Lahars large enough to reach populated areas are a hazard at Mount Adams, a massive volcano in the southern Cascade Range of Washington State (fig. 1). It is considered to be still active and has the potential to erupt again. By definition, lahars are gravity-driven flows of water-saturated mixtures of mud and rock (plus or minus ice, wood, and other debris), which originate from volcanoes and have a variety of potential triggering mechanisms (Vallance, 2000; Vallance and Iverson, 2015). Flowing mixtures can range in fluid consistency from something like a milkshake to something more like wet concrete, and they behave like flash floods, in that they can appear suddenly in river channels with little warning and commonly have boulder- or log-choked flow fronts. Lahars are hazardous because they can flow rapidly in confined valleys (commonly 20–35 miles per hour [mph] or 9–16 meters per second [m/s]), can travel more than 100 miles (mi) (161 kilometers [km]) from a source volcano, and can move with incredible destructive force, carrying multi-ton boulders and logs that can act as battering rams (Pierson, 1998). The biggest threats from lahars to downstream communities are present during eruptive activity, and impacts to communities can be dire. For example, a very large eruption-triggered lahar in Colombia in 1985 surprised and killed more than 20,000 people in a large town located about 45 mi (72 km) downstream and out of sight of the volcano that produced it (Pierson and others, 1990).
Mount Adams, one of the largest volcanoes in the Cascade Range, is a composite stratocone composed primarily of andesite lava flows. It has been the most continuously active volcano within the 480-mi2 Mount Adams volcanic field—a region covering parts of Klickitat, Skamania, Yakima, andLewis Counties and part of the Yakama Nation Reservation in Washington State (Hildreth and Fierstein,1995, 1997). About 500,000 years in age, Mount Adams reached its present size by about 15,000 years ago, primarily through the episodic effusion of lava flows; it has not had a history of major explosive eruptions like Mount St. Helens, its neighbor to the west. Timing of the most recent eruptive activity (recorded by four thin tephra layers) is on the order of 1,000 years ago; the tephras are bracketed by 2,500-year-old and 500-year-old ash layers from Mount St. Helens (Hildreth and Fierstein, 1995, 1997). Mount Adams currently shows no signs of renewed unrest.
Eruptive history does not tell us everything we need to know about hazards at Mount Adams, however, which are fully addressed in the volcano hazard assessment for Mount Adams (W.E. Scott and others, 1995). This volcano has had a long-active hydrothermal system that circulated acidic hydrothermal fluids, formed by the solution of volcanic gases in heated groundwater, through fractures and permeable zones into upper parts of the volcanic cone. Acid sulfate leaching of rocks in the summit area may still be occurring, but chemical and thermal evidence suggests that the main hydrothermal system is no longer active at Mount Adams (Nathenson and Mariner, 2013). However, these rock-weakening chemical reactions have operated long enough to change about 0.4 cubic miles (mi3) (1.7 cubic kilometers [km3]) of the hard lava rock in the volcano’s upper cone to a much weaker clay-rich rock, thus significantly reducing rock strength and thereby slope stability in parts of the cone (Finn and others, 2007). The two largest previous lahars from Mount Adams were triggered by landslides of hydrothermally altered rock from the upper southwestern flank of the cone, and any future large lahars are likely to be triggered by the same mechanism. Mount Rainier also has had extensive hydrothermal alteration of rock in its upper edifice, and it also has a history of large landslides that transform into lahars (K.M. Scott and others, 1995; Vallance and Scott, 1997; Reid and others, 2001).
The spatial depiction of modeled lahar inundation zones accompanying this report, shown in two different map perspectives, is intended to augment (not replace) the existing hazard maps for Mount Adams (W.E. Scott and others, 1995; Vallance, 1999). The maps in this report show potential areas of inundation by lahars of different initial volumes, which are determined by a computer model, LAHARZ (Iverson and others, 1998; Schilling, 1998). One map sheet presents LAHARZ-determined inundation areas on a normal plan-view shaded-relief map of the study area; the other gives an oblique perspective of the landscape with raised topography, as if one were viewing the landscape at an angle from an aircraft (Jenny and Patterson, 2007). LAHARZ was developed after the original hazard maps (based only on mapping of geologic deposits) were made. Predicted inundation zones on these maps provide an alternative approach to estimation of areas that could be inundated as lahars of different volumes pass through the valley. However, there is considerable uncertainty in the exact location of the hazard-zone boundaries shown on these maps, as well as on earlier maps.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181013","usgsCitation":"Griswold, J.P., Pierson, T.C., and Bard J.A., 2018, Modeled inundation limits of potential lahars from Mount Adams in the White Salmon River valley, Washington: U.S. Geological Survey Open-File Report 2018–1013, scale 1:75,000, 14 p., https://doi.org/10.3133/ofr20181013.","productDescription":"Sheet: 42.0 x 42.0 inches; Pamphlet: iii, 14 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-078093","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":353953,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1013/ofr20181013_pamphlet.pdf","text":"Pamphlet","size":"18.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1013 Pamphlet"},{"id":353952,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1013/ofr20181013_sheet_.pdf","size":"41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1013"},{"id":353951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1013/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Adams, While Salmon River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.8333,\n 45.682198608003404\n ],\n [\n -121.25,\n 45.682198608003404\n ],\n [\n -121.25,\n 46.25\n ],\n [\n -121.8333,\n 46.25\n ],\n [\n -121.8333,\n 45.682198608003404\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center
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Few regions have been more severely impacted by climate change in the USA than the Desert Southwest. Here, we use ecological genomics to assess the potential for adaptation to rising global temperatures in a widespread songbird, the willow flycatcher (Empidonax traillii), and find the endangered desert southwestern subspecies (E. t. extimus) most vulnerable to future climate change. Highly significant correlations between present abundance and estimates of genomic vulnerability – the mismatch between current and predicted future genotype–environment relationships – indicate small, fragmented populations of the southwestern willow flycatcher will have to adapt most to keep pace with climate change. Links between climate‐associated genotypes and genes important to thermal tolerance in birds provide a potential mechanism for adaptation to temperature extremes. Our results demonstrate that the incorporation of genotype–environment relationships into landscape‐scale models of climate vulnerability can facilitate more precise predictions of climate impacts and help guide conservation in threatened and endangered groups.
","language":"English","publisher":"Wiley","doi":"10.1111/ele.12977","usgsCitation":"Ruegg, K., Bay, R.A., Anderson, E.C., Saracco, J.F., Harrigan, R.J., Whitfield, M.J., Paxton, E., and Smith, T.B., 2018, Ecological genomics predicts climate vulnerability in an endangered southwestern songbird: Ecology Letters, v. 21, p. 1085-1096, https://doi.org/10.1111/ele.12977.","productDescription":"12 p.","startPage":"1085","endPage":"1096","ipdsId":"IP-095047","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":355634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-09","publicationStatus":"PW","scienceBaseUri":"5b46e58de4b060350a15d1cc","contributors":{"authors":[{"text":"Ruegg, Kristin","contributorId":206224,"corporation":false,"usgs":false,"family":"Ruegg","given":"Kristin","email":"","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":739831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bay, Rachael A.","contributorId":206219,"corporation":false,"usgs":false,"family":"Bay","given":"Rachael","email":"","middleInitial":"A.","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":739824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Eric C.","contributorId":206220,"corporation":false,"usgs":false,"family":"Anderson","given":"Eric","email":"","middleInitial":"C.","affiliations":[{"id":37289,"text":"Southwest Fisheries Science Center, National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":739825,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saracco, James F.","contributorId":206221,"corporation":false,"usgs":false,"family":"Saracco","given":"James","email":"","middleInitial":"F.","affiliations":[{"id":37290,"text":"The Institute for Bird Populations","active":true,"usgs":false}],"preferred":false,"id":739826,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harrigan, Ryan J.","contributorId":206222,"corporation":false,"usgs":false,"family":"Harrigan","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":739827,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitfield, Mary J.","contributorId":174933,"corporation":false,"usgs":false,"family":"Whitfield","given":"Mary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":739828,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":739829,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smith, Thomas B.","contributorId":206223,"corporation":false,"usgs":false,"family":"Smith","given":"Thomas","email":"","middleInitial":"B.","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":739830,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196848,"text":"fs20183030 - 2018 - Ecosystems science: Genes to landscapes","interactions":[{"subject":{"id":70156264,"text":"fs20153057 - 2015 - Science from genes to landscapes","indexId":"fs20153057","publicationYear":"2015","noYear":false,"title":"Science from genes to landscapes"},"predicate":"SUPERSEDED_BY","object":{"id":70196848,"text":"fs20183030 - 2018 - Ecosystems science: Genes to landscapes","indexId":"fs20183030","publicationYear":"2018","noYear":false,"title":"Ecosystems science: Genes to landscapes"},"id":1}],"lastModifiedDate":"2018-05-14T11:32:31","indexId":"fs20183030","displayToPublicDate":"2018-05-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3030","title":"Ecosystems science: Genes to landscapes","docAbstract":"Bountiful fisheries, healthy and resilient wildlife, flourishing forests and vibrant grasslands are coveted resources that benefit all Americans. U.S. Geological Survey (USGS) science supports the conservation and management of the Nation’s fish and wildlife, and the landscapes they inhabit. Our biological resources—ecosystems and the wild things that live in them—are the foundation of our conservation heritage and an economic asset to current and future generations of Americans.
The USGS Ecosystems Mission Area, the biological research arm of the Department of the Interior (DOI), provides science to help America achieve sustainable management and conservation of its biological resources. This work is done within the broader mission of the USGS—to serve the Nation with science that advances understanding of our natural resources, informs land and water stewardship, and helps safeguard communities from natural and environmental hazards. The Ecosystems Mission Area provides research, technical assistance, and education conducted by Cooperative Research Units and Science Centers located in nearly every State.
The quality of life and economic strength in America hinges on healthy ecosystems that support living things and natural processes. Ecosystem science better enables society to understand how and why ecosystems change and to guide actions that can prevent damage to, and restore and sustain ecosystems. It is through this knowledge that informed decisions are made about natural resources that can enhance our Nation’s economic and environmental well-being.
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http://www.usgs.gov/ask/
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Groundwater is an important source of drinking and irrigation water throughout Idaho, and groundwater quality is monitored by various Federal, State, and local agencies. The historical, multi-agency records of groundwater quality include a valuable dataset that has yet to be compiled or analyzed on a statewide level. The purpose of this study is to combine groundwater-quality data from multiple sources into a single database, to summarize this dataset, and to perform bulk analyses to reveal spatial and temporal patterns of water quality throughout Idaho. Data were retrieved from the Water Quality Portal (https://www.waterqualitydata.us/), the Idaho Department of Environmental Quality, and the Idaho Department of Water Resources. Analyses included counting the number of times a sample location had concentrations above Maximum Contaminant Levels (MCL), performing trends tests, and calculating correlations between water-quality analytes. The water-quality database and the analysis results are available through USGS ScienceBase (https://doi.org/10.5066/F72V2FBG).
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\"}}]}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
Submarine groundwater fluxes across the seafloor facilitate important hydrological and biogeochemical exchanges between oceans and seabed sediment, yet few studies have investigated spatially distributed groundwater fluxes in deep‐ocean environments such as continental slopes. Heat has been previously applied as a submarine groundwater tracer using an analytical solution to a heat flow equation assuming steady state conditions and homogeneous thermal conductivity. These assumptions are often violated in shallow seabeds due to ocean bottom temperature changes or sediment property variations. Here heat tracing analysis techniques recently developed for terrestrial settings are applied in concert to examine the influences of groundwater flow, ocean temperature changes, and seabed thermal conductivity variations on deep‐ocean sediment temperature profiles. Temperature observations from the sediment and bottom ocean water on the Scotian Slope off eastern Canada are used to demonstrate how simple thermal methods for tracing groundwater can be employed if more comprehensive techniques indicate that the simplifying assumptions are valid. The spatial distribution of the inferred groundwater fluxes on the slope suggests a downward groundwater flow system with recharge occurring over the upper‐middle slope and discharge on the lower slope. We speculate that the downward groundwater flow inferred on the Scotian Slope is due to density‐driven processes arising from underlying salt domes, in contrast with upward slope systems driven by geothermal convection. Improvements in the design of future submarine hydrogeological studies are proposed for thermal data collection and groundwater flow analysis, including new equations that quantify the minimum detectable flux magnitude for a given sensor accuracy and profile length.
","language":"English","publisher":"Wiley","doi":"10.1029/2017WR022353","usgsCitation":"Kurylyk, B.L., Irvine, D.J., Mohammed, A., Bense, V.F., Briggs, M.A., Loder, J., and Geshelin, Y., 2018, Rethinking the use of seabed sediment temperature profiles to trace submarine groundwater flow: Water Resources Research, v. 54, no. 7, p. 4595-4614, https://doi.org/10.1029/2017WR022353.","productDescription":"20 p.","startPage":"4595","endPage":"4614","ipdsId":"IP-095613","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468770,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017wr022353","text":"Publisher Index Page"},{"id":360328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Scotian Slope","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -63,\n 41\n ],\n [\n -60,\n 41\n ],\n [\n -60,\n 43\n ],\n [\n -63,\n 43\n ],\n [\n -63,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-07","publicationStatus":"PW","scienceBaseUri":"5c14cfb8e4b006c4f8545d3f","contributors":{"authors":[{"text":"Kurylyk, Barret L.","contributorId":176296,"corporation":false,"usgs":false,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":754277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Dylan J.","contributorId":190404,"corporation":false,"usgs":false,"family":"Irvine","given":"Dylan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":754278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mohammed, A.A.","contributorId":211492,"corporation":false,"usgs":false,"family":"Mohammed","given":"A.A.","email":"","affiliations":[{"id":16660,"text":"University of Calgary","active":true,"usgs":false}],"preferred":false,"id":754279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bense, V. F.","contributorId":211493,"corporation":false,"usgs":false,"family":"Bense","given":"V.","email":"","middleInitial":"F.","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":754280,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754276,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loder, J.W.","contributorId":211494,"corporation":false,"usgs":false,"family":"Loder","given":"J.W.","email":"","affiliations":[{"id":38259,"text":"Bedford Institute of Oceanography, Dartmouth, Canada","active":true,"usgs":false}],"preferred":false,"id":754281,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Geshelin, Y.","contributorId":211495,"corporation":false,"usgs":false,"family":"Geshelin","given":"Y.","email":"","affiliations":[{"id":38259,"text":"Bedford Institute of Oceanography, Dartmouth, Canada","active":true,"usgs":false}],"preferred":false,"id":754282,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70198904,"text":"70198904 - 2018 - Acquisition and dissemination of cephalosporin-resistant E. coli in migratory birds sampled at an Alaska landfill as inferred through genomic analysis","interactions":[],"lastModifiedDate":"2018-08-27T14:31:18","indexId":"70198904","displayToPublicDate":"2018-05-08T13:17:31","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Acquisition and dissemination of cephalosporin-resistant E. coli in migratory birds sampled at an Alaska landfill as inferred through genomic analysis","docAbstract":"Antimicrobial resistance (AMR) in bacterial pathogens threatens global health, though the spread of AMR bacteria and AMR genes between humans, animals, and the environment is still largely unknown. Here, we investigated the role of wild birds in the epidemiology of AMR Escherichia coli. Using next-generation sequencing, we characterized cephalosporin-resistant E. coli cultured from sympatric gulls and bald eagles inhabiting a landfill habitat in Alaska to identify genetic determinants conferring AMR, explore potential transmission pathways of AMR bacteria and genes at this site, and investigate how their genetic diversity compares to isolates reported in other taxa. We found genetically diverse E. coli isolates with sequence types previously associated with human infections and resistance genes of clinical importance, including blaCTX-M and blaCMY. Identical resistance profiles were observed in genetically unrelated E. coli isolates from both gulls and bald eagles. Conversely, isolates with indistinguishable core-genomes were found to have different resistance profiles. Our findings support complex epidemiological interactions including bacterial strain sharing between gulls and bald eagles and horizontal gene transfer among E. coli harboured by birds. Results suggest that landfills may serve as a source for AMR acquisition and/or maintenance, including bacterial sequence types and AMR genes relevant to human health.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41598-018-25474-w","usgsCitation":"Ahlstrom, C., Bonnedahl, J., Woksepp, H., Hernandez, J., Bjorn, O., and Ramey, A.M., 2018, Acquisition and dissemination of cephalosporin-resistant E. coli in migratory birds sampled at an Alaska landfill as inferred through genomic analysis: Scientific Reports, v. 8, no. 1, 7361, https://doi.org/10.1038/s41598-018-25474-w.","productDescription":"7361","ipdsId":"IP-093073","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468771,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-25474-w","text":"Publisher Index Page"},{"id":437918,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70V8C2Q","text":"USGS data release","linkHelpText":"Sampling and Resistance and Genomic Typing of Cephalosporin-resistant E. coli in Gulls (Larus spp.) and Bald Eagles (Haliaeetus leucocephalus) in Southcentral Alaska, 2016"},{"id":356734,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-05-09","publicationStatus":"PW","scienceBaseUri":"5b98a2c6e4b0702d0e842fe6","contributors":{"authors":[{"text":"Ahlstrom, Christina Ann 0000-0001-5414-8076","orcid":"https://orcid.org/0000-0001-5414-8076","contributorId":207262,"corporation":false,"usgs":false,"family":"Ahlstrom","given":"Christina Ann","affiliations":[],"preferred":false,"id":743366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonnedahl, Jonas","contributorId":181800,"corporation":false,"usgs":false,"family":"Bonnedahl","given":"Jonas","email":"","affiliations":[],"preferred":false,"id":743364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woksepp, Hanna","contributorId":207263,"corporation":false,"usgs":false,"family":"Woksepp","given":"Hanna","email":"","affiliations":[],"preferred":false,"id":743365,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hernandez, Jorge","contributorId":203652,"corporation":false,"usgs":false,"family":"Hernandez","given":"Jorge","affiliations":[{"id":36674,"text":"Department of Microbiology, Kalmar County Hospital, Kalmar, Sweden","active":true,"usgs":false}],"preferred":false,"id":743363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bjorn, Olsen","contributorId":207264,"corporation":false,"usgs":false,"family":"Bjorn","given":"Olsen","email":"","affiliations":[],"preferred":false,"id":743367,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":743362,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196868,"text":"70196868 - 2018 - Downstream impacts of dams: shifts in benthic invertivorous fish assemblages","interactions":[],"lastModifiedDate":"2018-05-14T13:12:42","indexId":"70196868","displayToPublicDate":"2018-05-08T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":873,"text":"Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Downstream impacts of dams: shifts in benthic invertivorous fish assemblages","docAbstract":"Impoundments alter connectivity, sediment transport and water discharge in rivers and floodplains, affecting recruitment, habitat and resource availability for fish including benthic invertivorous fish, which represent an important link between primary producers and higher trophic levels in tropical aquatic ecosystems. We investigated long-term changes to water regime, water quality, and invertivorous fish assemblages pre and post impoundment in three rivers downstream of Porto Primavera Reservoir in south Brazil: Paraná, Baía and Ivinhema rivers. Impacts were distinct in the Paraná River, which is fully obstructed by the dam, less evident in the Baía River which is partially obstructed by the dam, but absent in the unimpounded Ivinhema River. Changes in water regime were reflected mainly as changes in water-level fluctuation with little effect on timing. Water transparency increased in the Paraná River post impoundment but did not change in the Baía and Ivinhema rivers. Changes in fish assemblages included a decrease in benthic invertivorous fish in the Paraná River and a shift in invertivorous fish assemblage structure in the Baía and Paraná rivers but not in the unimpounded Ivinhema River. Changes in water regime and water transparency, caused by impoundment, directly or indirectly impacted invertivorous fish assemblages. Alterations of fish assemblages following environmental changes have consequences over the entire ecosystem, including a potential decrease in the diversity of mechanisms for energy flow. We suggest that keeping existing unimpounded tributaries free of dams, engineering artificial floods, and intensive management of fish habitat within the floodplain may preserve native fish assemblages and help maintain functionality and ecosystem services in highly impounded rivers.
","language":"English","publisher":"Springer","doi":"10.1007/s00027-018-0579-y","usgsCitation":"Granzotti, R.V., Miranda, L.E., Agostinho, A.A., and Gomes, L.C., 2018, Downstream impacts of dams: shifts in benthic invertivorous fish assemblages: Aquatic Sciences, v. 80, p. 1-14, https://doi.org/10.1007/s00027-018-0579-y.","productDescription":"Article 28; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-090186","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Baía River; Ivinhema River; Paraná River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -53,\n -23\n ],\n [\n -53.66,\n -23\n ],\n [\n -53.66,\n -22.33\n ],\n [\n -53,\n -22.33\n ],\n [\n -53,\n -23\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-23","publicationStatus":"PW","scienceBaseUri":"5afee6c2e4b0da30c1bfbdd4","contributors":{"authors":[{"text":"Granzotti, Rafaela Vendrametto","contributorId":204754,"corporation":false,"usgs":false,"family":"Granzotti","given":"Rafaela","email":"","middleInitial":"Vendrametto","affiliations":[],"preferred":false,"id":734880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":734817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Agostinho, Angelo A.","contributorId":204501,"corporation":false,"usgs":false,"family":"Agostinho","given":"Angelo","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":734881,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gomes, Luiz Carlos","contributorId":88227,"corporation":false,"usgs":true,"family":"Gomes","given":"Luiz","email":"","middleInitial":"Carlos","affiliations":[],"preferred":false,"id":734882,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196872,"text":"70196872 - 2018 - Leaf to landscape responses of giant sequoia to hotter drought: An introduction and synthesis for the special section","interactions":[],"lastModifiedDate":"2018-05-08T10:10:22","indexId":"70196872","displayToPublicDate":"2018-05-08T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Leaf to landscape responses of giant sequoia to hotter drought: An introduction and synthesis for the special section","docAbstract":"Hotter droughts are becoming more common as climate change progresses, and they may already have caused instances of forest dieback on all forested continents. Learning from hotter droughts, including where on the landscape forests are more or less vulnerable to these events, is critical to help resource managers proactively prepare for the future. As part of our Leaf to Landscape Project, we measured the response of giant sequoia, the world’s largest tree species, to the extreme 2012–2016 hotter drought in California. The project integrated leaf-level physiology measurements, crown-level foliage dieback surveys, and remotely sensed canopy water content (CWC) to shed light on mechanisms and spatial patterns in drought response. Here we summarize initial findings, present a conceptual model of drought response, and discuss management implications; details are presented in the other four articles of the special section on Giant Sequoias and Drought. Giant sequoias exhibited both leaf- and canopy-level responses that were effective in protecting whole-tree hydraulic integrity for the vast majority of individual sequoias. Very few giant sequoias died during the drought compared to other mixed conifer tree species; however, the magnitude of sequoia drought response varied across the landscape. This variability was partially explained by local site characteristics, including variables related to site water balance. We found that low CWC is an indicator of recent foliage dieback, which occurs when stress levels are high enough that leaf-level adjustments alone are insufficient for giant sequoias to maintain hydraulic integrity. CWC or change in CWC may be useful indicators of drought stress that reveal patterns of vulnerability to future hotter droughts. Future work will measure recovery from the drought and strengthen our ability to interpret CWC maps. Our ultimate goal is to produce giant sequoia vulnerability maps to help target management actions, such as reducing other stressors, increasing resistance to hotter drought through prescribed fire or mechanical thinning, and planting sequoias in projected future suitable habitat, which may occur outside current grove distributions. We suggest that managers compare different types of vulnerability assessments and combine vulnerability maps with other sources of information to inform decisions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2018.03.028","usgsCitation":"Nydick, K.R., Stephenson, N.L., Ambrose, A.R., Asner, G.P., Baxter, W.L., Das, A., Dawson, T.E., Martin, R.E., and Paz-Kagan, T., 2018, Leaf to landscape responses of giant sequoia to hotter drought: An introduction and synthesis for the special section: Forest Ecology and Management, v. 419-420, p. 249-256, https://doi.org/10.1016/j.foreco.2018.03.028.","productDescription":"8 p.","startPage":"249","endPage":"256","ipdsId":"IP-091082","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468772,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2018.03.028","text":"Publisher Index Page"},{"id":353982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"419-420","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c2e4b0da30c1bfbdd0","contributors":{"authors":[{"text":"Nydick, Koren R.","contributorId":196601,"corporation":false,"usgs":false,"family":"Nydick","given":"Koren","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":734830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stephenson, Nathan L. 0000-0003-0208-7229 nstephenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0208-7229","contributorId":2836,"corporation":false,"usgs":true,"family":"Stephenson","given":"Nathan","email":"nstephenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":734829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ambrose, Anthony R.","contributorId":204732,"corporation":false,"usgs":false,"family":"Ambrose","given":"Anthony","email":"","middleInitial":"R.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":734831,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Asner, Gregory P.","contributorId":25393,"corporation":false,"usgs":false,"family":"Asner","given":"Gregory","email":"","middleInitial":"P.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":734832,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baxter, Wendy L.","contributorId":204733,"corporation":false,"usgs":false,"family":"Baxter","given":"Wendy","email":"","middleInitial":"L.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":734833,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Das, Adrian J. 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":3842,"corporation":false,"usgs":true,"family":"Das","given":"Adrian J.","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":734834,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dawson, Todd E.","contributorId":176594,"corporation":false,"usgs":false,"family":"Dawson","given":"Todd","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":734835,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Martin, Roberta E.","contributorId":201234,"corporation":false,"usgs":false,"family":"Martin","given":"Roberta","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":734836,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Paz-Kagan, Tarin","contributorId":196597,"corporation":false,"usgs":false,"family":"Paz-Kagan","given":"Tarin","email":"","affiliations":[],"preferred":false,"id":734837,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70196867,"text":"70196867 - 2018 - Strategies for effective collaborative manuscript development in interdisciplinary science teams","interactions":[],"lastModifiedDate":"2018-05-08T11:31:29","indexId":"70196867","displayToPublicDate":"2018-05-08T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Strategies for effective collaborative manuscript development in interdisciplinary science teams","docAbstract":"Science is increasingly being conducted in large, interdisciplinary teams. As team size increases, challenges can arise during manuscript development, where achieving one team goal (e.g., inclusivity) may be in direct conflict with other goals (e.g., efficiency). Here, we present strategies for effective collaborative manuscript development that draw from our experiences in an interdisciplinary science team writing collaborative manuscripts for six years. These strategies are rooted in six guiding principles that were important to our team: to create a transparent, inclusive, and accountable research team that promotes and protects team members who have less power to influence decision‐making while fostering creativity and productivity. To help alleviate the conflicts that can arise in collaborative manuscript development, we present the following strategies: understand your team composition, create an authorship policy and discuss authorship early and often, openly announce manuscript ideas, identify and communicate the type of manuscript and lead author management style, and document and describe authorship contributions. These strategies can help reduce the probability of group conflict, uphold individual and team values, achieve fair authorship practices, and increase science productivity.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2206","usgsCitation":"Oliver, S., Fergus, C.E., Skaff, N.K., Wagner, T., Tan, P., Cheruvelil, K.S., and Soranno, P.A., 2018, Strategies for effective collaborative manuscript development in interdisciplinary science teams: Ecosphere, v. 9, no. 4, p. 1-13, https://doi.org/10.1002/ecs2.2206.","productDescription":"e02206; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-090031","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468773,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2206","text":"Publisher Index Page"},{"id":354006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-24","publicationStatus":"PW","scienceBaseUri":"5afee6c2e4b0da30c1bfbdd6","contributors":{"authors":[{"text":"Oliver, Samantha K.","contributorId":169273,"corporation":false,"usgs":false,"family":"Oliver","given":"Samantha K.","affiliations":[],"preferred":false,"id":734883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fergus, C. Emi","contributorId":150608,"corporation":false,"usgs":false,"family":"Fergus","given":"C.","email":"","middleInitial":"Emi","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":734884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skaff, Nicholas K.","contributorId":204098,"corporation":false,"usgs":false,"family":"Skaff","given":"Nicholas","email":"","middleInitial":"K.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":734885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734816,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tan, Pang-Ning","contributorId":172193,"corporation":false,"usgs":false,"family":"Tan","given":"Pang-Ning","affiliations":[],"preferred":false,"id":734886,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cheruvelil, Kendra Spence","contributorId":150607,"corporation":false,"usgs":false,"family":"Cheruvelil","given":"Kendra","email":"","middleInitial":"Spence","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":734887,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Soranno, Patricia A.","contributorId":172104,"corporation":false,"usgs":false,"family":"Soranno","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":734888,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196871,"text":"70196871 - 2018 - Application of microtremor horizontal-to-vertical spectral ratio (MHVSR) analysis for site characterization: State of the art","interactions":[],"lastModifiedDate":"2018-05-08T10:13:33","indexId":"70196871","displayToPublicDate":"2018-05-08T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3503,"text":"Surveys in Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Application of microtremor horizontal-to-vertical spectral ratio (MHVSR) analysis for site characterization: State of the art","docAbstract":"Nakamura (Q Rep Railway Tech Res Inst 30:25–33, 1989) popularized the application of the horizontal-to-vertical spectral ratio (HVSR) analysis of microtremor (seismic noise or ambient vibration) recordings to estimate the predominant frequency and amplification factor of earthquake shaking. During the following quarter century, popularity in the microtremor HVSR (MHVSR) method grew; studies have verified the stability of a site’s MHVSR response over time and validated the MHVSR response with that of earthquake HVSR response. Today, MHVSR analysis is a popular reconnaissance tool used worldwide for seismic microzonation and earthquake site characterization in numerous regions, specifically, in the mapping of site period or fundamental frequency and inverted for shear-wave velocity depth profiles, respectively. However, the ubiquity of MHVSR analysis is predominantly a consequence of its ease in application rather than our full understanding of its theory. We present the state of the art in MHVSR analyses in terms of the development of its theoretical basis, current state of practice, and we comment on its future for applications in earthquake site characterization.
","language":"English","publisher":"Springer","doi":"10.1007/s10712-018-9464-4","usgsCitation":"Molnar, S., Cassidy, J.F., Castellaro, S., Cornou, C., Crow, H., Hunter, J.A., Matsushima, S., Sanchez-Sesma, F.J., and Yong, A., 2018, Application of microtremor horizontal-to-vertical spectral ratio (MHVSR) analysis for site characterization: State of the art: Surveys in Geophysics, no. Online First, https://doi.org/10.1007/s10712-018-9464-4.","ipdsId":"IP-097849","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":353984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"Online First","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-06","publicationStatus":"PW","scienceBaseUri":"5afee6c2e4b0da30c1bfbdd2","contributors":{"authors":[{"text":"Molnar, S.","contributorId":203574,"corporation":false,"usgs":false,"family":"Molnar","given":"S.","email":"","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":734821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cassidy, J. F.","contributorId":203575,"corporation":false,"usgs":false,"family":"Cassidy","given":"J.","email":"","middleInitial":"F.","affiliations":[{"id":7219,"text":"Natural Resources Canada","active":true,"usgs":false}],"preferred":false,"id":734823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Castellaro, S.","contributorId":203576,"corporation":false,"usgs":false,"family":"Castellaro","given":"S.","email":"","affiliations":[{"id":36660,"text":"Università di Bologna","active":true,"usgs":false}],"preferred":false,"id":734822,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cornou, C.","contributorId":203577,"corporation":false,"usgs":false,"family":"Cornou","given":"C.","affiliations":[{"id":36661,"text":"Université Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":734824,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crow, H.","contributorId":203578,"corporation":false,"usgs":false,"family":"Crow","given":"H.","email":"","affiliations":[{"id":7219,"text":"Natural Resources Canada","active":true,"usgs":false}],"preferred":false,"id":734825,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hunter, J. A.","contributorId":203579,"corporation":false,"usgs":false,"family":"Hunter","given":"J.","email":"","middleInitial":"A.","affiliations":[{"id":7219,"text":"Natural Resources Canada","active":true,"usgs":false}],"preferred":false,"id":734826,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matsushima, S.","contributorId":203580,"corporation":false,"usgs":false,"family":"Matsushima","given":"S.","email":"","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":734827,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sanchez-Sesma, F. J.","contributorId":204731,"corporation":false,"usgs":false,"family":"Sanchez-Sesma","given":"F.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":734828,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":734820,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70206538,"text":"70206538 - 2018 - A snow density dataset for improving surface boundary conditions in Greenland ice sheet firn modeling","interactions":[],"lastModifiedDate":"2020-06-19T16:12:17.863811","indexId":"70206538","displayToPublicDate":"2018-05-07T10:04:58","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"A snow density dataset for improving surface boundary conditions in Greenland ice sheet firn modeling","docAbstract":"The surface snow density of glaciers and ice sheets is of fundamental importance in converting volume to mass in both altimetry and surface mass balance studies, yet it is often poorly constrained. Site-specific surface snow densities are typically derived from empirical relations based on temperature and wind speed. These parameterizations commonly calculate the average density of the top meter of snow, thereby systematically overestimating snow density at the actual surface. Therefore, constraining surface snow density to the top 0.1 m can improve boundary conditions in high-resolution firn-evolution modeling. We have compiled an extensive dataset of 200 point measurements of surface snow density from firn cores and snow pits on the Greenland ice sheet. We find that surface snow density within 0.1 m of the surface has an average value of 315 kg m−3 with a standard deviation of 44 kg m−3, and has an insignificant annual air temperature dependency. We demonstrate that two widely-used surface snow density parameterizations dependent on temperature systematically overestimate surface snow density over the Greenland ice sheet by 17–19%, and that using a constant density of 315 kg m−3 may give superior results when applied in surface mass budget modeling.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2018.00051","usgsCitation":"Fausto, R., Box, J.E., Baptiste Vandecrux, van As, D., Steffen, K., MacFerrin, M.J., Machguth, H., Colgan, W., Mcgrath, D., Koenig, L.S., Charalampidis, C., and Braithwaite, R.J., 2018, A snow density dataset for improving surface boundary conditions in Greenland ice sheet firn modeling: Frontiers in Earth Science, v. 6, 51, 10 p., https://doi.org/10.3389/feart.2018.00051.","productDescription":"51, 10 p.","ipdsId":"IP-082355","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":468774,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2018.00051","text":"Publisher Index 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S.","contributorId":220465,"corporation":false,"usgs":false,"family":"Koenig","given":"Lora","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":774974,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Charalampidis, Charalampos","contributorId":220466,"corporation":false,"usgs":false,"family":"Charalampidis","given":"Charalampos","email":"","affiliations":[],"preferred":false,"id":774975,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Braithwaite, Roger J.","contributorId":220467,"corporation":false,"usgs":false,"family":"Braithwaite","given":"Roger","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":774976,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70195939,"text":"cir1439 - 2018 - Integrating adaptive management and ecosystem services concepts to improve natural resource management: Challenges and opportunities","interactions":[],"lastModifiedDate":"2018-05-07T13:34:22","indexId":"cir1439","displayToPublicDate":"2018-05-07T10:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1439","title":"Integrating adaptive management and ecosystem services concepts to improve natural resource management: Challenges and opportunities","docAbstract":"Natural resource managers must make decisions that affect broad-scale ecosystem processes involving large spatial areas, complex biophysical interactions, numerous competing stakeholder interests, and highly uncertain outcomes. Natural and social science information and analyses are widely recognized as important for informing effective management. Chief among the systematic approaches for improving the integration of science into natural resource management are two emergent science concepts, adaptive management and ecosystem services. Adaptive management (also referred to as “adaptive decision making”) is a deliberate process of learning by doing that focuses on reducing uncertainties about management outcomes and system responses to improve management over time. Ecosystem services is a conceptual framework that refers to the attributes and outputs of ecosystems (and their components and functions) that have value for humans.
This report explores how ecosystem services can be moved from concept into practice through connection to a decision framework—adaptive management—that accounts for inherent uncertainties. Simultaneously, the report examines the value of incorporating ecosystem services framing and concepts into adaptive management efforts.
Adaptive management and ecosystem services analyses have not typically been used jointly in decision making. However, as frameworks, they have a natural—but to date underexplored—affinity. Both are policy and decision oriented in that they attempt to represent the consequences of resource management choices on outcomes of interest to stakeholders. Both adaptive management and ecosystem services analysis take an empirical approach to the analysis of ecological systems. This systems orientation is a byproduct of the fact that natural resource actions affect ecosystems—and corresponding societal outcomes—often across large geographic scales. Moreover, because both frameworks focus on resource systems, both must confront the analytical challenges of systems modeling—in terms of complexity, dynamics, and uncertainty.
Given this affinity, the integration of ecosystem services analysis and adaptive management poses few conceptual hurdles. In this report, we synthesize discussions from two workshops that considered ways in which adaptive management approaches and ecosystem service concepts may be complementary, such that integrating them into a common framework may lead to improved natural resource management outcomes. Although the literature on adaptive management and ecosystem services is vast and growing, the report focuses specifically on the integration of these two concepts rather than aiming to provide new definitions or an indepth review or primer of the concepts individually.
Key issues considered include the bidirectional links between adaptive decision making and ecosystem services, as well as the potential benefits and inevitable challenges arising in the development and use of an integrated framework. Specifically, the workshops addressed the following questions:
Director, Science and Decisions Center
U.S. Geological Survey
913 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
We consider estimation of the covariance matrix of a multivariate normal distribution when the correlation matrix is separable in the sense that it factors as a Kronecker product of two smaller matrices. A computationally convenient coordinate descent-type algorithm is developed for maximum likelihood estimation. Simulations indicate our method often gives smaller estimation error than some common alternatives when correlation is separable, and that correctly sized tests for correlation separability can be obtained using a parametric bootstrap. Using dissolved oxygen data from the Upper Mississippi River, we illustrate how our model can lead to interesting scientific findings that may be missed when using competing models.
Coastal lagoons are common features of the Puerto Rico shoreline that provide habitat for commercial and recreational species and serve important roles in the nutrient cycle of the ecosystems. The U.S. Geological Survey, in cooperation with the Puerto Rico Environmental Quality Board, conducted a limnological study at Caño Boquerón in Cabo Rojo and at Puerto Mosquito on Isla de Vieques, Puerto Rico, to assess the principal mechanisms affecting the hydrology and water-quality characteristics of these coastal lagoons and provide baseline information to the regulatory agencies responsible for the management and conservation of these coastal waters and the preservation of their aquatic life.
Field measurements and water samples were collected and processed during July 2015–July 2016 for analysis of physical, chemical, biological, and bacteriological characteristics. In addition, bathymetric surveys were made and sediment cores were collected in each lagoon to determine water volume and sediment deposition rate. Physicochemical properties assessed at Caño Boquerón indicated values were generally in compliance with Puerto Rico Environmental Quality Board standards; turbidity was occasionally slightly greater than the established standards, and dissolved oxygen concentration at bottom depths was lower than standards limits. Water transparency was evaluated through the Secchi disk method, and the average depth of disappearance was 1.0 meter (m) for Caño Boquerón and 1.9 m for Puerto Mosquito.
Assessment of biological characteristics at both sites included primary productivity calculations as well as carbon production equivalents and monthly water sampling for bacteriological and nutrient analyses. For Caño Boquerón, gross plankton primary productivity averaged 3.38 grams of oxygen per cubic meter per day (gO2/m3-d); this value was computed as the sum of net phytoplankton primary productivity (0.74 gO2/m3-d) and plankton respiration (2.64 gO2/m3-d). Net community primary productivity averaged 1.44 gO2/m3-d, and the community respiration rate averaged 8.10 gO2/m3-d, which indicates that the biological community, aside from phytoplankton, acts as a net consumer rather than a net producer of biomass. In Puerto Mosquito, gross plankton primary productivity averaged 2.07 gO2/m3-d, of which 0.39 gO2/m3-d could be ascribed to net phytoplankton primary productivity, and 1.68 gO2/m3-d could be ascribed to plankton respiration. Diel studies conducted at Puerto Mosquito reflected an average net community primary productivity of 2.43 gO2/m3-d, and the average respiration rate was 6.72 gO2/m3-d.
In a bathymetric survey conducted in August 2015, the water volume for the Caño Boquerón lagoon was calculated as 967,000 cubic meters (m3), and the water volume at Puerto Mosquito was calculated as 1,182,200 m3, with an average depth of 1.5 m for Caño Boquerón and 1.8 m for Puerto Mosquito. The daily seawater exchange for Caño Boquerón and Puerto Mosquito was 13 and 5 percent of their water volumes referenced to mean sea level, respectively. A total of 20 sediment samples were processed and analyzed for cesium-137 (137Cs) and lead-210 (210Pb) radioisotopes. Analyses indicated that the sediment deposition rate at Caño Boquerón ranged from 0.32 to 0.36 centimeter per year, based on age dating analysis of 137Cs and 210Pb data; in Puerto Mosquito, the sediment deposition rate ranged from 0.26 to 0.27 centimeter per year, based on 137Cs and 210Pb data.
Bacteriological analyses at Caño Boquerón and Puerto Mosquito indicated that fecal coliform and enterococci concentrations were below Puerto Rico Environmental Quality Board standards during the study. The highest concentrations of fecal coliform (22 colonies per 100 milliliters) and enterococci (9 colonies per 100 milliliters) at Caño Boquerón occurred in July, which coincided with the busiest season of vacation rentals near the lagoon. Bacteria concentrations were generally lower in Puerto Mosquito than in Caño Boquerón; maximum concentrations of fecal coliform and enterococci bacteria were measured in November 2015. The potential sources of contamination for Puerto Mosquito are limited, because it is within a conservation area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185018","collaboration":"Prepared in cooperation with the Puerto Rico Environmental Quality Board","usgsCitation":"Gómez-Fragoso, J.M., and Santiago-Sáez, J.A., 2018, Hydrologic and water-quality characteristics of Caño Boquerón, Cabo Rojo, and Puerto Mosquito, Isla de Vieques, Puerto Rico, July 2015–July 2016: U.S. Geological Survey Scientific Investigations Report 2018–5018, 34 p., https://doi.org/10.3133/sir20185018.","productDescription":"Report: ix, 34 p.; Data Release","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-078162","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":437920,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WH2P6K","text":"USGS data release","linkHelpText":"Gomez-Fragoso, Julieta, 2017, Data for the Hydrologic and Water-Quality Characterization of Cano Boqueron, Cabo Rojo, and Puerto Mosquito, Isla de Vieques, Puerto Rico, July 2015-July 2016: U.S. Geological Survey data release"},{"id":353903,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7WH2P6K","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data for the Hydrologic and Water-Quality Characterization of Puerto Mosquito, Vieques and Caño Boquerón, Cabo Rojo, Puerto Rico, July 2015–July 2016"},{"id":353901,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5018/coverthb2.jpg"},{"id":353902,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5018/sir20185018.pdf","text":"Report","size":"10.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5018"}],"country":"United States","otherGeospatial":"Caño Boquerón, Cabo Rojo, Puerto Mosquito, Isla de Vieques, Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.2167,\n 17.9833\n ],\n [\n -67.1333,\n 17.9833\n ],\n [\n -67.1333,\n 18.04\n ],\n [\n -67.2167,\n 18.04\n ],\n [\n -67.2167,\n 17.9833\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -65.4833,\n 18.0833\n ],\n [\n -65.4,\n 18.0833\n ],\n [\n -65.4,\n 18.1333\n ],\n [\n -65.4833,\n 18.1333\n ],\n [\n -65.4833,\n 18.0833\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Our different kinds of minds and types of thinking affect the ways we decide, take action, and cooperate (or not). The comment by Walker et al. (2018, https://doi.org/10.1002/2017EF000750) illustrates several points made by Glynn et al. (2017, https://doi.org/10.1002/2016EF000487) and many other articles. Namely, biases and beliefs often drive scientific reasoning, and scientists, just like other humans, are intimately attached to their values and heuristics. Scientists, just like many other people, also tend to read and interpret text in ways that best match their individual perceptions of a problem or issue: in many cases paraphrasing and changing the meaning of what they read to better match their initial ideas. Walker et al. are doing interesting and important research on uncertainty. Nonetheless, they misinterpret the work, assumptions, and conclusions brought forth by Glynn et al. (2017, https://doi.org/10.1002/2016EF000487).
","language":"English","publisher":"AGU","doi":"10.1002/2018EF000819","usgsCitation":"Glynn, P.D., Voinov, A.A., Shapiro, C.D., and White, P.A., 2018, Response to comment by Walker et al. on “From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments”: Earth's Future, v. 6, no. 5, p. 762-769, https://doi.org/10.1002/2018EF000819.","productDescription":"8 p.","startPage":"762","endPage":"769","ipdsId":"IP-094986","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468776,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2018ef000819","text":"Publisher Index Page"},{"id":353976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-06","publicationStatus":"PW","scienceBaseUri":"5afee6c3e4b0da30c1bfbdda","contributors":{"authors":[{"text":"Glynn, Pierre D. 0000-0001-8804-7003 pglynn@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7003","contributorId":2141,"corporation":false,"usgs":true,"family":"Glynn","given":"Pierre","email":"pglynn@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":734795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voinov, Alexey A.","contributorId":197796,"corporation":false,"usgs":false,"family":"Voinov","given":"Alexey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":734796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shapiro, Carl D. 0000-0002-1598-6808 cshapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-1598-6808","contributorId":3048,"corporation":false,"usgs":true,"family":"Shapiro","given":"Carl","email":"cshapiro@usgs.gov","middleInitial":"D.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":734797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, Paul A.","contributorId":197797,"corporation":false,"usgs":false,"family":"White","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":734798,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198090,"text":"70198090 - 2018 - Crustal structure and quaternary acceleration of deformation rates in central Washington revealed by stream profile inversion, potential field geophysics, and structural geology of the Yakima folds","interactions":[],"lastModifiedDate":"2018-07-23T12:52:42","indexId":"70198090","displayToPublicDate":"2018-05-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Crustal structure and quaternary acceleration of deformation rates in central Washington revealed by stream profile inversion, potential field geophysics, and structural geology of the Yakima folds","docAbstract":"Post‐Miocene tectonic uplift along fault‐cored anticlines within central Washington produced the Yakima Fold Province, a region of active NNE‐SSW shortening in the Cascadian backarc. The relative timing and rate of deformation along individual structures is coarsely defined yet imperative for seismic hazard assessment. In this work, we use geomorphic and geophysical mapping, stream profile inversion, and balanced cross‐section methods to constrain fault geometries and slip rates in the Yakima Canyon region. We extract stream profiles from LiDAR data and analytically solve for the rate of relative rock uplift along several active fault‐cored anticlines. To constrain the fault geometries at depth and the long‐term magnitude of deformation, we constructed two line‐balanced cross sections across the folds with forward‐modeled magnetic and gravity anomaly data. Our stream profile results indicate an increase of incision rates in the Pleistocene, and we infer the increase is tectonically controlled. We estimate modern slip rates between 0.4 and 0.6 mm/year accommodated on reverse faults that core the Manastash Ridge, Umtanum Ridge, and Selah Butte anticlines and establish that these faults reactivate and invert older normal faults in basement rocks. Finally, we calculate the time required to accumulate sufficient strain energy for a large magnitude earthquake (M ≥ 7) along individual structures in the Yakima Fold Province. Results show that the Yakima folds likely accommodate large magnitude earthquakes and that it takes several hundred to several thousand years to accumulate sufficient strain energy for an M ≥ 7 earthquake.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2017TC004916","usgsCitation":"Staisch, L.M., Blakely, R.J., Kelsey, H., Styron, R., and Sherrod, B.L., 2018, Crustal structure and quaternary acceleration of deformation rates in central Washington revealed by stream profile inversion, potential field geophysics, and structural geology of the Yakima folds: Tectonics, v. 37, no. 6, p. 1750-1770, https://doi.org/10.1029/2017TC004916.","productDescription":"21 p.","startPage":"1750","endPage":"1770","ipdsId":"IP-092865","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":468777,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017tc004916","text":"Publisher Index Page"},{"id":355670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Yakima Folds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.364990234375,\n 45.40616374516014\n ],\n [\n -117.7734375,\n 45.40616374516014\n ],\n [\n -117.7734375,\n 49.0738659012854\n ],\n [\n -125.364990234375,\n 49.0738659012854\n ],\n [\n -125.364990234375,\n 45.40616374516014\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-06","publicationStatus":"PW","scienceBaseUri":"5b6fc450e4b0f5d57878ea4f","contributors":{"authors":[{"text":"Staisch, Lydia M. 0000-0002-1414-5994 lstaisch@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-5994","contributorId":167068,"corporation":false,"usgs":true,"family":"Staisch","given":"Lydia","email":"lstaisch@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":739972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":739973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelsey, Harvey","contributorId":106978,"corporation":false,"usgs":true,"family":"Kelsey","given":"Harvey","affiliations":[],"preferred":false,"id":739976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Styron, Richard","contributorId":201082,"corporation":false,"usgs":false,"family":"Styron","given":"Richard","email":"","affiliations":[],"preferred":false,"id":739974,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":739975,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196859,"text":"70196859 - 2018 - Modeling the fish community population dynamics and forecasting the eradication success of an exotic fish from an alpine stream","interactions":[],"lastModifiedDate":"2018-05-07T11:13:53","indexId":"70196859","displayToPublicDate":"2018-05-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the fish community population dynamics and forecasting the eradication success of an exotic fish from an alpine stream","docAbstract":"Management actions aimed at eradicating exotic fish species from riverine ecosystems can be better informed by forecasting abilities of mechanistic models. We illustrate this point with an example of the Logan River, Utah, originally populated with endemic cutthroat trout (Oncorhynchus clarkii utah), which compete with exotic brown trout (Salmo trutta). The coexistence equilibrium was disrupted by a large scale, experimental removal of the exotic species in 2009–2011 (on average, 8.2% of the stock each year), followed by an increase in the density of the native species. We built a spatially-explicit, reaction-diffusion model encompassing four key processes: population growth in heterogeneous habitat, competition, dispersal, and a management action. We calibrated the model with detailed long-term monitoring data (2001–2016) collected along the 35.4-km long river main channel. Our model, although simple, did a remarkable job reproducing the system steady state prior to the management action. Insights gained from the model independent predictions are consistent with available knowledge and indicate that the exotic species is more competitive; however, the native species still occupies more favorable habitat upstream. Dynamic runs of the model also recreated the observed increase of the native species following the management action. The model can simulate two possible distinct long-term outcomes: recovery or eradication of the exotic species. The processing of available knowledge using Bayesian methods allowed us to conclude that the chance for eradication of the invader was low at the beginning of the experimental removal (0.7% in 2009) and increased (20.5% in 2016) by using more recent monitoring data. We show that accessible mathematical and numerical tools can provide highly informative insights for managers (e.g., outcome of their conservation actions), identify knowledge gaps, and provide testable theory for researchers.
The hydrogeologic setting and groundwater flow system in Florida and parts of Georgia, Alabama, and South Carolina is dominated by the highly transmissive Floridan aquifer system. This principal aquifer is a vital source of freshwater for public and domestic supply, as well as for industrial and agricultural uses throughout the southeastern United States. Population growth, increased tourism, and increased agricultural production have led to increased demand on groundwater from the Floridan aquifer system, particularly since 1950. The response of the Floridan aquifer system to these stresses often poses regional challenges for water-resource management that commonly transcend political or jurisdictional boundaries. To help water-resource managers address these regional challenges, the U.S. Geological Survey (USGS) Water Availability and Use Science Program began assessing groundwater availability of the Floridan aquifer system in 2009.
The current conceptual groundwater flow system was developed for the Floridan aquifer system and adjacent systems partly on the basis of previously published USGS Regional Aquifer-System Analysis (RASA) studies, specifically many of the potentiometric maps and the modeling efforts in these studies. The Floridan aquifer system extent was divided into eight hydrogeologically distinct subregional groundwater basins delineated on the basis of the estimated predevelopment (circa 1880s) potentiometric surface: (1) Panhandle, (2) Dougherty Plain-Apalachicola, (3) Thomasville-Tallahassee, (4) Southeast Georgia-Northeast Florida-South South Carolina, (5) Suwannee, (6) West-central Florida, (7) East-central Florida, and (8) South Florida. The use of these subregions allows for a more detailed analysis of the individual basins and the groundwater flow system as a whole.
The hydrologic conditions and associated groundwater budget were updated relative to previous RASA studies to include additional data collected since the 1980s and to reflect the entire groundwater flow system, including the surficial, intermediate, and Floridan aquifer systems for a contemporary period (1995–2010). Inflow to the groundwater flow system of 33,700 million gallons per day (Mgal/d) was assumed to be exclusively from net recharge (precipitation minus evapotranspiration and surface runoff). Outflow from the groundwater flow system included spring discharge (7,700 Mgal/d) and groundwater withdrawals (5,200 Mgal/d). Estimates for all components of the groundwater system were not possible because of large uncertainties associated with internal leakage, coastal discharge, and discharge to streams and lakes. A numerical modeling analysis is required to improve this hydrologic budget calculation and to forecast future changes in groundwater levels and aquifer storage caused by groundwater withdrawals, land-use change, and the effects of climate variability and change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185030","collaboration":"Water Availability and Use Science Program","usgsCitation":"Bellino, J.C., Kuniansky, E.L., O’Reilly, A.M., and Dixon, J.F., 2018, Hydrogeologic setting, conceptual groundwater flow system, and hydrologic conditions 1995–2010 in Florida and parts of Georgia, Alabama, and South Carolina: U.S. Geological Survey Scientific Investigations Report 2018–5030, 103 p., https://doi.org/10.3133/sir20185030.","productDescription":"Report: viii, 103 p.; Plate: 36.0 x 49.0 inches; Data Releases","numberOfPages":"115","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056534","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":353934,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2018/5030/sir20185030_plate.pdf","text":"Plate 1","size":"3.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5030 Plate 1"},{"id":353936,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CJ8BMS","text":"USGS data release","description":"USGS Data Release","linkHelpText":" Soil-Water-Balance model datasets used to estimate mean groundwater recharge in Florida and parts of Georgia, Alabama, and South Carolina, 1995–2010"},{"id":353933,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5030/sir20185030.pdf","text":"Report","size":"46.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5030"},{"id":353932,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5030/coverthb2.jpg"},{"id":353937,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75Q4TZD","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Potentiometric Surface Contours, Wells, and Groundwater Basin Divides for the Upper Floridan Aquifer in Florida and Parts of Georgia, South Carolina, and Alabama, May–June 2010—Updated"},{"id":353935,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78K7749","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Groundwater Withdrawals in Florida and parts of Georgia, Alabama, and South Carolina, 1995–2010"}],"country":"United States","state":"Alabama, Florida, Georgia, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.17626953125,\n 24.467150664739002\n ],\n [\n -79.6728515625,\n 24.467150664739002\n ],\n [\n -79.6728515625,\n 32.85190345738802\n ],\n [\n -88.17626953125,\n 32.85190345738802\n ],\n [\n -88.17626953125,\n 24.467150664739002\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane
Lutz, FL 33559
Maintaining intraspecific diversity is an important goal for fisheries conservation and recovery actions. While ecomorphological studies have demonstrated intraspecific diversity related to feeding or flow regime, there has been little assessment of such variation in regard to spawning habitat. We evaluated the relationship between individual morphology of Robust Redhorse and Notchlip Redhorse and variables describing the spawning habitat from which they were captured, such as current velocity, depth, and substrate particle size. Robust Redhorse (n = 58) and Notchlip Redhorse (n = 43) were captured from spawning aggregations in the lower Savannah River, South Carolina-Georgia using prepositioned grid electrofishers. They were then measured and photographed before being released. We constructed a truss network using digitized landmarks on each of the photographs. Relationships between the morphological and environmental datasets were assessed using canonical correlation analysis. In both species, these morphological predictors were correlated primarily to depth, though current velocity also contributed to the environmental canonical score for Robust Redhorse. Robust Redhorse captured from the deeper locations with higher current velocities had heads with lower aspect ratio compared to individuals captured from shallower areas. Notchlip Redhorse from shallower areas were deeper-bodied and had shorter trunks than counterparts from deeper areas. These differences suggest that ensuring spawning habitat heterogeneity may be an important component to conserving intraspecific diversity, particularly in systems where such habitat is limiting.
","language":"English","publisher":"Springer","doi":"10.1007/s10641-018-0772-9","usgsCitation":"Grabowski, T.B., Pease, J.E., and Groeschel, J.R., 2018, Intraspecific differences in morphology correspond to differential spawning habitat use in two riverine catostomid species: Environmental Biology of Fishes, v. 101, no. 8, p. 1249-1260, https://doi.org/10.1007/s10641-018-0772-9.","productDescription":"12 p.","startPage":"1249","endPage":"1260","ipdsId":"IP-089415","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":356615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia, South Carolina","otherGeospatial":"Savannah River","volume":"101","issue":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-04","publicationStatus":"PW","scienceBaseUri":"5b98a2c6e4b0702d0e842fe8","contributors":{"authors":[{"text":"Grabowski, Timothy B. 0000-0001-9763-8948 tgrabowski@usgs.gov","orcid":"https://orcid.org/0000-0001-9763-8948","contributorId":4178,"corporation":false,"usgs":true,"family":"Grabowski","given":"Timothy","email":"tgrabowski@usgs.gov","middleInitial":"B.","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":742845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pease, Jessica E.","contributorId":201491,"corporation":false,"usgs":false,"family":"Pease","given":"Jessica","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":743046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Groeschel, Jillian R.","contributorId":172958,"corporation":false,"usgs":false,"family":"Groeschel","given":"Jillian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":743047,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198081,"text":"70198081 - 2018 - A tale of two wildfires; testing detection and prediction of invasive species distributions using models fit with topographic and spectral indices","interactions":[],"lastModifiedDate":"2018-07-16T11:25:35","indexId":"70198081","displayToPublicDate":"2018-05-04T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A tale of two wildfires; testing detection and prediction of invasive species distributions using models fit with topographic and spectral indices","docAbstract":"Context
Developing species distribution models (SDMs) to detect invasive species cover and evaluate habitat suitability are high priorities for land managers.
Objectives
We tested SDMs fit with different variable combinations to provide guidelines for future invasive species model development based on transferability between landscapes.
Methods
Generalized linear model, boosted regression trees, multivariate adaptive regression splines, and Random Forests were fit with location data for high cheatgrass (Bromus tectorum) cover in situ for two post-burn sites independently using topographic indices, spectral indices derived from multiple dates of Landsat 8 satellite imagery, or both. Models developed for one site were applied to the other, using independent cheatgrass cover data from the respective ex situ site to test model transferability.
Results
Fitted models were statistically robust and comparable when fit with at least 200 cover plots in situ and transferred to the ex situ site. Only the Random Forests models were robust when fit with a small number of cover plots in situ.
Conclusions
Our study indicated spectral indices can be used in SDMs to estimate species cover across landscapes (e.g., both within the same Landsat scene and in an adjacent Landsat scene). Important considerations for transferability include the model employed, quantity of cover data used to train/test the models, and phenology of the species coupled with the timing of imagery. The results also suggest that when cover data are limited, SDMs fit with topographic indices are sufficient for evaluating cheatgrass habitat suitability in new post-disturbance landscapes; however, spectral indices can provide a more robust estimate for detection based on local phenology.
Wetlands in the Prairie Pothole Region (PPR) of North America support macroinvertebrate communities that are integral to local food webs and important to breeding waterfowl. Macroinvertebrates in PPR wetlands are primarily generalists and well adapted to within and among year changes in water permanence and salinity. The Williston Basin, a major source of U.S. energy production, underlies the southwest portion of the PPR. Development of oil and gas results in the coproduction of large volumes of highly saline, sodium chloride dominated water (brine) and the introduction of brine can alter wetland salinity. To assess potential effects of brine contamination on macroinvertebrate communities, 155 PPR wetlands spanning a range of hydroperiods and salinities were sampled between 2014 and 2016. Brine contamination was documented in 34 wetlands with contaminated wetlands having significantly higher chloride concentrations, specific conductance and percent dominant taxa, and significantly lower taxonomic richness, Shannon diversity, and Pielou evenness scores compared to uncontaminated wetlands. Non-metric multidimensional scaling found significant correlations between several water quality parameters and macroinvertebrate communities. Chloride concentration and specific conductance, which can be elevated in naturally saline wetlands, but are also associated with brine contamination, had the strongest correlations. Five wetland groups were identified from cluster analysis with many of the highly contaminated wetlands located in a single cluster. Low or moderately contaminated wetlands were distributed among the remaining clusters and had macroinvertebrate communities similar to uncontaminated wetlands. While aggregate changes in macroinvertebrate community structure were observed with brine contamination, systematic changes were not evident, likely due to the strong and potentially confounding influence of hydroperiod and natural salinity. Therefore, despite the observed negative response of macroinvertebrate communities to brine contamination, macroinvertebrate community structure alone is likely not the most sensitive indicator of brine contamination in PPR wetlands.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2018.04.088","usgsCitation":"Preston, T.M., Borgreen, M.J., and Ray, A.M., 2018, Effects of brine contamination from energy development on wetland macroinvertebrate community structure in the Prairie Pothole Region: Environmental Pollution, v. 239, p. 722-732, https://doi.org/10.1016/j.envpol.2018.04.088.","productDescription":"11 p.","startPage":"722","endPage":"732","ipdsId":"IP-093113","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":437922,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DB8141","text":"USGS data release","linkHelpText":"Macroinvertebrate and water quality data from the Prairie Pothole Region of the Williston Basin (2014-2016)"},{"id":353964,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","otherGeospatial":"Williston Basin","volume":"239","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c3e4b0da30c1bfbde2","contributors":{"authors":[{"text":"Preston, Todd M. 0000-0002-8812-9233","orcid":"https://orcid.org/0000-0002-8812-9233","contributorId":204676,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","email":"","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":734648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borgreen, Michael J. 0000-0002-5879-6414","orcid":"https://orcid.org/0000-0002-5879-6414","contributorId":204677,"corporation":false,"usgs":false,"family":"Borgreen","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":734649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ray, Andrew M.","contributorId":167601,"corporation":false,"usgs":false,"family":"Ray","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":734650,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196175,"text":"fs20183014 - 2018 - Assessment of undiscovered continuous oil and gas resources of Upper Cretaceous Shales in the Songliao Basin of China, 2017","interactions":[],"lastModifiedDate":"2018-05-03T13:56:59","indexId":"fs20183014","displayToPublicDate":"2018-05-03T12:40:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3014","title":"Assessment of undiscovered continuous oil and gas resources of Upper Cretaceous Shales in the Songliao Basin of China, 2017","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean undiscovered, technically recoverable resources of 3.3 billion barrels of oil and 887 billion cubic feet of gas in shale reservoirs of the Upper Cretaceous Qingshankou and Nenjiang Formations in the Songliao Basin of northeastern China.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183014","usgsCitation":"Potter, C.J., Schenk, C.J., Pitman, J.K., Klett, T.R., Tennyson, M.E., Gaswirth, S.B., Leathers-Miller, H.M., Finn, T.M., Brownfield, M.E., Mercier, T.J., Marra, K.R., and Woodall, C.A., 2018, Assessment of undiscovered continuous oil and gas resources of Upper Cretaceous Shales in the Songliao Basin of China, 2017: U.S. Geological Survey Fact Sheet 2018–3014, 2 p., https://doi.org/10.3133/fs20183014.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-092276","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":353925,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3014/fs20183014.pdf","text":"Report","size":"1.24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3014"},{"id":353924,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3014/coverthb.jpg"}],"country":"China","otherGeospatial":"Songliao Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 120,\n 42.5\n ],\n [\n 128,\n 42.5\n ],\n [\n 128,\n 50\n ],\n [\n 120,\n 50\n ],\n [\n 120,\n 42.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Many species have distributions that span distinctly different physiographic regions, and effective conservation of such taxa will require a full accounting of all factors that potentially influence populations. Ecologists recognize effects of physiographic differences in topography, geology and climate on local habitat configurations, and thus the relevance of landscape heterogeneity to species distributions and abundances. However, research is lacking that examines how physiography affects the processes underlying metapopulation dynamics. We used data describing occupancy dynamics of stream fishes to evaluate evidence that physiography influences rates at which individual taxa persist in or colonize stream reaches under different flow conditions. Using periodic survey data from a stream fish assemblage in a large river basin that encompasses multiple physiographic regions, we fit multi-species dynamic occupancy models. Our modeling results suggested that stream fish colonization but not persistence was strongly governed by physiography, with estimated colonization rates considerably higher in Coastal Plain streams than in Piedmont and Blue Ridge systems. Like colonization, persistence was positively related to an index of stream flow magnitude, but the relationship between flow and persistence did not depend on physiography. Understanding the relative importance of colonization and persistence, and how one or both processes may change across the landscape, is critical information for the conservation of broadly distributed taxa, and conservation strategies explicitly accounting for spatial variation in these processes are likely to be more successful for such taxa.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.04.023","usgsCitation":"Wheeler, K., Wenger, S., Walsh, S.J., Martin, Z.P., Jelks, H.L., and Freeman, M., 2018, Stream fish colonization but not persistence varies regionally across a large North American river basin: Biological Conservation, v. 223, p. 1-10, https://doi.org/10.1016/j.biocon.2018.04.023.","productDescription":"10 p.","startPage":"1","endPage":"10","ipdsId":"IP-091967","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":460780,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2018.04.023","text":"Publisher Index Page"},{"id":353928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Georgia","otherGeospatial":"Apalachicola-Chattahoochee-Flint River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.792236328125,\n 30.65681556429287\n ],\n [\n -83.38623046875,\n 30.65681556429287\n ],\n [\n -83.38623046875,\n 34.939985151560435\n ],\n [\n -85.792236328125,\n 34.939985151560435\n ],\n [\n -85.792236328125,\n 30.65681556429287\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"223","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c3e4b0da30c1bfbde4","contributors":{"authors":[{"text":"Wheeler, Kit","contributorId":203872,"corporation":false,"usgs":false,"family":"Wheeler","given":"Kit","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":734573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":734574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, Stephen J. 0000-0002-1009-8537 swalsh@usgs.gov","orcid":"https://orcid.org/0000-0002-1009-8537","contributorId":1456,"corporation":false,"usgs":true,"family":"Walsh","given":"Stephen","email":"swalsh@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":734577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Zachary P. 0000-0001-5779-3548 zmartin@usgs.gov","orcid":"https://orcid.org/0000-0001-5779-3548","contributorId":204653,"corporation":false,"usgs":false,"family":"Martin","given":"Zachary","email":"zmartin@usgs.gov","middleInitial":"P.","affiliations":[{"id":36970,"text":"Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA, USA","active":true,"usgs":false}],"preferred":false,"id":734576,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jelks, Howard L. 0000-0002-0672-6297 hjelks@usgs.gov","orcid":"https://orcid.org/0000-0002-0672-6297","contributorId":168997,"corporation":false,"usgs":true,"family":"Jelks","given":"Howard","email":"hjelks@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":734575,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":734572,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196406,"text":"ds1083 - 2018 - Soil moisture datasets at five sites in the central Sierra Nevada and northern Coast Ranges, California","interactions":[],"lastModifiedDate":"2018-05-04T10:15:17","indexId":"ds1083","displayToPublicDate":"2018-05-03T00:00:00","publicationYear":"2018","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":"1083","title":"Soil moisture datasets at five sites in the central Sierra Nevada and northern Coast Ranges, California","docAbstract":"In situ soil moisture datasets are important inputs used to calibrate and validate watershed, regional, or statewide modeled and satellite-based soil moisture estimates. The soil moisture dataset presented in this report includes hourly time series of the following: soil temperature, volumetric water content, water potential, and total soil water content. Data were collected by the U.S. Geological Survey at five locations in California: three sites in the central Sierra Nevada and two sites in the northern Coast Ranges. This report provides a description of each of the study areas, procedures and equipment used, processing steps, and time series data from each site in the form of comma-separated values (.csv) tables.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1083","collaboration":"Prepared in cooperation with the California Department of Water Resources, National Park Service, and Pepperwood Preserve","usgsCitation":"Stern, M.A., Anderson, F.A., Flint, L.E., and Flint, A.L., 2018, Soil moisture datasets at five sites in the central Sierra Nevada and northern Coast Ranges, California: U.S. Geological Survey Data Series 1083, 23 p., https://doi.org/10.3133/ds1083.","productDescription":"Report: viii, 23 p.; 5 Tables","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080152","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":353696,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1083/coverthb.jpg"},{"id":353697,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1083/ds1083_.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Data Series 1083"},{"id":353698,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/1083/ds1083_tables12-15_17.zip","text":"Tables 12, 13, 14, 15, and 17","size":"5.3 MB","linkFileType":{"id":6,"text":"zip"},"description":"Data Series 1083 table files"}],"country":"United States","state":"California","otherGeospatial":"Central Sierra Nevada Range, Northern Coast Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.83612060546874,\n 37.73379707124429\n ],\n [\n -119.20852661132812,\n 37.73379707124429\n ],\n [\n -119.20852661132812,\n 37.965854128749434\n ],\n [\n -119.83612060546874,\n 37.965854128749434\n ],\n [\n -119.83612060546874,\n 37.73379707124429\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6963424682617,\n 38.56887107621966\n ],\n [\n -122.68930435180664,\n 38.56887107621966\n ],\n [\n -122.68930435180664,\n 38.57256189519067\n ],\n [\n -122.6963424682617,\n 38.57256189519067\n ],\n [\n -122.6963424682617,\n 38.56887107621966\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
No abstract available.
","language":"English","publisher":"Wildlife Disease Association","usgsCitation":"Richards, B.J., Bodenstein, B., Ballmann, A., and White, C.L., 2018, Quarterly wildlife mortality report April 2018: Wildlife Disease Association Newsletter, p. 19-21.","productDescription":"3 p.","startPage":"19","endPage":"21","ipdsId":"IP-096493","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":357994,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":357989,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.wildlifedisease.org/PersonifyEbusiness/Resources/Publications/Newsletter/Archive"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02ff8e4b0fc368eb539b2","contributors":{"authors":[{"text":"Richards, Bryan J. 0000-0001-9955-2523 brichards@usgs.gov","orcid":"https://orcid.org/0000-0001-9955-2523","contributorId":3533,"corporation":false,"usgs":true,"family":"Richards","given":"Bryan","email":"brichards@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":746987,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bodenstein, Barbara L. 0000-0001-7946-0103 bbodenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-7946-0103","contributorId":189820,"corporation":false,"usgs":true,"family":"Bodenstein","given":"Barbara","email":"bbodenstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":746988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ballmann, Anne 0000-0002-0380-056X aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":746989,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, C. LeAnn 0000-0002-5004-5165 clwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-5004-5165","contributorId":4315,"corporation":false,"usgs":true,"family":"White","given":"C.","email":"clwhite@usgs.gov","middleInitial":"LeAnn","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":746990,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}