,\n 45.034714778688624\n ],\n [\n -110.775146484375,\n 50.15578588538455\n ],\n [\n -119.14672851562499,\n 50.15578588538455\n ],\n [\n -119.14672851562499,\n 45.034714778688624\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"522","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":787470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Box, Stephen E. 0000-0002-5268-8375 sbox@usgs.gov","orcid":"https://orcid.org/0000-0002-5268-8375","contributorId":1843,"corporation":false,"usgs":true,"family":"Box","given":"Stephen","email":"sbox@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":787471,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195835,"text":"70195835 - 2016 - Estimating microcystin levels at recreational sites in western Lake Erie and Ohio","interactions":[],"lastModifiedDate":"2018-03-07T10:40:01","indexId":"70195835","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"title":"Estimating microcystin levels at recreational sites in western Lake Erie and Ohio","docAbstract":"Cyanobacterial harmful algal blooms (cyanoHABs) and associated toxins, such as microcystin, are a major global water-quality issue. Water-resource managers need tools to quickly predict when and where toxin-producing cyanoHABs will occur. This could be done by using site-specific models that estimate the potential for elevated toxin concentrations that cause public health concerns. With this study, samples were collected at three Ohio lakes to identify environmental and water-quality factors to develop linear-regression models to estimate microcystin levels. Measures of the algal community (phycocyanin, cyanobacterial biovolume, and cyanobacterial gene concentrations) and pH were most strongly correlated with microcystin concentrations. Cyanobacterial genes were quantified for general cyanobacteria, general Microcystis and Dolichospermum, and for microcystin synthetase (mcyE) for Microcystis, Dolichospermum, and Planktothrix. For phycocyanin, the relations were different between sites and were different between hand-held measurements on-site and nearby continuous monitor measurements for the same site. Continuous measurements of parameters such as phycocyanin, pH, and temperature over multiple days showed the highest correlations to microcystin concentrations. The development of models with high R2values (0.81–0.90), sensitivities (92%), and specificities (100%) for estimating microcystin concentrations above or below the Ohio Recreational Public Health Advisory level of 6 μg L−1 was demonstrated for one site; these statistics may change as more data are collected in subsequent years. This study showed that models could be developed for estimates of exceeding a microcystin threshold concentration at a recreational freshwater lake site, with potential to expand their use to provide relevant public health information to water resource managers and the public for both recreational and drinking waters.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.hal.2016.07.003","usgsCitation":"Francy, D.S., Brady, A.M., Ecker, C.D., Graham, J.L., Stelzer, E.A., Struffolino, P., and Loftin, K.A., 2016, Estimating microcystin levels at recreational sites in western Lake Erie and Ohio: Harmful Algae, v. 58, p. 23-34, https://doi.org/10.1016/j.hal.2016.07.003.","productDescription":"12 p.","startPage":"23","endPage":"34","ipdsId":"IP-068433","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":352264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Lake Erie","volume":"58","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee98be4b0da30c1bfc568","contributors":{"authors":[{"text":"Francy, Donna S. 0000-0001-9229-3557 dsfrancy@usgs.gov","orcid":"https://orcid.org/0000-0001-9229-3557","contributorId":1853,"corporation":false,"usgs":true,"family":"Francy","given":"Donna","email":"dsfrancy@usgs.gov","middleInitial":"S.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brady, Amie M.G. 0000-0002-7414-0992 amgbrady@usgs.gov","orcid":"https://orcid.org/0000-0002-7414-0992","contributorId":2544,"corporation":false,"usgs":true,"family":"Brady","given":"Amie","email":"amgbrady@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730222,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ecker, Christopher D. 0000-0003-0353-5855 cdecker@usgs.gov","orcid":"https://orcid.org/0000-0003-0353-5855","contributorId":149530,"corporation":false,"usgs":true,"family":"Ecker","given":"Christopher","email":"cdecker@usgs.gov","middleInitial":"D.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":730221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730220,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stelzer, Erin A. 0000-0001-7645-7603 eastelzer@usgs.gov","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":1933,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin","email":"eastelzer@usgs.gov","middleInitial":"A.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730224,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Struffolino, Pamela","contributorId":202922,"corporation":false,"usgs":false,"family":"Struffolino","given":"Pamela","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":730219,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":730223,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70170460,"text":"ds987 - 2016 - Groundwater-quality data in the Monterey–Salinas shallow aquifer study unit, 2013: Results from the California GAMA Program","interactions":[],"lastModifiedDate":"2017-01-18T09:45:02","indexId":"ds987","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"987","title":"Groundwater-quality data in the Monterey–Salinas shallow aquifer study unit, 2013: Results from the California GAMA Program","docAbstract":"Groundwater quality in the 3,016-square-mile Monterey–Salinas Shallow Aquifer study unit was investigated by the U.S. Geological Survey (USGS) from October 2012 to May 2013 as part of the California State Water Resources Control Board Groundwater Ambient Monitoring and Assessment (GAMA) Program’s Priority Basin Project. The GAMA Monterey–Salinas Shallow Aquifer study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the shallow-aquifer systems in parts of Monterey and San Luis Obispo Counties and to facilitate statistically consistent comparisons of untreated-groundwater quality throughout California. The shallow-aquifer system in the Monterey–Salinas Shallow Aquifer study unit was defined as those parts of the aquifer system shallower than the perforated depth intervals of public-supply wells, which generally corresponds to the part of the aquifer system used by domestic wells. Groundwater quality in the shallow aquifers can differ from the quality in the deeper water-bearing zones; shallow groundwater can be more vulnerable to surficial contamination.
Samples were collected from 170 sites that were selected by using a spatially distributed, randomized grid-based method. The study unit was divided into 4 study areas, each study area was divided into grid cells, and 1 well was sampled in each of the 100 grid cells (grid wells). The grid wells were domestic wells or wells with screen depths similar to those in nearby domestic wells. A greater spatial density of data was achieved in 2 of the study areas by dividing grid cells in those study areas into subcells, and in 70 subcells, samples were collected from exterior faucets at sites where there were domestic wells or wells with screen depths similar to those in nearby domestic wells (shallow-well tap sites).
Field water-quality indicators (dissolved oxygen, water temperature, pH, and specific conductance) were measured, and samples for analysis of inorganic constituents (trace elements, nutrients, major and minor ions, silica, total dissolved solids, and alkalinity) were collected at all 170 sites. In addition to these constituents, the samples from grid wells were analyzed for organic constituents (volatile organic compounds, pesticides and pesticide degradates), constituents of special interest (perchlorate and N-nitrosodimethylamine, or NDMA), radioactive constituents (radon-222 and gross-alpha and gross-beta radioactivity), and geochemical and age-dating tracers (stable isotopes of carbon in dissolved inorganic carbon, carbon-14 abundances, stable isotopes of hydrogen and oxygen in water, and tritium activities).
Three types of quality-control samples (blanks, replicates, and matrix spikes) were collected at up to 11 percent of the wells in the Monterey–Salinas Shallow Aquifer study unit, and the results for these samples were used to evaluate the quality of the data from the groundwater samples. With the exception of trace elements, blanks rarely contained detectable concentrations of any constituent, indicating that contamination from sample-collection procedures was not a significant source of bias in the data for the groundwater samples. Low concentrations of some trace elements were detected in blanks; therefore, the data were re-censored at higher reporting levels. Replicate samples generally were within the limits of acceptable analytical reproducibility. The median values of matrix-spike recoveries were within the acceptable range (70 to 130 percent) for the volatile organic compounds (VOCs) and N-nitrosodimethylamine (NDMA), but were only approximately 64 percent for pesticides and pesticide degradates.
The sample-collection protocols used in this study were designed to obtain representative samples of groundwater. The quality of groundwater can differ from the quality of drinking water because water chemistry can change as a result of contact with plumbing systems or the atmosphere; because of treatment, disinfection, or blending with water from other sources; or some combination of these. Water quality in domestic wells is not regulated in California, however, to provide context for the water-quality data presented in this report, results were compared to benchmarks established for drinking-water quality. The primary comparison benchmarks were maximum contaminant levels established by the U.S. Environmental Protection Agency and the State of California (MCL-US and MCL-CA, respectively). Non-regulatory benchmarks were used for constituents without maximum contaminant levels (MCLs), including Health
Based Screening Levels (HBSLs) developed by the USGS and State of California secondary maximum contaminant levels (SMCL-CA) and notification levels. Most constituents detected in samples from the Monterey–Salinas Shallow Aquifer study unit had concentrations less than their respective benchmarks.
Of the 148 organic constituents analyzed in the 100 grid-well samples, 38 were detected, and all concentrations were less than the benchmarks. Volatile organic compounds were detected in 26 of the grid wells, and pesticides and pesticide degradates were detected in 28 grid wells. The special-interest constituent NDMA was detected above the HBSL in three samples, one of which also had a perchlorate concentration greater than the MCL-CA.
Of the inorganic constituents, 6 were detected at concentrations above their respective MCL benchmarks in grid-well samples: arsenic (5 grid wells above the MCL of 10 micrograms per liter, μg/L), selenium (3 grid wells, MCL of 50 μg/L), uranium (4 grid wells, MCL of 30 μg/L), nitrate (16 grid wells, MCL of 10 milligrams per liter, mg/L), adjusted gross alpha particle activity (10 grid wells, MCL of 15 picocuries per liter, pCi/L), and gross beta particle activity (1 grid well, MCL of 50 pCi/L). An additional 4 inorganic constituents were detected at concentrations above their respective HBSL benchmarks in grid-well samples: boron (1 grid well above the HBSL of 6,000 μg/L), manganese (8 grid wells, HBSL of 300 μg/L), molybdenum (6 grid wells, HBSL of 40 μg/L), and strontium (6 grid wells, HBSL of 4,000 μg/L). Of the inorganic constituents, 4 were detected at concentrations above their non-health based SMCL benchmarks in grid-well samples: iron (9 grid wells above the SMCL of 300 μg/L), chloride (7 grid wells, SMCL of 500 mg/L), sulfate (14 grid wells, SMCL of 500 mg/L), and total dissolved solids (27 grid wells, SMCL of 1,000 mg/L).
Of the inorganic constituents analyzed in the 70 shallow-well tap sites, 10 were detected at concentrations above the benchmarks. Of the inorganic constituents, 3 were detected at concentrations above their respective MCL benchmarks in shallow-well tap sites: arsenic (2 shallow-well tap sites above the MCL of 10 μg/L), uranium (2 shallow-well tap sites, MCL of 30 μg/L), and nitrate (24 shallow-well tap sites, MCL of 10 mg/L). An additional 3 inorganic constituents were detected above their respective HBSL benchmarks in shallow-well tap sites: manganese (4 shallow-well tap sites above the HBSL of 300 μg/L), molybdenum (4 shallow-well tap sites, HBSL of 40 μg/L), and zinc (2 shallow-well tap sites, HBSL of 2,000 μg/L). Of the inorganic constituents, 4 were detected at concentrations above their non-health based SMCL benchmarks in shallow-well tap sites: iron (6 shallow-well tap sites above the SMCL of 300 μg/L), chloride (1 shallow-well tap site, SMCL of 500 mg/L), sulfate (9 shallow-well tap sites, SMCL of 500 mg/L), and total dissolved solids (15 shallow-well tap sites, SMCL of 1,000 mg/L).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds987","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Goldrath, D.A., Kulongoski, J.T., and Davis, T.A., 2015, Groundwater-quality data in the Monterey–Salinas shallow aquifer study unit, (ver. 1.1, January 2017): Results from the California GAMA Program: U.S. Geological Survey Data Series 987, 132 p., https://dx.doi.org/10.3133/ds987.","productDescription":"ix, 132 p. ","numberOfPages":"146","onlineOnly":"Y","ipdsId":"IP-049716","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":333267,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/0987/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":328193,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0987/coverthb2.jpg"},{"id":328194,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0987/ds0987.pdf","text":"Report","size":"17.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 987"}],"country":"United States","state":"California ","otherGeospatial":"Monterey–Salinas Shallow Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.08282470703124,\n 36.96086580957587\n ],\n [\n -122.05261230468751,\n 36.9367208722872\n ],\n [\n -122.01690673828124,\n 36.94769679250732\n ],\n [\n -121.981201171875,\n 36.954281585675965\n ],\n [\n -121.9317626953125,\n 36.95647639022989\n ],\n [\n -121.88507080078125,\n 36.94111143010772\n ],\n [\n -121.85760498046875,\n 36.88181755936464\n ],\n [\n -121.827392578125,\n 36.82687474287728\n ],\n [\n -121.80816650390625,\n 36.78949107451841\n ],\n [\n -121.827392578125,\n 36.71687068791304\n ],\n [\n -121.85211181640625,\n 36.65079252503471\n ],\n [\n -121.871337890625,\n 36.62214102821768\n ],\n [\n -121.91802978515625,\n 36.64858894203172\n ],\n [\n -121.95648193359374,\n 36.64638529597495\n ],\n [\n -121.8878173828125,\n 36.59347887826919\n ],\n [\n -121.80816650390625,\n 36.619936625629215\n ],\n [\n -121.75872802734375,\n 36.65079252503471\n ],\n [\n -121.58843994140625,\n 36.578041001498704\n ],\n [\n -121.30004882812499,\n 36.295204533693536\n ],\n [\n -121.11328124999999,\n 36.140092827322654\n ],\n [\n -120.84136962890625,\n 35.89572525865906\n ],\n [\n -120.80291748046874,\n 35.811131416437966\n ],\n [\n -120.794677734375,\n 35.708607653285505\n ],\n [\n -120.46234130859376,\n 35.5188142812306\n ],\n [\n -120.22338867187499,\n 35.42486791930558\n ],\n [\n -120.00640869140624,\n 35.33529320309331\n ],\n [\n -119.86633300781249,\n 35.290468565908775\n ],\n [\n -119.76470947265625,\n 35.3285710912542\n ],\n [\n -119.674072265625,\n 35.250105158539355\n ],\n [\n -119.5806884765625,\n 35.191766965947394\n ],\n [\n -119.4873046875,\n 35.10193405724606\n ],\n [\n -119.43237304687499,\n 35.05922870088872\n ],\n [\n -119.29229736328126,\n 35.02099970111467\n ],\n [\n -119.07531738281251,\n 35.007502842952896\n ],\n [\n -119.02587890624999,\n 35.0502352513963\n ],\n [\n -119.02862548828125,\n 35.11766197360177\n ],\n [\n -119.05334472656249,\n 35.18952235197259\n ],\n [\n -119.25933837890624,\n 35.28374272801905\n ],\n [\n -119.43237304687499,\n 35.411438052435464\n ],\n [\n -119.49005126953124,\n 35.49198366469642\n ],\n [\n -119.65484619140625,\n 35.54116627999815\n ],\n [\n -119.91577148437499,\n 35.69522525087309\n ],\n [\n -120.09979248046874,\n 35.70414710206052\n ],\n [\n -120.24261474609374,\n 35.72421761691415\n ],\n [\n -120.28930664062499,\n 35.86456960744962\n ],\n [\n -120.9320068359375,\n 36.20660692859011\n ],\n [\n -121.13525390625,\n 36.575835338491764\n ],\n [\n -121.4813232421875,\n 36.85325222344018\n ],\n [\n -121.63238525390626,\n 36.901587303978474\n ],\n [\n -121.76422119140625,\n 36.97183825093165\n ],\n [\n -121.82464599609375,\n 37.00035919622158\n ],\n [\n -121.92626953124999,\n 37.00913272027146\n ],\n [\n -122.04986572265624,\n 37.01351910258053\n ],\n [\n -122.08282470703124,\n 36.96086580957587\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: September 1, 2016; Version 1.1: January 7, 2017","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
Mandt's black guillemot (Cepphus grylle mandtii) is one of the few seabirds associated in all seasons with Arctic sea ice, a habitat that is changing rapidly. Recent decreases in summer ice have reduced breeding success and colony size of this species in Arctic Alaska. Little is known about the species' movements and distribution during the nine month non-breeding period (September–May), when changes in sea ice extent and composition are also occurring and predicted to continue. To examine bird movements and the seasonal role of sea ice to non-breeding Mandt's black guillemots, we deployed and recovered (n = 45) geolocators on individuals at a breeding colony in Arctic Alaska during 2011–2015. Black guillemots moved north to the marginal ice zone (MIZ) in the Beaufort and Chukchi seas immediately after breeding, moved south to the Bering Sea during freeze-up in December, and wintered in the Bering Sea January–April. Most birds occupied the MIZ in regions averaging 30–60% sea ice concentration, with little seasonal variation. Birds regularly roosted on ice in all seasons averaging 5 h d−1, primarily at night. By using the MIZ, with its roosting opportunities and associated prey, black guillemots can remain in the Arctic during winter when littoral waters are completely covered by ice.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rsbl.2016.0275","usgsCitation":"Divoky, G., Douglas, D.C., and Stenhouse, I.J., 2016, Arctic sea ice a major determinant in Mandt's black guillemot movement and distribution during non-breeding season: Biology Letters, v. 12, no. 9, Article 20160275, https://doi.org/10.1098/rsbl.2016.0275.","productDescription":"Article 20160275","ipdsId":"IP-074728","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":470608,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsbl.2016.0275","text":"Publisher Index Page"},{"id":341394,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591c0fc9e4b0a7fdb43ddef2","contributors":{"authors":[{"text":"Divoky, G.J.","contributorId":15971,"corporation":false,"usgs":true,"family":"Divoky","given":"G.J.","affiliations":[],"preferred":false,"id":695398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":695397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stenhouse, I. J.","contributorId":192075,"corporation":false,"usgs":false,"family":"Stenhouse","given":"I.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":695399,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188433,"text":"70188433 - 2016 - Synthesis and revision of the lithostratigraphic groups and formations in the Upper Permian?–Lower Jurassic Newark Supergroup of eastern North America","interactions":[],"lastModifiedDate":"2017-06-09T14:35:50","indexId":"70188433","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"Synthesis and revision of the lithostratigraphic groups and formations in the Upper Permian?–Lower Jurassic Newark Supergroup of eastern North America","docAbstract":"The Upper Permian? - Lower Jurassic Newark Supergroup of eastern North America has a strikingly uniform succession of lithologic units. This uniformity is seen regardless of whether these units are characterized on the basis of their lithostratigraphy, allostratigraphy, biostratigraphy, or chemostratigraphy. After deposition, these units were broken up tectonically and attacked erosionally; parts of them survive today only within localized, down-faulted areas. Many lines of evidence compellingly demonstrate that most or all of these remnant units once were physically continuous between remaining outcrops. It is needlessly confusing to give every remnant of each unit a different name in each area where it persists simply because it is now physically isolated by erosion from other portions of the same unit. Instead, these units should be defined within a regional lithostratigraphic framework that emphasizes their common origins and original stratigraphic continuity. To this end, the formation-level stratigraphy of the Newark Supergroup is reduced from 58 locally applied and locally defined formations to a succession of only 16 uniformly defined and regionally recognizable formations. In all cases the oldest name validly applied to each formation is given priority over more recently erected synonymous names, which are either abandoned or, in a few cases, changed in rank to a member of one of the formations recognized here. The Newark Supergroup is here organized into four regionally recognizable groups, each subdivided into regionally recognizable formations. In ascending order, the Upper Permian?-Middle Triassic Acadia Group (new name) includes the Honeycomb Point Formation, Chedabucto Formation, Economy Formation, and Evangeline Formation. This group is preserved only in the Canadian Fundy and Chedabucto basins. The Upper Triassic (Carnian-Norian) Chatham Group includes the Doswell Formation, Stockton Formation, Lockatong Formation, and Passaic Formation. The Upper Triassic-Lower Jurassic (upper Rhaetian-lower Hettangian) Meriden Group includes the Talcott Formation, Shuttle Meadow Formation, Holyoke Formation, East Berlin Formation, and Hampden Formation. The term \"Agawam Group,\" previously proposed to encompass all Newark Supergroup strata above the highest basalt of the Meriden Group, is here abandoned and replaced with the name \"Portland Group\" for the same suite of strata. The Lower Jurassic (upper Hettangian-lower Sinemurian) Portland Group includes a lower Boonton Formation, an overlying Longmeadow Sandstone (here reinstated), and the Mount Toby Conglomerate, which laterally intertongues with both the Boonton Formation and the Longmeadow Sandstone.
","language":"English","publisher":"Micropaleontology Press","usgsCitation":"Weems, R.E., Tanner, L.H., and Lucas, S.G., 2016, Synthesis and revision of the lithostratigraphic groups and formations in the Upper Permian?–Lower Jurassic Newark Supergroup of eastern North America: Stratigraphy, v. 13, no. 2, p. 111-153.","productDescription":"43 p.","startPage":"111","endPage":"153","ipdsId":"IP-070837","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":342344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":342332,"type":{"id":15,"text":"Index Page"},"url":"https://www.micropress.org/microaccess/stratigraphy/issue-326/article-1988"}],"volume":"13","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593bb3a1e4b0764e6c60e7b8","contributors":{"authors":[{"text":"Weems, Robert E. 0000-0002-1907-7804 rweems@usgs.gov","orcid":"https://orcid.org/0000-0002-1907-7804","contributorId":2663,"corporation":false,"usgs":true,"family":"Weems","given":"Robert","email":"rweems@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":697716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tanner, Lawrence H.","contributorId":192775,"corporation":false,"usgs":false,"family":"Tanner","given":"Lawrence","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":697717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lucas, Spencer G.","contributorId":192776,"corporation":false,"usgs":false,"family":"Lucas","given":"Spencer","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":697718,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187566,"text":"70187566 - 2016 - Land use effects on pesticides in sediments of prairie pothole wetlands in North and South Dakota","interactions":[],"lastModifiedDate":"2017-05-09T11:00:06","indexId":"70187566","displayToPublicDate":"2016-09-01T00:00:00","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":"Land use effects on pesticides in sediments of prairie pothole wetlands in North and South Dakota","docAbstract":"Prairie potholes are the dominant wetland type in the intensively cultivated northern Great Plains of North America, and thus have the potential to receive pesticide runoff and drift. We examined the presence of pesticides in sediments of 151 wetlands split among the three dominant land use types, Conservation Reserve Program (CRP), cropland, and native prairie, in North and South Dakota in 2011. Herbicides (glyphosate and atrazine) and fungicides were detected regularly, with no insecticide detections. Glyphosate was the most detected pesticide, occurring in 61% of all wetlands, with atrazine in only 8% of wetlands. Pyraclostrobin was one of five fungicides detected, but the only one of significance, being detected in 31% of wetlands. Glyphosate was the only pesticide that differed by land use, with concentrations in cropland over four-times that in either native prairie or CRP, which were equal in concentration and frequency of detection. Despite examining several landscape variables, such as wetland proximity to specific crop types, watershed size, and others, land use was the best variable explaining pesticide concentrations in potholes. CRP ameliorated glyphosate in wetlands at concentrations comparable to native prairie and thereby provides another ecosystem service from this expansive program.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.04.209","usgsCitation":"McMurry, S.T., Belden, J.B., Smith, L.M., Morrison, S.A., Daniel, D.W., Euliss, B.R., Euliss, N., Kensinger, B.J., and Tangen, B., 2016, Land use effects on pesticides in sediments of prairie pothole wetlands in North and South Dakota: Science of the Total Environment, v. 565, p. 682-689, https://doi.org/10.1016/j.scitotenv.2016.04.209.","productDescription":"8 p.","startPage":"682","endPage":"689","ipdsId":"IP-062716","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":462105,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.04.209","text":"Publisher Index Page"},{"id":340991,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota, South Dakota","volume":"565","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5912d537e4b0e541a03d4523","contributors":{"authors":[{"text":"McMurry, Scott T.","contributorId":191876,"corporation":false,"usgs":false,"family":"McMurry","given":"Scott","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":694581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belden, Jason B.","contributorId":191877,"corporation":false,"usgs":false,"family":"Belden","given":"Jason","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":694582,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Loren M.","contributorId":191878,"corporation":false,"usgs":false,"family":"Smith","given":"Loren","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":694583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morrison, Shane A.","contributorId":191879,"corporation":false,"usgs":false,"family":"Morrison","given":"Shane","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":694584,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Daniel, Dale W.","contributorId":191880,"corporation":false,"usgs":false,"family":"Daniel","given":"Dale","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":694585,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Euliss, Betty R.","contributorId":191881,"corporation":false,"usgs":false,"family":"Euliss","given":"Betty","email":"","middleInitial":"R.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":694586,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Euliss, Ned H. Jr.","contributorId":178233,"corporation":false,"usgs":false,"family":"Euliss","given":"Ned H. Jr.","affiliations":[],"preferred":false,"id":694587,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kensinger, Bart J.","contributorId":191882,"corporation":false,"usgs":false,"family":"Kensinger","given":"Bart","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":694588,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tangen, Brian 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":167277,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":694580,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70188438,"text":"70188438 - 2016 - Holocene climate changes in eastern Beringia (NW North America) – A systematic review of multi-proxy evidence","interactions":[],"lastModifiedDate":"2017-06-09T14:10:37","indexId":"70188438","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Holocene climate changes in eastern Beringia (NW North America) – A systematic review of multi-proxy evidence","docAbstract":"Reconstructing climates of the past relies on a variety of evidence from a large number of sites to capture the varied features of climate and the spatial heterogeneity of climate change. This review summarizes available information from diverse Holocene paleoenvironmental records across eastern Beringia (Alaska, westernmost Canada and adjacent seas), and it quantifies the primary trends of temperature- and moisture-sensitive records based in part on midges, pollen, and biogeochemical indicators (compiled in the recently published Arctic Holocene database, and updated here to v2.1). The composite time series from these proxy records are compared with new summaries of mountain-glacier and lake-level fluctuations, terrestrial water-isotope records, sea-ice and sea-surface-temperature analyses, and peatland and thaw-lake initiation frequencies to clarify multi-centennial- to millennial-scale trends in Holocene climate change. To focus the synthesis, the paleo data are used to frame specific questions that can be addressed with simulations by Earth system models to investigate the causes and dynamics of past and future climate change. This systematic review shows that, during the early Holocene (11.7–8.2 ka; 1 ka = 1000 cal yr BP), rather than a prominent thermal maximum as suggested previously, temperatures were highly variable, at times both higher and lower than present (approximate mid-20th-century average), with no clear spatial pattern. Composited pollen, midge and other proxy records average out the variability and show the overall lowest summer and mean-annual temperatures across the study region during the earliest Holocene, followed by warming over the early Holocene. The sparse data available on early Holocene glaciation show that glaciers in southern Alaska were as extensive then as they were during the late Holocene. Early Holocene lake levels were low in interior Alaska, but moisture indicators show pronounced differences across the region. The highest frequency of both peatland and thaw-lake initiation ages also occurred during the early Holocene. During the middle Holocene (8.2–4.2 ka), glaciers retreated as the regional average temperature increased to a maximum between 7 and 5 ka, as reflected in most proxy types. Following the middle Holocene thermal maximum, temperatures decreased starting between 4 and 3 ka, signaling the onset of Neoglacial cooling. Glaciers in the Brooks and Alaska Ranges advanced to their maximum Holocene extent as lakes generally rose to modern levels. Temperature differences for averaged 500-year time steps typically ranged by 1–2 °C for individual records in the Arctic Holocene database, with a transition to a cooler late Holocene that was neither abrupt nor spatially coherent. The longest and highest-resolution terrestrial water isotope records previously interpreted to represent changes in the Aleutian low-pressure system around this time are here shown to be largely contradictory. Furthermore, there are too few records with sufficient resolution to identify sub-centennial-scale climate anomalies, such as the 8.2 ka event. The review concludes by suggesting some priorities for future paleoclimate research in the region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2015.10.021","usgsCitation":"Kaufman, D.S., Axford, Y.L., Henderson, A.C., McKay, N.P., Oswald, W., Saenger, C., Anderson, R., Bailey, H.L., Clegg, B., Gajewski, K., Hu, F.S., Jones, M.C., Massa, C., Routson, C.C., Werner, A., Wooller, M.J., and Yu, Z., 2016, Holocene climate changes in eastern Beringia (NW North America) – A systematic review of multi-proxy evidence: Quaternary Science Reviews, v. 147, p. 312-339, https://doi.org/10.1016/j.quascirev.2015.10.021.","productDescription":"28 p.","startPage":"312","endPage":"339","ipdsId":"IP-068458","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":470606,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2015.10.021","text":"Publisher Index Page"},{"id":342340,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593bb3a0e4b0764e6c60e7b4","contributors":{"authors":[{"text":"Kaufman, Darrell S.","contributorId":192787,"corporation":false,"usgs":false,"family":"Kaufman","given":"Darrell","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":697736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Axford, Yarrow L.","contributorId":192788,"corporation":false,"usgs":false,"family":"Axford","given":"Yarrow","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":697737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henderson, Andrew C.G.","contributorId":192789,"corporation":false,"usgs":false,"family":"Henderson","given":"Andrew","email":"","middleInitial":"C.G.","affiliations":[],"preferred":false,"id":697738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKay, Nicolas P.","contributorId":192790,"corporation":false,"usgs":false,"family":"McKay","given":"Nicolas","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":697739,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oswald, W. 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Pollen-vegetation models and process-based models of dispersal typically assume stable relationships between source vegetation and corresponding pollen in surface sediments, as well as stable parameterizations of dispersal and productivity. These assumptions, however, are largely unevaluated. This paper reports a test of the stability of pollen-vegetation relationships using vegetation and pollen data from the Midwestern region of the United States, during a period of large changes in land use and vegetation driven by Euro-American settlement. We compared a dataset of pollen records for the early settlement-era with three other datasets of pollen and forest composition for two time periods: before Euro-American settlement, and the late 20th century. Results from generalized linear models for thirteen genera indicate that pollen-vegetation relationships significantly differ (p < 0.05) between pre-settlement and the modern era for several genera: Fagus, Betula, Tsuga, Quercus, Pinus, and Picea. The estimated pollen source radius for the 8 km gridded vegetation data and associated pollen data is 25–85 km, consistent with prior studies using similar methods and spatial resolutions.
Hence, the rapid changes in land cover associated with the Anthropocene affect the accuracy of ecological predictions for both the future and the past. In the Anthropocene, paleoecology should move beyond the assumption that pollen-vegetation relationships are stable over time. Multi-temporal calibration datasets are increasingly possible and enable paleoecologists to better understand the complex processes governing pollen-vegetation relationships through space and time.
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sand shinnery oak prairies with herbicide and grazing in New Mexico","docAbstract":"Sand shinnery oak (Quercus havardii) prairies are increasingly disappearing and increasingly degraded in the Southern High Plains of Texas and New Mexico. Restoring and managing sand shinnery oak prairie can support biodiversity, specific species of conservation concern, and livestock production. We measured vegetation response to four treatment combinations of herbicide (tebuthiuron applied at 0.60 kg/ha) and moderate-intensity grazing (50% removal of annual herbaceous production) over a 10-year period in a sand shinnery oak prairie of eastern New Mexico. We compared the annual vegetation response to the historical climax plant community (HCPC) as outlined by the U.S. Department of Agriculture Ecological Site Description. From 2 to 10 years postapplication, tebuthiuron-treated plots had reduced shrub cover with twice as much forb and grass cover as untreated plots. Tebuthiuron-treated plots, regardless of the presence of grazing, most frequently met HCPC. Tebuthiuron and moderate-intensity grazing increased vegetation heterogeneity and, based on comparison of the HCPC, successfully restored sand shinnery oak prairie to a vegetation composition similar to presettlement.
","language":"English","publisher":"Southwestern Association of Naturalists","doi":"10.1894/0038-4909-61.3.225","usgsCitation":"Zavaleta, J.C., Haukos, D.A., Grisham, B.A., Boal, C.W., and Dixon, C., 2016, Restoring sand shinnery oak prairies with herbicide and grazing in New Mexico: Southwestern Naturalist, v. 61, no. 3, p. 225-232, https://doi.org/10.1894/0038-4909-61.3.225.","productDescription":"8 p.","startPage":"225","endPage":"232","ipdsId":"IP-056147","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","volume":"61","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fcd5e4b06e28e9c2439a","contributors":{"authors":[{"text":"Zavaleta, Jennifer C.","contributorId":102785,"corporation":false,"usgs":true,"family":"Zavaleta","given":"Jennifer","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":723911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grisham, Blake A.","contributorId":75419,"corporation":false,"usgs":true,"family":"Grisham","given":"Blake","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":723912,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":723913,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dixon, Charles","contributorId":68203,"corporation":false,"usgs":true,"family":"Dixon","given":"Charles","email":"","affiliations":[],"preferred":false,"id":723914,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192911,"text":"70192911 - 2016 - Radiometric calibration updates to the Landsat collection","interactions":[],"lastModifiedDate":"2018-04-23T09:09:51","indexId":"70192911","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Radiometric calibration updates to the Landsat collection","docAbstract":"The Landsat Project is planning to implement a new collection management strategy for Landsat products generated at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The goal of the initiative is to identify a collection of consistently geolocated and radiometrically calibrated images across the entire Landsat archive that is readily suitable for time-series analyses. In order to perform an accurate land change analysis, the data from all Landsat sensors must be on the same radiometric scale. Landsat 7 Enhanced Thematic Mapper Plus (ETM+) is calibrated to a radiance standard and all previous sensors are cross-calibrated to its radiometric scale. Landsat 8 Operational Land Imager (OLI) is calibrated to both radiance and reflectance standards independently. The Landsat 8 OLI reflectance calibration is considered to be most accurate. To improve radiometric calibration accuracy of historical data, Landsat 1-7 sensors also need to be cross-calibrated to the OLI reflectance scale. Results of that effort, as well as other calibration updates including the absolute and relative radiometric calibration and saturated pixel replacement for Landsat 8 OLI and absolute calibration for Landsat 4 and 5 Thematic Mappers (TM), will be implemented into Landsat products during the archive reprocessing campaign planned within the new collection management strategy. This paper reports on the planned radiometric calibration updates to the solar reflective bands of the new Landsat collection.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings Volume 9972, Earth Observing Systems XXI","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Society of Photo-Optical Instrumentation Engineers","doi":"10.1117/12.2239426","usgsCitation":"Micijevic, E., Haque, O., and Mishra, N., 2016, Radiometric calibration updates to the Landsat collection, in Proceedings Volume 9972, Earth Observing Systems XXI, v. 9972, 12 p., https://doi.org/10.1117/12.2239426.","productDescription":"12 p.","ipdsId":"IP-079592","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":350127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9972","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fcd5e4b06e28e9c24393","contributors":{"authors":[{"text":"Micijevic, Esad 0000-0002-3828-9239 emicijevic@usgs.gov","orcid":"https://orcid.org/0000-0002-3828-9239","contributorId":3075,"corporation":false,"usgs":true,"family":"Micijevic","given":"Esad","email":"emicijevic@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haque, Obaidul 0000-0002-0914-1446 ohaque@usgs.gov","orcid":"https://orcid.org/0000-0002-0914-1446","contributorId":4691,"corporation":false,"usgs":true,"family":"Haque","given":"Obaidul","email":"ohaque@usgs.gov","affiliations":[{"id":40546,"text":"KBR, Contractor to the USGS Earth Resources Observation and Science (EROS) Center","active":true,"usgs":false}],"preferred":true,"id":717347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mishra, Nischal nischal.mishra.ctr@usgs.gov","contributorId":198842,"corporation":false,"usgs":true,"family":"Mishra","given":"Nischal","email":"nischal.mishra.ctr@usgs.gov","affiliations":[],"preferred":false,"id":717348,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192912,"text":"70192912 - 2016 - Landsat-7 ETM+ radiometric calibration status","interactions":[],"lastModifiedDate":"2017-12-20T10:56:58","indexId":"70192912","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Landsat-7 ETM+ radiometric calibration status","docAbstract":"Now in its 17th year of operation, the Enhanced Thematic Mapper + (ETM+), on board the Landsat-7 satellite, continues to systematically acquire imagery of the Earth to add to the 40+ year archive of Landsat data. Characterization of the ETM+ on-orbit radiometric performance has been on-going since its launch in 1999. The radiometric calibration of the reflective bands is still monitored using on-board calibration devices, though the Pseudo-Invariant Calibration Sites (PICS) method has proven to be an effective tool as well. The calibration gains were updated in April 2013 based primarily on PICS results, which corrected for a change of as much as -0.2%/year degradation in the worst case bands. A new comparison with the SADE database of PICS results indicates no additional degradation in the updated calibration. PICS data are still being tracked though the recent trends are not well understood. The thermal band calibration was updated last in October 2013 based on a continued calibration effort by NASA/Jet Propulsion Lab and Rochester Institute of Technology. The update accounted for a 0.036 W/m2 sr μm or 0.26K at 300K bias error. The updated lifetime trend is now stable to within +/- 0.4K.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings Volume 9972, Earth Observing Systems XXI","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"SPIE","doi":"10.1117/12.2238625","usgsCitation":"Barsi, J.A., Markham, B.L., Czapla-Myers, J.S., Helder, D.L., Hook, S., Schott, J.R., and Haque, O., 2016, Landsat-7 ETM+ radiometric calibration status, in Proceedings Volume 9972, Earth Observing Systems XXI, v. 9972, https://doi.org/10.1117/12.2238625.","ipdsId":"IP-079294","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470629,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://doi.org/10.1117/12.2238625","text":"External Repository"},{"id":350125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9972","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fcd4e4b06e28e9c24390","contributors":{"authors":[{"text":"Barsi, Julia A.","contributorId":71822,"corporation":false,"usgs":false,"family":"Barsi","given":"Julia","email":"","middleInitial":"A.","affiliations":[{"id":12721,"text":"NASA GSFC SSAI","active":true,"usgs":false}],"preferred":false,"id":725247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Markham, Brian L.","contributorId":90482,"corporation":false,"usgs":false,"family":"Markham","given":"Brian","email":"","middleInitial":"L.","affiliations":[{"id":12721,"text":"NASA GSFC SSAI","active":true,"usgs":false}],"preferred":false,"id":725248,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Czapla-Myers, J. S.","contributorId":101968,"corporation":false,"usgs":true,"family":"Czapla-Myers","given":"J.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":725249,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Helder, Dennis L.","contributorId":105613,"corporation":false,"usgs":true,"family":"Helder","given":"Dennis","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":725250,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hook, Simon","contributorId":150339,"corporation":false,"usgs":false,"family":"Hook","given":"Simon","affiliations":[{"id":7218,"text":"California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":725251,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schott, John R.","contributorId":199175,"corporation":false,"usgs":false,"family":"Schott","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":725252,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haque, Obaidul 0000-0002-0914-1446 ohaque@usgs.gov","orcid":"https://orcid.org/0000-0002-0914-1446","contributorId":4691,"corporation":false,"usgs":true,"family":"Haque","given":"Obaidul","email":"ohaque@usgs.gov","affiliations":[{"id":40546,"text":"KBR, Contractor to the USGS Earth Resources Observation and Science (EROS) Center","active":true,"usgs":false}],"preferred":true,"id":717349,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192761,"text":"70192761 - 2016 - Toxicity of potassium chloride to veliger and byssal stage dreissenid mussels related to water quality","interactions":[],"lastModifiedDate":"2017-11-07T14:58:56","indexId":"70192761","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Toxicity of potassium chloride to veliger and byssal stage dreissenid mussels related to water quality","docAbstract":"Natural resource managers are seeking appropriate chemical eradication and control protocols for infestations of zebra mussels, Dreissena polymorpha (Pallas, 1769), and quagga mussels. D. rostiformis bugensis (Andrusov, 1897) that have limited effect on non-target species. Applications of low concentrations of potassium salt (as potash) have shown promise for use where the infestation and treatment can be contained or isolated. To further our understanding of such applications and obtain data that could support a pesticide registration, we conducted studies of the acute and chronic toxicity of potassium chloride to dreissenid mussels in four different water sources from infested and non-infested locations (ground water from northern Idaho, surface water from the Snake River, Idaho, USA, surface water from Lake Ontario, Ontario, Canada, and surface water from the Colorado River, Arizona, USA). We found short term exposure of veligers (< 24 h) to concentrations of 960 mg/L KCl produced rapid mortality in water from three locations, but veligers tested in Colorado River water were resistant. We used probit models to compare the mortality responses, predicted median lethal times and 95% confidence intervals. In separate experiments, we explored the sensitivity of byssal stage mussels in chronic exposures (>29 d) at concentrations of 100 and 200 mg/L KCl. Rapid mortality occurred within 10 d of exposure to concentrations of 200 mg/L KCl, regardless of water source. Kaplan-Meier estimates of mean survival of byssal mussels in 100 mg/L KCl prepared in surface water from Idaho and Lake Ontario were 4.9 or 6.9 d, respectively; however, mean survival of mussels tested in the Colorado River water was > 23 d. The sodium content of the Colorado River water was nearly three times that measured in waters from the other locations, and we hypothesized sodium concentrations may affect mussel survival. To test our hypothesis, we supplemented Snake River and Lake Ontario water with NaCl to equivalent conductivity as the Colorado River, and found mussel survival increased to levels observed in tests of veliger and byssal mussels in Colorado River water. We recommend KCl disinfection and eradication protocols must be developed to carefully consider the water quality characteristics of treatment locations.
","language":"English","publisher":"REABIC","doi":"10.3391/mbi.2016.7.3.05","usgsCitation":"Moffitt, C.M., Stockton-Fiti, K.A., and Claudi, R., 2016, Toxicity of potassium chloride to veliger and byssal stage dreissenid mussels related to water quality: Management of Biological Invasions, v. 7, no. 3, p. 257-268, https://doi.org/10.3391/mbi.2016.7.3.05.","productDescription":"12 p.","startPage":"257","endPage":"268","ipdsId":"IP-073121","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470626,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2016.7.3.05","text":"Publisher Index Page"},{"id":348406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e9dbe4b09af898c8cc5c","contributors":{"authors":[{"text":"Moffitt, Christine M. 0000-0001-6020-9728 cmoffitt@usgs.gov","orcid":"https://orcid.org/0000-0001-6020-9728","contributorId":2583,"corporation":false,"usgs":true,"family":"Moffitt","given":"Christine","email":"cmoffitt@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stockton-Fiti, Kelly A.","contributorId":200103,"corporation":false,"usgs":false,"family":"Stockton-Fiti","given":"Kelly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":721003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Claudi, Renata","contributorId":171420,"corporation":false,"usgs":false,"family":"Claudi","given":"Renata","email":"","affiliations":[{"id":26908,"text":"RNT Consulting Inc., Canada","active":true,"usgs":false}],"preferred":false,"id":721004,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192660,"text":"70192660 - 2016 - A global review of freshwater crayfish temperature tolerance, preference, and optimal growth","interactions":[],"lastModifiedDate":"2017-11-27T11:38:49","indexId":"70192660","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3278,"text":"Reviews in Fish Biology and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"A global review of freshwater crayfish temperature tolerance, preference, and optimal growth","docAbstract":"Conservation efforts, environmental planning, and management must account for ongoing ecosystem alteration due to a changing climate, introduced species, and shifting land use. This type of management can be facilitated by an understanding of the thermal ecology of aquatic organisms. However, information on thermal ecology for entire taxonomic groups is rarely compiled or summarized, and reviews of the science can facilitate its advancement. Crayfish are one of the most globally threatened taxa, and ongoing declines and extirpation could have serious consequences on aquatic ecosystem function due to their significant biomass and ecosystem roles. Our goal was to review the literature on thermal ecology for freshwater crayfish worldwide, with emphasis on studies that estimated temperature tolerance, temperature preference, or optimal growth. We also explored relationships between temperature metrics and species distributions. We located 56 studies containing information for at least one of those three metrics, which covered approximately 6 % of extant crayfish species worldwide. Information on one or more metrics existed for all 3 genera of Astacidae, 4 of the 12 genera of Cambaridae, and 3 of the 15 genera of Parastacidae. Investigations employed numerous methodological approaches for estimating these parameters, which restricts comparisons among and within species. The only statistically significant relationship we observed between a temperature metric and species range was a negative linear relationship between absolute latitude and optimal growth temperature. We recommend expansion of studies examining the thermal ecology of freshwater crayfish and identify and discuss methodological approaches that can improve standardization and comparability among studies.
","language":"English","publisher":"Springer","doi":"10.1007/s11160-016-9430-5","usgsCitation":"Westhoff, J.T., and Rosenberger, A.E., 2016, A global review of freshwater crayfish temperature tolerance, preference, and optimal growth: Reviews in Fish Biology and Fisheries, v. 26, no. 3, p. 329-349, https://doi.org/10.1007/s11160-016-9430-5.","productDescription":"21 p.","startPage":"329","endPage":"349","ipdsId":"IP-069980","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349354,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-14","publicationStatus":"PW","scienceBaseUri":"5a60fcd5e4b06e28e9c24396","contributors":{"authors":[{"text":"Westhoff, Jacob T.","contributorId":58106,"corporation":false,"usgs":true,"family":"Westhoff","given":"Jacob","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":723539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":716669,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191809,"text":"70191809 - 2016 - Panarchy use in environmental science for risk and resilience planning","interactions":[],"lastModifiedDate":"2017-10-18T11:10:57","indexId":"70191809","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5016,"text":"Environment Systems and Decisions","active":true,"publicationSubtype":{"id":10}},"title":"Panarchy use in environmental science for risk and resilience planning","docAbstract":"Environmental sciences have an important role in informing sustainable management of built environments by providing insights about the drivers and potentially negative impacts of global environmental change. Here, we discuss panarchy theory, a multi-scale hierarchical concept that accounts for the dynamism of complex socio-ecological systems, especially for those systems with strong cross-scale feedbacks. The idea of panarchy underlies much of system resilience, focusing on how systems respond to known and unknown threats. Panarchy theory can provide a framework for qualitative and quantitative research and application in the environmental sciences, which can in turn inform the ongoing efforts in socio-technical resilience thinking and adaptive and transformative approaches to management.
","language":"English","publisher":"Springer","doi":"10.1007/s10669-016-9605-6","usgsCitation":"Angeler, D., Allen, C.R., Garmestani, A.S., Gunderson, L.H., and Linkov, I., 2016, Panarchy use in environmental science for risk and resilience planning: Environment Systems and Decisions, v. 36, no. 3, p. 225-228, https://doi.org/10.1007/s10669-016-9605-6.","productDescription":"4 p.","startPage":"225","endPage":"228","ipdsId":"IP-076511","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470607,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10669-016-9605-6","text":"Publisher Index Page"},{"id":346837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-02","publicationStatus":"PW","scienceBaseUri":"59e86838e4b05fe04cd4d214","contributors":{"authors":[{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":713272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":713212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garmestani, Ahjond S.","contributorId":77285,"corporation":false,"usgs":true,"family":"Garmestani","given":"Ahjond","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":713273,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunderson, Lance H.","contributorId":12182,"corporation":false,"usgs":true,"family":"Gunderson","given":"Lance","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":713274,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Linkov, Igor","contributorId":172407,"corporation":false,"usgs":false,"family":"Linkov","given":"Igor","email":"","affiliations":[],"preferred":false,"id":713275,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192982,"text":"70192982 - 2016 - Estimating the effects of 17α-ethinylestradiol on stochastic population growth rate of fathead minnows: a population synthesis of empirically derived vital rates","interactions":[],"lastModifiedDate":"2018-03-26T11:39:57","indexId":"70192982","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the effects of 17α-ethinylestradiol on stochastic population growth rate of fathead minnows: a population synthesis of empirically derived vital rates","docAbstract":"Urban freshwater streams in arid climates are wastewater effluent dominated ecosystems particularly impacted by bioactive chemicals including steroid estrogens that disrupt vertebrate reproduction. However, more understanding of the population and ecological consequences of exposure to wastewater effluent is needed. We used empirically derived vital rate estimates from a mesocosm study to develop a stochastic stage-structured population model and evaluated the effect of 17α-ethinylestradiol (EE2), the estrogen in human contraceptive pills, on fathead minnow Pimephales promelas stochastic population growth rate. Tested EE2 concentrations ranged from 3.2 to 10.9 ng L−1 and produced stochastic population growth rates (λ S ) below 1 at the lowest concentration, indicating potential for population decline. Declines in λ S compared to controls were evident in treatments that were lethal to adult males despite statistically insignificant effects on egg production and juvenile recruitment. In fact, results indicated that λ S was most sensitive to the survival of juveniles and female egg production. More broadly, our results document that population model results may differ even when empirically derived estimates of vital rates are similar among experimental treatments, and demonstrate how population models integrate and project the effects of stressors throughout the life cycle. Thus, stochastic population models can more effectively evaluate the ecological consequences of experimentally derived vital rates.
","language":"English","publisher":"Springer","doi":"10.1007/s10646-016-1688-9","usgsCitation":"Schwindt, A.R., and Winkelman, D.L., 2016, Estimating the effects of 17α-ethinylestradiol on stochastic population growth rate of fathead minnows: a population synthesis of empirically derived vital rates: Ecotoxicology, v. 25, no. 7, p. 1364-1375, https://doi.org/10.1007/s10646-016-1688-9.","productDescription":"12 p.","startPage":"1364","endPage":"1375","ipdsId":"IP-057272","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-02","publicationStatus":"PW","scienceBaseUri":"5a07e9dae4b09af898c8cc5a","contributors":{"authors":[{"text":"Schwindt, Adam R.","contributorId":173697,"corporation":false,"usgs":false,"family":"Schwindt","given":"Adam","email":"","middleInitial":"R.","affiliations":[{"id":25665,"text":"Oregon State University, Corvallis, Oregon","active":true,"usgs":false}],"preferred":false,"id":720901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":717527,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193141,"text":"70193141 - 2016 - Nesting ecology of Whimbrels in boreal Alaska","interactions":[],"lastModifiedDate":"2017-11-21T13:43:44","indexId":"70193141","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5557,"text":"Wader Study","active":true,"publicationSubtype":{"id":10}},"title":"Nesting ecology of Whimbrels in boreal Alaska","docAbstract":"Breeding ecology studies of boreal waders have been relatively scarce in North America. This paucity is due in part to boreal habitats being difficult to access, and boreal waders being widely dispersed and thus difficult to monitor. Between 2008 and 2014 we studied the nesting ecology of Whimbrels Numenius phaeopus hudsonicus in interior Alaska, a region characterized by an active wildfire regime. Our objectives were to (1) describe the nesting ecology of Whimbrels in tundra patches within the boreal forest, (2) assess the influence of habitat features at multiple scales on nest-site selection, and (3) characterize factors affecting nest survival. Whimbrels nested in the largest patches and exhibited a consistently compressed annual breeding schedule. We hypothesized that these Whimbrels would exhibit synchronous and clustered nesting, but observed synchronous nesting in only 2009 and 2011, and evidence of clustered nesting at just one study area in 2009, providing limited support for the hypothesis. Nests tended to be on hummocks and exhibited lateral concealment around the bowl, suggesting a trade-off between a greater view from the nest and concealment. However, our analysis failed to identify other important habitat features at scales from 1–400 m from the nest. Our best-supported nest survival model showed a strong difference between our two main study areas, but this difference remains largely unexplained. Given the increased frequency, severity, and extent of wildfires predicted under climate change scenarios, our study highlights the importance of monitoring the persistence of boreal tundra patches and the Whimbrels breeding therein.
","language":"English","publisher":"International Wader Study Group","doi":"10.18194/ws.00037","usgsCitation":"Harwood, C.M., Gill, R., and Powell, A., 2016, Nesting ecology of Whimbrels in boreal Alaska: Wader Study, v. 123, no. 2, p. 99-113, https://doi.org/10.18194/ws.00037.","productDescription":"15 p.","startPage":"99","endPage":"113","ipdsId":"IP-070372","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kanuti National Wildlife Refuge","volume":"123","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-25","publicationStatus":"PW","scienceBaseUri":"5a60fcd3e4b06e28e9c24389","contributors":{"authors":[{"text":"Harwood, Christopher M.","contributorId":40515,"corporation":false,"usgs":true,"family":"Harwood","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":723064,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gill, Robert E. Jr. 0000-0002-6385-4500 rgill@usgs.gov","orcid":"https://orcid.org/0000-0002-6385-4500","contributorId":171747,"corporation":false,"usgs":true,"family":"Gill","given":"Robert E.","suffix":"Jr.","email":"rgill@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":718089,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Abby 0000-0002-9783-134X abby_powell@usgs.gov","orcid":"https://orcid.org/0000-0002-9783-134X","contributorId":176843,"corporation":false,"usgs":true,"family":"Powell","given":"Abby","email":"abby_powell@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":718088,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70185230,"text":"70185230 - 2016 - Life history characteristics and vital rates of Yellowstone Cutthroat Trout in two headwater basins","interactions":[],"lastModifiedDate":"2017-03-16T12:45:43","indexId":"70185230","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Life history characteristics and vital rates of Yellowstone Cutthroat Trout in two headwater basins","docAbstract":"The Yellowstone Cutthroat Trout Oncorhynchus clarkii bouvieri is native to the Rocky Mountains and has declined in abundance and distribution as a result of habitat degradation and introduced salmonid species. Many of its remaining strongholds are in headwater basins with minimal human disturbances. Understanding the life histories, vital rates, and behaviors of Yellowstone Cutthroat Trout within headwater stream networks remains limited yet is critical for effective management and conservation. We estimated annual relative growth in length and weight, annual survival rates, and movement patterns of Yellowstone Cutthroat Trout from three tributaries of Spread Creek, Wyoming, and two tributaries of Shields River, Montana, from 2011 through 2013 using PIT tag antennas within a mark–recapture framework. Mean annual growth rates varied among tributaries and size-classes, but were slow compared with populations of Yellowstone Cutthroat Trout from large, low-elevation streams. Survival rates were relatively high compared with those of other Cutthroat Trout subspecies, but we found an inverse relationship between survival and size, a pattern contrary to what has been reported for Cutthroat Trout in large streams. Mean annual survival rates ranged from 0.32 (SE = 0.04) to 0.68 (SE = 0.05) in the Spread Creek basin and from 0.30 (SE = 0.07) to 0.69 (SE = 0.10) in the Shields River basin. Downstream movements from tributaries were substantial, with as much as 26.5% of a tagging cohort leaving over the course of the study. Integrating our growth, survival, and movement results demonstrates the importance of considering strategies to enhance headwater stream habitats and highlights the importance of connectivity with larger stream networks.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2016.1206643","usgsCitation":"Uthe, P., Al-Chokhachy, R.K., Zale, A.V., Shepard, B.B., McMahon, T., and Stephens, T., 2016, Life history characteristics and vital rates of Yellowstone Cutthroat Trout in two headwater basins: North American Journal of Fisheries Management, v. 36, no. 6, p. 1240-1253, https://doi.org/10.1080/02755947.2016.1206643.","productDescription":"14 p.","startPage":"1240","endPage":"1253","ipdsId":"IP-076407","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":337749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"58cba41be4b0849ce97dc746","contributors":{"authors":[{"text":"Uthe, Patrick","contributorId":189424,"corporation":false,"usgs":false,"family":"Uthe","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":684806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":684805,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zale, Alexander V. 0000-0003-1703-885X zale@usgs.gov","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":3010,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"zale@usgs.gov","middleInitial":"V.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":684807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shepard, Bradley B.","contributorId":145880,"corporation":false,"usgs":false,"family":"Shepard","given":"Bradley","email":"","middleInitial":"B.","affiliations":[{"id":6765,"text":"Montana State University, Department of Land Resources and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":684808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McMahon, Thomas E.","contributorId":189425,"corporation":false,"usgs":false,"family":"McMahon","given":"Thomas E.","affiliations":[],"preferred":false,"id":684809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stephens, Tracy","contributorId":189426,"corporation":false,"usgs":false,"family":"Stephens","given":"Tracy","email":"","affiliations":[],"preferred":false,"id":684810,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70185062,"text":"70185062 - 2016 - SNP discovery in candidate adaptive genes using exon capture in a free-ranging alpine ungulate","interactions":[],"lastModifiedDate":"2017-03-13T17:00:12","indexId":"70185062","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2776,"text":"Molecular Ecology Resources","active":true,"publicationSubtype":{"id":10}},"title":"SNP discovery in candidate adaptive genes using exon capture in a free-ranging alpine ungulate","docAbstract":"Identification of genes underlying genomic signatures of natural selection is key to understanding adaptation to local conditions. We used targeted resequencing to identify SNP markers in 5321 candidate adaptive genes associated with known immunological, metabolic and growth functions in ovids and other ungulates. We selectively targeted 8161 exons in protein-coding and nearby 5′ and 3′ untranslated regions of chosen candidate genes. Targeted sequences were taken from bighorn sheep (Ovis canadensis) exon capture data and directly from the domestic sheep genome (Ovis aries v. 3; oviAri3). The bighorn sheep sequences used in the Dall's sheep (Ovis dalli dalli) exon capture aligned to 2350 genes on the oviAri3 genome with an average of 2 exons each. We developed a microfluidic qPCR-based SNP chip to genotype 476 Dall's sheep from locations across their range and test for patterns of selection. Using multiple corroborating approaches (lositan and bayescan), we detected 28 SNP loci potentially under selection. We additionally identified candidate loci significantly associated with latitude, longitude, precipitation and temperature, suggesting local environmental adaptation. The three methods demonstrated consistent support for natural selection on nine genes with immune and disease-regulating functions (e.g. Ovar-DRA, APC, BATF2, MAGEB18), cell regulation signalling pathways (e.g. KRIT1, PI3K, ORRC3), and respiratory health (CYSLTR1). Characterizing adaptive allele distributions from novel genetic techniques will facilitate investigation of the influence of environmental variation on local adaptation of a northern alpine ungulate throughout its range. This research demonstrated the utility of exon capture for gene-targeted SNP discovery and subsequent SNP chip genotyping using low-quality samples in a nonmodel species.
","language":"English","publisher":"Wiley","doi":"10.1111/1755-0998.12560","usgsCitation":"Roffler, G.H., Amish, S.J., Smith, S., Cosart, T.F., Kardos, M., Schwartz, M.K., and Luikart, G., 2016, SNP discovery in candidate adaptive genes using exon capture in a free-ranging alpine ungulate: Molecular Ecology Resources, v. 16, no. 5, p. 1147-1164, https://doi.org/10.1111/1755-0998.12560.","productDescription":"18 p.","startPage":"1147","endPage":"1164","ipdsId":"IP-077118","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470614,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1755-0998.12560","text":"Publisher Index Page"},{"id":337477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-18","publicationStatus":"PW","scienceBaseUri":"58c7afa0e4b0849ce9795e9c","chorus":{"doi":"10.1111/1755-0998.12560","url":"http://dx.doi.org/10.1111/1755-0998.12560","publisher":"Wiley-Blackwell","authors":"Roffler Gretchen H., Amish Stephen J., Smith Seth, Cosart Ted, Kardos Marty, Schwartz Michael K., Luikart Gordon","journalName":"Molecular Ecology Resources","publicationDate":"7/18/2016"},"contributors":{"authors":[{"text":"Roffler, Gretchen H. groffler@usgs.gov","contributorId":1946,"corporation":false,"usgs":true,"family":"Roffler","given":"Gretchen","email":"groffler@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":684124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amish, Stephen J.","contributorId":104799,"corporation":false,"usgs":false,"family":"Amish","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":684170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Seth","contributorId":189234,"corporation":false,"usgs":false,"family":"Smith","given":"Seth","email":"","affiliations":[],"preferred":false,"id":684171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cosart, Ted F.","contributorId":177052,"corporation":false,"usgs":false,"family":"Cosart","given":"Ted","email":"","middleInitial":"F.","affiliations":[{"id":5091,"text":"Flathead Lake Biological Station, Fish and Wildlife Genomics Group, Division of Biological Sciences, University of Montana, Polson, MT 59860, USA","active":true,"usgs":false}],"preferred":false,"id":684172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kardos, Marty","contributorId":189235,"corporation":false,"usgs":false,"family":"Kardos","given":"Marty","affiliations":[],"preferred":false,"id":684173,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwartz, Michael K.","contributorId":102326,"corporation":false,"usgs":true,"family":"Schwartz","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":684174,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Luikart, Gordon","contributorId":145746,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","email":"","affiliations":[{"id":16220,"text":"Flathead Lake Biological Station, Div. Biological Science, UM","active":true,"usgs":false}],"preferred":false,"id":684175,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70182077,"text":"70182077 - 2016 - Evidence for wild waterfowl origin of H7N3 influenza A virus detected in captive-reared New Jersey pheasants","interactions":[],"lastModifiedDate":"2018-08-16T21:28:42","indexId":"70182077","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":892,"text":"Archives of Virology","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for wild waterfowl origin of H7N3 influenza A virus detected in captive-reared New Jersey pheasants","docAbstract":"In August 2014, a low-pathogenic H7N3 influenza A virus was isolated from pheasants at a New Jersey gamebird farm and hunting preserve. In this study, we use phylogenetic analyses and calculations of genetic similarity to gain inference into the genetic ancestry of this virus and to identify potential routes of transmission. Results of maximum-likelihood (ML) and maximum-clade-credibility (MCC) phylogenetic analyses provide evidence that A/pheasant/New Jersey/26996-2/2014 (H7N3) had closely related H7 hemagglutinin (HA) and N3 neuraminidase (NA) gene segments as compared to influenza A viruses circulating among wild waterfowl in the central and eastern USA. The estimated time of the most recent common ancestry (TMRCA) between the pheasant virus and those most closely related from wild waterfowl was early 2013 for both the H7 HA and N3 NA gene segments. None of the viruses from waterfowl identified as being most closely related to A/pheasant/New Jersey/26996-2/2014 at the HA and NA gene segments in ML and MCC phylogenetic analyses shared ≥99 % nucleotide sequence identity for internal gene segment sequences. This result indicates that specific viral strains identified in this study as being closely related to the HA and NA gene segments of A/pheasant/New Jersey/26996-2/2014 were not the direct predecessors of the etiological agent identified during the New Jersey outbreak. However, the recent common ancestry of the H7 and N3 gene segments of waterfowl-origin viruses and the virus isolated from pheasants suggests that viral diversity maintained in wild waterfowl likely played an important role in the emergence of A/pheasant/New Jersey/26996-2/2014.
","language":"English","publisher":"Springer","doi":"10.1007/s00705-016-2947-z","usgsCitation":"Ramey, A.M., Kim Torchetti, M., Poulson, R.L., Carter, D.L., Reeves, A.B., Link, P., Walther, P., Lebarbenchon, C., and Stallknecht, D.E., 2016, Evidence for wild waterfowl origin of H7N3 influenza A virus detected in captive-reared New Jersey pheasants: Archives of Virology, v. 161, no. 9, p. 2519-2526, https://doi.org/10.1007/s00705-016-2947-z.","productDescription":"8 p.","startPage":"2519","endPage":"2526","ipdsId":"IP-073296","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470618,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11302360","text":"External Repository"},{"id":335678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"161","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-02","publicationStatus":"PW","scienceBaseUri":"58a6c832e4b025c46428628c","chorus":{"doi":"10.1007/s00705-016-2947-z","url":"http://dx.doi.org/10.1007/s00705-016-2947-z","publisher":"Springer Nature","authors":"Ramey Andrew M., Kim Torchetti Mia, Poulson Rebecca L., Carter Deborah, Reeves Andrew B., Link Paul, Walther Patrick, Lebarbenchon Camille, Stallknecht David E.","journalName":"Archives of Virology","publicationDate":"7/2/2016","auditedOn":"2/8/2017","publiclyAccessibleDate":"7/2/2016"},"contributors":{"authors":[{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":669532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kim Torchetti, Mia","contributorId":139355,"corporation":false,"usgs":false,"family":"Kim Torchetti","given":"Mia","email":"","affiliations":[{"id":12747,"text":"USDA APHIS VS National Veterinary Services Laboratories, Ames, IA","active":true,"usgs":false}],"preferred":false,"id":669533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poulson, Rebecca L.","contributorId":68669,"corporation":false,"usgs":true,"family":"Poulson","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":669534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carter, Deborah L.","contributorId":87473,"corporation":false,"usgs":true,"family":"Carter","given":"Deborah","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":669535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":669536,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Link, Paul","contributorId":22707,"corporation":false,"usgs":true,"family":"Link","given":"Paul","affiliations":[],"preferred":false,"id":669537,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walther, Patrick","contributorId":42153,"corporation":false,"usgs":true,"family":"Walther","given":"Patrick","affiliations":[],"preferred":false,"id":669538,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lebarbenchon, Camille","contributorId":140670,"corporation":false,"usgs":false,"family":"Lebarbenchon","given":"Camille","email":"","affiliations":[],"preferred":false,"id":669539,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stallknecht, David E.","contributorId":20230,"corporation":false,"usgs":true,"family":"Stallknecht","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":669540,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70185033,"text":"70185033 - 2016 - A strategy for recovering continuous behavioral telemetry data from Pacific walruses","interactions":[],"lastModifiedDate":"2018-06-16T17:47:36","indexId":"70185033","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"A strategy for recovering continuous behavioral telemetry data from Pacific walruses","docAbstract":"Tracking animal behavior and movement with telemetry sensors can offer substantial insights required for conservation. Yet, the value of data collected by animal-borne telemetry systems is limited by bandwidth constraints. To understand the response of Pacific walruses (Odobenus rosmarus divergens) to rapid changes in sea ice availability, we required continuous geospatial chronologies of foraging behavior. Satellite telemetry offered the only practical means to systematically collect such data; however, data transmission constraints of satellite data-collection systems limited the data volume that could be acquired. Although algorithms exist for reducing sensor data volumes for efficient transmission, none could meet our requirements. Consequently, we developed an algorithm for classifying hourly foraging behavior status aboard a tag with limited processing power. We found a 98% correspondence of our algorithm's classification with a test classification based on time–depth data recovered and characterized through multivariate analysis in a separate study. We then applied our algorithm within a telemetry system that relied on remotely deployed satellite tags. Data collected by these tags from Pacific walruses across their range during 2007–2015 demonstrated the consistency of foraging behavior collected by this strategy with data collected by data logging tags; and demonstrated the ability to collect geospatial behavioral chronologies with minimal missing data where recovery of data logging tags is precluded. Our strategy for developing a telemetry system may be applicable to any study requiring intelligent algorithms to continuously monitor behavior, and then compress those data into meaningful information that can be efficiently transmitted.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.685","usgsCitation":"Fischbach, A.S., and Jay, C.V., 2016, A strategy for recovering continuous behavioral telemetry data from Pacific walruses: Wildlife Society Bulletin, v. 40, no. 3, p. 599-604, https://doi.org/10.1002/wsb.685.","productDescription":"6 p.","startPage":"599","endPage":"604","ipdsId":"IP-072182","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":500040,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/8556f5253616444cbdd9ed1af2942bf8","text":"External Repository"},{"id":337496,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-12","publicationStatus":"PW","scienceBaseUri":"58c90125e4b0849ce97abcd9","chorus":{"doi":"10.1002/wsb.685","url":"http://dx.doi.org/10.1002/wsb.685","publisher":"Wiley-Blackwell","authors":"Fischbach Anthony, Jay Chadwick V.","journalName":"Wildlife Society Bulletin","publicationDate":"9/2016"},"contributors":{"authors":[{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":2865,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony","email":"afischbach@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":684021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":684022,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185032,"text":"70185032 - 2016 - Iron oxide minerals in dust-source sediments from the Bodélé Depression, Chad: Implications for radiative properties and Fe bioavailability of dust plumes from the Sahara","interactions":[],"lastModifiedDate":"2017-03-14T12:15:24","indexId":"70185032","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":666,"text":"Aeolian Research","active":true,"publicationSubtype":{"id":10}},"title":"Iron oxide minerals in dust-source sediments from the Bodélé Depression, Chad: Implications for radiative properties and Fe bioavailability of dust plumes from the Sahara","docAbstract":"Atmospheric mineral dust can influence climate and biogeochemical cycles. An important component of mineral dust is ferric oxide minerals (hematite and goethite) which have been shown to influence strongly the optical properties of dust plumes and thus affect the radiative forcing of global dust. Here we report on the iron mineralogy of dust-source samples from the Bodélé Depression (Chad, north-central Africa), which is estimated to be Earth’s most prolific dust producer and may be a key contributor to the global radiative budget of the atmosphere as well as to long-range nutrient transport to the Amazon Basin. By using a combination of magnetic property measurements, Mössbauer spectroscopy, reflectance spectroscopy, chemical analysis, and scanning electron microscopy, we document the abundance and relative amounts of goethite, hematite, and magnetite in dust-source samples from the Bodélé Depression. The partition between hematite and goethite is important to know to improve models for the radiative effects of ferric oxide minerals in mineral dust aerosols. The combination of methods shows (1) the dominance of goethite over hematite in the source sediments, (2) the abundance and occurrences of their nanosize components, and (3) the ubiquity of magnetite, albeit in small amounts. Dominant goethite and subordinate hematite together compose about 2% of yellow-reddish dust-source sediments from the Bodélé Depression and contribute strongly to diminution of reflectance in bulk samples. These observations imply that dust plumes from the Bodélé Depression that are derived from goethite-dominated sediments strongly absorb solar radiation. The presence of ubiquitous magnetite (0.002–0.57 wt%) is also noteworthy for its potentially higher solubility relative to ferric oxide and for its small sizes, including PM < 0.1 μm. For all examined samples, the average iron apportionment is estimated at about 33% in ferric oxide minerals, 1.4% in magnetite, and 65% in ferric silicates. Structural iron in clay minerals may account for much of the iron in the ferric silicates. We estimate that the mean ferric oxides flux exported from the Bodélé Depression is 0.9 Tg/yr with greater than 50% exported as ferric oxide nanoparticles (<0.1 μm). The high surface-to-volume ratios of ferric oxide nanoparticles once entrained into dust plumes may facilitate increased atmospheric chemical and physical processing and affect iron solubility and bioavailability to marine and terrestrial ecosystems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aeolia.2016.07.001","usgsCitation":"Moskowitz, B.M., Reynolds, R.L., Goldstein, H.L., Beroquo, T., Kokaly, R.F., and Bristow, C.S., 2016, Iron oxide minerals in dust-source sediments from the Bodélé Depression, Chad: Implications for radiative properties and Fe bioavailability of dust plumes from the Sahara: Aeolian Research, v. 22, p. 93-106, https://doi.org/10.1016/j.aeolia.2016.07.001.","productDescription":"14 p.","startPage":"93","endPage":"106","ipdsId":"IP-071700","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":462095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aeolia.2016.07.001","text":"Publisher Index Page"},{"id":337498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c90126e4b0849ce97abcdb","contributors":{"authors":[{"text":"Moskowitz, Bruce M.","contributorId":189164,"corporation":false,"usgs":false,"family":"Moskowitz","given":"Bruce","email":"","middleInitial":"M.","affiliations":[{"id":17684,"text":"University of Minnesota, Minneapolis, MN","active":true,"usgs":false}],"preferred":false,"id":684016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reynolds, Richard L. 0000-0002-4572-2942 rreynolds@usgs.gov","orcid":"https://orcid.org/0000-0002-4572-2942","contributorId":147880,"corporation":false,"usgs":true,"family":"Reynolds","given":"Richard","email":"rreynolds@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":271,"text":"Federal Center","active":false,"usgs":true}],"preferred":true,"id":684017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldstein, Harland L. 0000-0002-6092-8818 hgoldstein@usgs.gov","orcid":"https://orcid.org/0000-0002-6092-8818","contributorId":147881,"corporation":false,"usgs":true,"family":"Goldstein","given":"Harland","email":"hgoldstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":684015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beroquo, Thelma","contributorId":189165,"corporation":false,"usgs":false,"family":"Beroquo","given":"Thelma","email":"","affiliations":[],"preferred":false,"id":684018,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101 raymond@usgs.gov","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":150717,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"raymond@usgs.gov","middleInitial":"F.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":684019,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bristow, Charlie S","contributorId":189166,"corporation":false,"usgs":false,"family":"Bristow","given":"Charlie","email":"","middleInitial":"S","affiliations":[],"preferred":false,"id":684020,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70184317,"text":"70184317 - 2016 - Mapping changing distributions of dominant species in oil-contaminated salt marshes of Louisiana using imaging spectroscopy","interactions":[],"lastModifiedDate":"2017-03-07T16:15:12","indexId":"70184317","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Mapping changing distributions of dominant species in oil-contaminated salt marshes of Louisiana using imaging spectroscopy","docAbstract":"The April 2010 Deepwater Horizon (DWH) oil spill was the largest coastal spill in U.S. history. Monitoring subsequent change in marsh plant community distributions is critical to assess ecosystem impacts and to establish future coastal management priorities. Strategically deployed airborne imaging spectrometers, like the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), offer the spectral and spatial resolution needed to differentiate plant species. However, obtaining satisfactory and consistent classification accuracies over time is a major challenge, particularly in dynamic intertidal landscapes.
Here, we develop and evaluate an image classification system for a time series of AVIRIS data for mapping dominant species in a heavily oiled salt marsh ecosystem. Using field-referenced image endmembers and canonical discriminant analysis (CDA), we classified 21 AVIRIS images acquired during the fall of 2010, 2011 and 2012. Classification results were evaluated using ground surveys that were conducted contemporaneously to AVIRIS collection dates. We analyzed changes in dominant species cover from 2010 to 2012 for oiled and non-oiled shorelines.
CDA discriminated dominant species with a high level of accuracy (overall accuracy = 82%, kappa = 0.78) and consistency over three imaging dates (overall2010 = 82%, overall2011 = 82%, overall2012 = 88%). Marshes dominated by Spartina alterniflora were the most spatially abundant in shoreline zones (≤ 28 m from shore) for all three dates (2010 = 79%, 2011 = 61%, 2012 = 63%), followed by Juncus roemerianus (2010 = 11%, 2011 = 19%, 2012 = 17%) and Distichlis spicata (2010 = 4%, 2011 = 10%, 2012 = 7%).
Marshes that were heavily contaminated with oil exhibited variable responses from 2010 to 2012. Marsh vegetation classes converted to a subtidal, open water class along oiled and non-oiled shorelines that were similarly situated in the landscape. However, marsh loss along oil-contaminated shorelines doubled that of non-oiled shorelines. Only S. alterniflora dominated marshes were extensively degraded, losing 15% (354,604 m2) cover in oiled shoreline zones, suggesting that S. alterniflora marshes may be more vulnerable to shoreline erosion following hydrocarbon stress, due to their landscape position.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2016.04.024","usgsCitation":"Beland, M., Roberts, D.A., Peterson, S.H., Biggs, T.W., Kokaly, R., Piazza, S., Roth, K.L., Khanna, S., and Ustin, S.L., 2016, Mapping changing distributions of dominant species in oil-contaminated salt marshes of Louisiana using imaging spectroscopy: Remote Sensing of Environment, v. 182, p. 192-207, https://doi.org/10.1016/j.rse.2016.04.024.","productDescription":"16 p.","startPage":"192","endPage":"207","ipdsId":"IP-069176","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":470617,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://escholarship.org/uc/item/81m5219m","text":"Publisher Index Page"},{"id":336983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","volume":"182","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58bfd4f3e4b014cc3a3ba4a1","contributors":{"authors":[{"text":"Beland, Michael","contributorId":139569,"corporation":false,"usgs":false,"family":"Beland","given":"Michael","email":"","affiliations":[{"id":12805,"text":"Univ. of California at San Diego","active":true,"usgs":false}],"preferred":false,"id":680982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, Dar A.","contributorId":100503,"corporation":false,"usgs":false,"family":"Roberts","given":"Dar","email":"","middleInitial":"A.","affiliations":[{"id":12804,"text":"Univ. of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":680983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Seth H.","contributorId":139568,"corporation":false,"usgs":false,"family":"Peterson","given":"Seth","email":"","middleInitial":"H.","affiliations":[{"id":12804,"text":"Univ. of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":680984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Biggs, Trent W.","contributorId":187592,"corporation":false,"usgs":false,"family":"Biggs","given":"Trent","email":"","middleInitial":"W.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":680985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101 raymond@usgs.gov","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":1785,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond F.","email":"raymond@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":680981,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Piazza, Sarai 0000-0001-6962-9008 piazzas@usgs.gov","orcid":"https://orcid.org/0000-0001-6962-9008","contributorId":169024,"corporation":false,"usgs":true,"family":"Piazza","given":"Sarai","email":"piazzas@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":680986,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roth, Keely L.","contributorId":187593,"corporation":false,"usgs":false,"family":"Roth","given":"Keely","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":680987,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Khanna, Shruti","contributorId":74287,"corporation":false,"usgs":true,"family":"Khanna","given":"Shruti","affiliations":[],"preferred":false,"id":680988,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ustin, Susan L.","contributorId":52878,"corporation":false,"usgs":false,"family":"Ustin","given":"Susan","email":"","middleInitial":"L.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":680989,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}