Atoll and island coastal communities are highly exposed to sea-level rise, tsunamis, storm surges, rogue waves, king tides, and the occasional combination of multiple factors, such as high regional sea levels, extreme high local tides, and unusually strong wave set-up. The elevation of most of these atolls averages just under 3 meters (m), with many areas roughly at sea level. The lack of high-resolution topographic data has been identified as a critical data gap for hazard vulnerability and adaptation efforts and for high-resolution inundation modeling for atoll nations. Modern topographic survey equipment and airborne lidar surveys can be very difficult and costly to deploy. Therefore, unmanned aircraft systems (UAS) were investigated for collecting overlapping imagery to generate topographic digital elevation models (DEMs). Medium- and high-resolution satellite imagery (Landsat 8 and WorldView-3) was investigated to derive nearshore bathymetry.
The Republic of the Marshall Islands is associated with the United States through a Compact of Free Association, and Majuro Atoll is home to the capital city of Majuro and the largest population of the Republic of the Marshall Islands. The only elevation datasets currently available for the entire Majuro Atoll are the Shuttle Radar Topography Mission and the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model Version 2 elevation data, which have a 30-m grid-cell spacing and a 8-m vertical root mean square error (RMSE). Both these datasets have inadequate spatial resolution and vertical accuracy for inundation modeling.
The final topobathymetric DEM (TBDEM) developed for Majuro Atoll is derived from various data sources including charts, soundings, acoustic sonar, and UAS and satellite imagery spanning over 70 years of data collection (1944 to 2016) on different sections of the atoll. The RMSE of the TBDEM over the land area is 0.197 m using over 70,000 Global Navigation Satellite System real-time kinematic survey points for validation, and 1.066 m for Landsat 8 and 1.112 m for WorldView-3 derived bathymetry using over 16,000 and 9,000 lidar bathymetry points, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185047","usgsCitation":"Palaseanu-Lovejoy, M., Poppenga, S.K., Danielson, J.J., Tyler, D.J., Gesch, D.B., Kottermair, M., Jalandoni, A., Carlson, E., Thatcher, C.A., and Barbee, M.M., 2018, One-meter topobathymetric digital elevation model for Majuro Atoll, Republic of the Marshall Islands, 1944 to 2016: U.S. Geological Survey Scientific Investigations Report 2018–5047, 16 p., https://doi.org/10.3133/sir20185047.","productDescription":"vii, 16 p.","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-090429","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":352868,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5047/sir20185047.pdf","text":"Report","size":"2.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5047"},{"id":352867,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5047/coverthb.jpg"}],"country":"Republic of the Marshall Islands","otherGeospatial":"Majuro Atoll","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 170.96923828125,\n 7.009578865370235\n ],\n [\n 171.42654418945312,\n 7.009578865370235\n ],\n [\n 171.42654418945312,\n 7.261669781279355\n ],\n [\n 170.96923828125,\n 7.261669781279355\n ],\n [\n 170.96923828125,\n 7.009578865370235\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geographic Science Center
U.S. Geological Survey
Mail Stop 521
12201 Sunrise Valley Drive
Reston, VA 20192
This study presents a synthesis of century-scale hydroclimate variations in North America for the Common Era (last 2000 years) using new age models of previously published multiple proxy-based paleoclimate data. This North American Hydroclimate Synthesis (NAHS) examines regional hydroclimate patterns and related environmental indicators, including vegetation, lake water elevation, stream flow and runoff, cave drip rates, biological productivity, assemblages of living organisms, and salinity. Centennial-scale hydroclimate anomalies are obtained by iteratively sampling the proxy data on each of thousands of age model realizations and determining the fractions of possible time series indicating that the century-smoothed data was anomalously wet or dry relative to the 100 BCE to 1900 CE mean. Results suggest regionally asynchronous wet and dry periods over multidecadal to centennial timescales and frequent periods of extended regional drought. Most sites indicate drying during previously documented multicentennial periods of warmer Northern Hemisphere temperatures, particularly in the western U.S., central U.S., and Canada. Two widespread droughts were documented by the NAHS: from 50 BCE to 450 CE and from 800 to 1100 CE. Major hydroclimate reorganizations occurred out of sync with Northern Hemisphere temperature variations and widespread wet and dry anomalies occurred during both warm and cool periods. We present a broad assessment of paleoclimate relationships that highlights the potential influences of internal variability and external forcing and supports a prominent role for Pacific and Atlantic Ocean dynamics on century-scale continental hydroclimate.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gloplacha.2017.12.025","usgsCitation":"Rodysill, J.R., Anderson, L., Cronin, T.M., Jones, M.C., Thompson, R.S., Wahl, D.B., Willard, D.A., Addison, J.A., Alder, J.R., Anderson, K.H., Anderson, L., Barron, J.A., Bernhardt, C.E., Hostetler, S.W., Kehrwald, N.M., Khan, N., Richey, J.N., Starratt, S.W., Strickland, L.E., Toomey, M., Treat, C.C., and Wingard, G.L., 2018, A North American Hydroclimate Synthesis (NAHS) of the Common Era: Global and Planetary Change, v. 162, p. 175-198, https://doi.org/10.1016/j.gloplacha.2017.12.025.","productDescription":"24 p.","startPage":"175","endPage":"198","ipdsId":"IP-089799","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - 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While land change impacts on ecosystem carbon dynamics have been the focus of numerous studies, few efforts have been based on observational data incorporating multiple ecosystem types spanning large geographic areas over long time horizons. In this study we use a variety of synoptic-scale remote sensing data to estimate the effect of LULC changes associated with urbanization, agricultural expansion and contraction, forest harvest, and wildfire on the carbon balance of terrestrial ecosystems (forest, grasslands, shrublands, and agriculture) in the conterminous United States (i.e. excluding Alaska and Hawaii) between 1973 and 2010. We estimate large net declines in the area of agriculture and forest, along with relatively small increases in grasslands and shrublands. The largest net change in any class was an estimated gain of 114 865 km2 of developed lands, an average rate of 3282 km2 yr−1. On average, US ecosystems sequestered carbon at an annual rate of 254 Tg C yr−1. In forest lands, the net sink declined by 35% over the study period, largely a result of land-use legacy, increasing disturbances, and reductions in forest area due to land use conversion. Uncertainty in LULC change data contributed to a ~16% margin of error in the annual carbon sink estimate prior to 1985 (approximately ±40 Tg C yr−1). Improvements in LULC and disturbance mapping starting in the mid-1980s reduced this uncertainty by ~50% after 1985. We conclude that changes in LULC are a critical component to understanding ecosystem carbon dynamics, and continued improvements in detection, quantification, and attribution of change have the potential to significantly reduce current uncertainties.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/aab540","usgsCitation":"Sleeter, B.M., Liu, J., Daniel, C., Rayfield, B., Sherba, J.T., Hawbaker, T., Zhu, Z., Selmants, P., and Loveland, T., 2018, Effects of contemporary land-use and land-cover change on the carbon balance of terrestrial ecosystems in the United States: Environmental Research Letters, v. 13, Article 045006; 13 p., https://doi.org/10.1088/1748-9326/aab540.","productDescription":"Article 045006; 13 p.","ipdsId":"IP-093889","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":468880,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aab540","text":"Publisher Index Page"},{"id":352987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-29","publicationStatus":"PW","scienceBaseUri":"5afee6f5e4b0da30c1bfbfa7","contributors":{"authors":[{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Jinxun 0000-0003-0561-8988 jxliu@usgs.gov","orcid":"https://orcid.org/0000-0003-0561-8988","contributorId":3414,"corporation":false,"usgs":true,"family":"Liu","given":"Jinxun","email":"jxliu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":732103,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daniel, Colin 0000-0001-7367-2041","orcid":"https://orcid.org/0000-0001-7367-2041","contributorId":203689,"corporation":false,"usgs":false,"family":"Daniel","given":"Colin","email":"","affiliations":[{"id":36689,"text":"Apex Resource Management Solutions; University of Toronto","active":true,"usgs":false}],"preferred":false,"id":732104,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rayfield, Bronwyn 0000-0003-1768-1300","orcid":"https://orcid.org/0000-0003-1768-1300","contributorId":203690,"corporation":false,"usgs":false,"family":"Rayfield","given":"Bronwyn","email":"","affiliations":[{"id":36690,"text":"Apex Resource Management Solutions","active":true,"usgs":false}],"preferred":false,"id":732105,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherba, Jason T. 0000-0001-9151-686X jsherba@usgs.gov","orcid":"https://orcid.org/0000-0001-9151-686X","contributorId":196154,"corporation":false,"usgs":true,"family":"Sherba","given":"Jason","email":"jsherba@usgs.gov","middleInitial":"T.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":732106,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":732107,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true}],"preferred":true,"id":732108,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Selmants, Paul 0000-0001-6211-3957 pselmants@usgs.gov","orcid":"https://orcid.org/0000-0001-6211-3957","contributorId":192591,"corporation":false,"usgs":true,"family":"Selmants","given":"Paul","email":"pselmants@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":732109,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Loveland, Thomas R. 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":3005,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas R.","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":732110,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70196289,"text":"70196289 - 2018 - Phylogeny and species traits predict bird detectability","interactions":[],"lastModifiedDate":"2018-10-04T13:31:07","indexId":"70196289","displayToPublicDate":"2018-03-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Phylogeny and species traits predict bird detectability","docAbstract":"Avian acoustic communication has resulted from evolutionary pressures and ecological constraints. We therefore expect that auditory detectability in birds might be predictable by species traits and phylogenetic relatedness. We evaluated the relationship between phylogeny, species traits, and field‐based estimates of the two processes that determine species detectability (singing rate and detection distance) for 141 bird species breeding in boreal North America. We used phylogenetic mixed models and cross‐validation to compare the relative merits of using trait data only, phylogeny only, or the combination of both to predict detectability. We found a strong phylogenetic signal in both singing rates and detection distances; however the strength of phylogenetic effects was less than expected under Brownian motion evolution. The evolution of behavioural traits that determine singing rates was found to be more labile, leaving more room for species to evolve independently, whereas detection distance was mostly determined by anatomy (i.e. body size) and thus the laws of physics. Our findings can help in disentangling how complex ecological and evolutionary mechanisms have shaped different aspects of detectability in boreal birds. Such information can greatly inform single‐ and multi‐species models but more work is required to better understand how to best correct possible biases in phylogenetic diversity and other community metrics.
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.03415","usgsCitation":"Solymos, P., Matsuoka, S.M., Stralberg, D., Barker, N.K., and Bayne, E.M., 2018, Phylogeny and species traits predict bird detectability: Ecography, v. 41, no. 10, p. 1595-1603, https://doi.org/10.1111/ecog.03415.","productDescription":"9 p.","startPage":"1595","endPage":"1603","ipdsId":"IP-088898","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":353019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-09","publicationStatus":"PW","scienceBaseUri":"5afee6f4e4b0da30c1bfbfa3","contributors":{"authors":[{"text":"Solymos, Peter","contributorId":203718,"corporation":false,"usgs":false,"family":"Solymos","given":"Peter","email":"","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":732170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matsuoka, Steven M. 0000-0001-6415-1885 smatsuoka@usgs.gov","orcid":"https://orcid.org/0000-0001-6415-1885","contributorId":184173,"corporation":false,"usgs":true,"family":"Matsuoka","given":"Steven","email":"smatsuoka@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":732169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stralberg, Diana","contributorId":187413,"corporation":false,"usgs":false,"family":"Stralberg","given":"Diana","email":"","affiliations":[],"preferred":false,"id":732171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barker, Nicole K. S.","contributorId":203720,"corporation":false,"usgs":false,"family":"Barker","given":"Nicole","email":"","middleInitial":"K. S.","affiliations":[{"id":36697,"text":"Boreal Avian Modeling Project","active":true,"usgs":false}],"preferred":false,"id":732172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bayne, Erin M.","contributorId":140675,"corporation":false,"usgs":false,"family":"Bayne","given":"Erin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":732173,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196237,"text":"ofr20181030 - 2018 - GIS database and discussion for the distribution, composition, and age of Cenozoic volcanic rocks of the Pacific Northwest Volcanic Aquifer System study area","interactions":[],"lastModifiedDate":"2018-04-11T11:26:08","indexId":"ofr20181030","displayToPublicDate":"2018-03-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1030","title":"GIS database and discussion for the distribution, composition, and age of Cenozoic volcanic rocks of the Pacific Northwest Volcanic Aquifer System study area","docAbstract":"A substantial part of the U.S. Pacific Northwest is underlain by Cenozoic volcanic and continental sedimentary rocks and, where widespread, these strata form important aquifers. The legacy geologic mapping presented with this report contains new thematic categorization added to state digital compilations published by the U.S. Geological Survey for Oregon, California, Idaho, Nevada, Utah, and Washington (Ludington and others, 2005). Our additional coding is designed to allow rapid characterization, mainly for hydrogeologic purposes, of similar rocks and deposits within a boundary expanded slightly beyond that of the Pacific Northwest Volcanic Aquifer System study area. To be useful for hydrogeologic analysis and to be more statistically manageable, statewide compilations from Ludington and others (2005) were mosaicked into a regional map and then reinterpreted into four main categories on the basis of (1) age, (2) composition, (3) hydrogeologic grouping, and (4) lithologic pattern. The coding scheme emphasizes Cenozoic volcanic or volcanic-related rocks and deposits, and of primary interest are the codings for composition and age.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181030","usgsCitation":"Sherrod, D.R., and Keith, M.K., 2018, GIS database and discussion for the distribution, composition, and age of Cenozoic volcanic rocks of the Pacific Northwest Volcanic Aquifer System study area: U.S. Geological Survey Open-File Report 2018–1030, 16 p., https://doi.org/10.3133/ofr20181030. ","productDescription":"Pamphlet: iv, 16 p.; Spatial data; Metadata; Readme","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085785","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":353011,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/2018/1030/ofr20181030_readme.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2018-1030 Read Me"},{"id":353014,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2018/1030/ofr20181030_NVASA_AgeComp_gis.zip","size":"14.1 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2018-1030 GIS"},{"id":353008,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1030/coverthb.jpg"},{"id":353009,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1030/ofr20181030_pamphlet.pdf","text":"Pamphlet","size":"5.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1030 Pamphlet"},{"id":353013,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1030/ofr20181030_NVASA_AgeComp_metadata.zip","size":"14 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2018-1030 Metadata"}],"country":"United States","otherGeospatial":"Pacific Northwest Volcanic Aquifer System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123,\n 39\n ],\n [\n -113,\n 39\n ],\n [\n -113,\n 47\n ],\n [\n -123,\n 47\n ],\n [\n -123,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center
Cascades Volcano Observatory - Portland
U.S. Geological Survey
1300 SE Cardinal Court
Vancouver, WA, 98683
Recent short-term drought conditions have emphasized the need to better understand the delicate balance between abundance, sustainability, and scarcity of groundwater in the Ozark Plateaus aquifer system. In 2014, the U.S. Geological Survey began construction of a groundwater-flow model as a tool for the assessment of groundwater availability in the Ozark Plateaus aquifer system. The model was developed to benefit concurrent and future investigations involving groundwater-pumping scenarios, optimization, particle transport, and groundwater-monitoring network analysis.
The groundwater model simulates 116 years (1900–2015) of hydrologic conditions and the response of the groundwater system to changes in stress including changes in recharge and groundwater pumping for water supply. Semiseasonal stress periods were simulated from the later part of 1991 to 2015 and represent higher demand and lower recharge in the spring and summer months and lower demand and higher recharge in the fall and winter months. Groundwater pumping increases throughout the simulation period with a maximum rate of about 600 million gallons per day (Mgal/d).
The process of matching historical hydrologic data for the Ozark Plateaus aquifer system model was accomplished by a combination of manual changes to parameter values and automated calibration methods. Observation data used in the development and evaluation of the model included 19,045 hydraulic-head observations from 6,683 wells within the model area. Observation data also included stream leakage estimates summed to calculate a net gain or net loss value for approximately 81 named streams.
The majority (mean of over 95 percent) of the recharge component is discharged through streams simulated in the model. The total simulated discharge to streams fluctuates seasonally between 7,500 and 17,500 Mgal/d with a mean outflow of 11,500 Mgal/d. Much of the remaining balance between modeled recharge inflows and stream outflows is made up by water moving into or out of storage in the aquifer system resulting in changes in modeled groundwater levels.
The goal of the model was to develop a model capable of suitable accuracy at regional scales. The intent was not to reproduce individual local-scale details, which are typically not possible given the uniform cell size of 1 square mile. Although the model may not represent each local-scale detail, the model can be applied for a better understanding of the regional flow system and to evaluate responses to changes in climate and groundwater pumping.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185035","collaboration":"Water Availability and Use Science Program","usgsCitation":"Clark, B.R., Richards, J.M., and Knierim, K.J., 2018, The Ozark Plateaus Regional Aquifer Study—Documentation of a groundwater-flow model constructed to assess water availability in the Ozark Plateaus: U.S. Geological Survey Report 2018–5035, 33 p., https://doi.org/10.3133/sir20185035.","productDescription":"Report: v, 33 p.; Data Release","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079993","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":352956,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5035/coverthb2.jpg"},{"id":352962,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://water.usgs.gov/wausp/","text":"Water Availability and Use Science Program"},{"id":352957,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5035/sir20185035.pdf","text":"Report","size":"15.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5035"},{"id":352958,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F718350W","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model of groundwater flow in the Ozark Plateaus aquifer system"}],"country":"United States","otherGeospatial":" Ozark Plateaus aquifer system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.3,\n 35.0333\n ],\n [\n -89.25,\n 35.0333\n ],\n [\n -89.25,\n 39.0667\n ],\n [\n -95.3,\n 39.0667\n ],\n [\n -95.3,\n 35.0333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
700 W. Research Blvd.
Fayetteville, AR 72701
Water, bed sediment, and biota were sampled in selected streams from Butte to near Missoula, Montana, as part of a monitoring program in the upper Clark Fork Basin of western Montana. The sampling program was led by the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, to characterize aquatic resources in the Clark Fork Basin, with emphasis on trace elements associated with historic mining and smelting activities. Sampling sites were on the Clark Fork and selected tributaries. Water samples were collected periodically at 20 sites from October 2015 through September 2016. Bed-sediment and biota samples were collected once at 13 sites during August 2016.
This report presents the analytical results and quality-assurance data for water-quality, bed-sediment, and biota samples collected at sites from October 2015 through September 2016. Water-quality data include concentrations of selected major ions, trace elements, and suspended sediment. Samples for analysis of turbidity were collected at 13 sites, whereas samples for analysis of dissolved organic carbon were collected at 10 sites. In addition, samples for analysis of nitrogen (nitrate plus nitrite) were collected at two sites. Daily values of mean suspended-sediment concentration and suspended-sediment discharge were determined for three sites. Seasonal daily values of turbidity were determined for five sites. Bed-sediment data include trace-element concentrations in the fine-grained (less than 0.063 millimeter) fraction. Biological data include trace-element concentrations in whole-body tissue of aquatic benthic insects. Statistical summaries of water-quality, bed-sediment, and biological data for sites in the upper Clark Fork Basin are provided for the period of record.
","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171136","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Dodge, K.A., Hornberger, M.I., and Turner, M.A., 2018, Water-quality, bed-sediment, and biological data (October 2015 through September 2016) and statistical summaries of data for streams in the Clark Fork Basin, Montana: U.S. Geological Survey Open-File Report 2017–1136, 118 p., https://doi.org/10.3133/ofr20171136.","productDescription":"Report: vi, 118 p.; Data Release","numberOfPages":"128","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-089429","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":352885,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79C6WDM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-Quality, Bed-Sediment, and Biological Data (October 2015 through September 2016) and Statistical Summaries of Data for Streams in the Clark Fork Basin, Montana"},{"id":352884,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pubs/of/2017/1136/ofr20171136.pdf","text":"Report","size":"3.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2017–1136"},{"id":352883,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pubs/of/2017/1136/coverthb2.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Clark Fork Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114,\n 45.85\n ],\n [\n -112.41485595703125,\n 45.85\n ],\n [\n -112.41485595703125,\n 47\n ],\n [\n -114,\n 47\n ],\n [\n -114,\n 45.85\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
The practice of fire suppression across the western United States over the past century has led to dense forests, and when coupled with drought has contributed to an increase in large and destructive wildfires. Forest management efforts aimed at reducing flammable fuels through various fuel treatments can help to restore frequent fire regimes and increase forest resilience. Our research examines how different fuel treatments influenced burn severity and post-fire vegetative stand dynamics on the San Carlos Apache Reservation, in east-central Arizona, U.S.A. Our methods included the use of multitemporal remote sensing data and cloud computing to evaluate burn severity and post-fire vegetation conditions as well as statistical analyses. We investigated how forest thinning, commercial harvesting, prescribed burning, and resource benefit burning (managed wildfire) related to satellite measured burn severity (the difference Normalized Burn Ratio – dNBR) following the 2013 Creek Fire and used spectral measures of post-fire stand dynamics to track changes in land surface characteristics (i.e., brightness, greenness and wetness). We found strong negative relationships between dNBR and post-fire greenness and wetness, and a positive non-linear relationship between dNBR and brightness, with greater variability at higher severities. Fire severity and post-fire surface changes also differed by treatment type. Our results showed harvested and thinned sites that were not treated with prescribed fire had the highest severity fire. When harvesting was followed by a prescribed burn, the sites experienced lower burn severity and reduced post-fire changes in vegetation greenness and wetness. Areas that had previously experienced resource benefit burns had the lowest burn severities and the highest post-fire greenness measurements compared to all other treatments, except for where the prescribed burn had occurred. These results suggest that fire treatments may be most effective at reducing the probability of hazardous fire and increasing post-fire recovery. This research demonstrates the utility of remote sensing and spatial data to inform forest management, and how various fuel treatments can influence burn severity and post-fire vegetation response within ponderosa pine forests across the southwestern U.S.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2018.01.036","usgsCitation":"Petrakis, R., Villarreal, M.L., Wu, Z., Hetzler, R., Middleton, B.R., and Norman, L., 2018, Evaluating and monitoring forest fuel treatments using remote sensing applications in Arizona, U.S.A.: Forest Ecology and Management, v. 413, p. 48-61, https://doi.org/10.1016/j.foreco.2018.01.036.","productDescription":"14 p.","startPage":"48","endPage":"61","ipdsId":"IP-083699","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":468881,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2018.01.036","text":"Publisher Index Page"},{"id":437976,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z31WW4","text":"USGS data release","linkHelpText":"Dataset for 2013 Creek Fire Research Points, Pre- and Post-Fire Data"},{"id":352992,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.75,\n 33\n ],\n [\n -109.5,\n 33\n ],\n [\n -109.5,\n 33.8\n ],\n [\n -110.75,\n 33.8\n ],\n [\n -110.75,\n 33\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"413","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6f5e4b0da30c1bfbfaf","contributors":{"authors":[{"text":"Petrakis, Roy E. 0000-0001-8932-077X rpetrakis@usgs.gov","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":174623,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy","email":"rpetrakis@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":732009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":732010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true}],"preferred":true,"id":732014,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hetzler, Robert","contributorId":203299,"corporation":false,"usgs":false,"family":"Hetzler","given":"Robert","email":"","affiliations":[{"id":36595,"text":"BIA","active":true,"usgs":false}],"preferred":false,"id":732011,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Middleton, Barry R. 0000-0001-8924-4121 bmiddleton@usgs.gov","orcid":"https://orcid.org/0000-0001-8924-4121","contributorId":3947,"corporation":false,"usgs":true,"family":"Middleton","given":"Barry","email":"bmiddleton@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":732012,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":732013,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202375,"text":"70202375 - 2018 - A consistent global approach for the morphometric characterization of subaqueous landslides","interactions":[],"lastModifiedDate":"2019-03-01T13:25:29","indexId":"70202375","displayToPublicDate":"2018-03-28T13:25:17","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1791,"text":"Geological Society, London, Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"A consistent global approach for the morphometric characterization of subaqueous landslides","docAbstract":"Landslides are common in aquatic settings worldwide, from lakes and coastal environments to the deep sea. Fast-moving, large-volume landslides can potentially trigger destructive tsunamis. Landslides damage and disrupt global communication links and other critical marine infrastructure. Landslide deposits act as foci for localized, but important, deep-seafloor biological communities. Under burial, landslide deposits play an important role in a successful petroleum system. While the broad importance of understanding subaqueous landslide processes is evident, a number of important scientific questions have yet to receive the needed attention. Collecting quantitative data is a critical step to addressing questions surrounding subaqueous landslides.
Quantitative metrics of subaqueous landslides are routinely recorded, but which ones, and how they are defined, depends on the end-user focus. Differences in focus can inhibit communication of knowledge between communities, and complicate comparative analysis. This study outlines an approach specifically for consistent measurement of subaqueous landslide morphometrics to be used in the design of a broader, global open-source, peer-curated database. Examples from different settings illustrate how the approach can be applied, as well as the difficulties encountered when analysing different landslides and data types. Standardizing data collection for subaqueous landslides should result in more accurate geohazard predictions and resource estimation.
","language":"English","publisher":"Geological Society of London","doi":"10.1144/SP477.15","usgsCitation":"Clare, M., Chaytor, J., Dabson, O., Gamboa, D., Georgiopoulou, A., Eady, H., Hunt, J., Jackson, C., Katz, O., Krastel, S., Leon, R., Micallef, A., Moernaut, J., Moriconi, R., Moscardelli, L., Mueller, C., Normandeau, A., Patacci, M., Steventon, M., Urlaub, M., Volker, D., Wood, L., and Jobe, Z.R., 2018, A consistent global approach for the morphometric characterization of subaqueous landslides: Geological Society, London, Special Publications, v. 477, 23 p., https://doi.org/10.1144/SP477.15.","productDescription":"23 p.","ipdsId":"IP-090342","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468884,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1144/sp477.15","text":"Publisher Index Page"},{"id":361649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"477","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Clare, Michael","contributorId":213585,"corporation":false,"usgs":false,"family":"Clare","given":"Michael","email":"","affiliations":[{"id":38805,"text":"National Oceanography Centre, University of Southampton Waterfront Campus, European Way, Southampton, SO14 3ZH, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":758069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chaytor, Jason 0000-0001-8135-8677 jchaytor@usgs.gov","orcid":"https://orcid.org/0000-0001-8135-8677","contributorId":140095,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":758068,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dabson, Oliver","contributorId":213586,"corporation":false,"usgs":false,"family":"Dabson","given":"Oliver","email":"","affiliations":[{"id":38806,"text":"CH2M, Elms House, 43 Brook Green, London W6 7EF, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":758070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gamboa, Davide","contributorId":213587,"corporation":false,"usgs":false,"family":"Gamboa","given":"Davide","email":"","affiliations":[{"id":38807,"text":"British Geological Survey, Room 0.73 Cardiff University Main Building, Cardiff CF110 3AT, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":758071,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Georgiopoulou, Aggeliki","contributorId":213588,"corporation":false,"usgs":false,"family":"Georgiopoulou","given":"Aggeliki","email":"","affiliations":[{"id":38808,"text":"UCD School of Earth Sciences, University College Dublin, Dublin, Ireland","active":true,"usgs":false}],"preferred":false,"id":758072,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eady, Harry","contributorId":213589,"corporation":false,"usgs":false,"family":"Eady","given":"Harry","email":"","affiliations":[{"id":38809,"text":"Fugro GeoServices Limited, Fugro House, Hithercroft Road, Wallingford, Oxfordshire OX10 9RB","active":true,"usgs":false}],"preferred":false,"id":758073,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hunt, James","contributorId":213884,"corporation":false,"usgs":false,"family":"Hunt","given":"James","affiliations":[],"preferred":false,"id":758074,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jackson, Christopher","contributorId":213885,"corporation":false,"usgs":false,"family":"Jackson","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":758075,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Katz, Oded","contributorId":213590,"corporation":false,"usgs":false,"family":"Katz","given":"Oded","email":"","affiliations":[{"id":38810,"text":"Geological Survey of Israel, Jerusalem, Israel","active":true,"usgs":false}],"preferred":false,"id":758076,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Krastel, Sebastian","contributorId":175295,"corporation":false,"usgs":false,"family":"Krastel","given":"Sebastian","email":"","affiliations":[],"preferred":false,"id":758077,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Leon, Ricardo","contributorId":213591,"corporation":false,"usgs":false,"family":"Leon","given":"Ricardo","email":"","affiliations":[{"id":38811,"text":"IGME, Geological Survey of Spain, 28003 Madrid, Spain","active":true,"usgs":false}],"preferred":false,"id":758078,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Micallef, Aaron","contributorId":175297,"corporation":false,"usgs":false,"family":"Micallef","given":"Aaron","email":"","affiliations":[],"preferred":false,"id":758079,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Moernaut, Jasper","contributorId":194084,"corporation":false,"usgs":false,"family":"Moernaut","given":"Jasper","email":"","affiliations":[],"preferred":false,"id":758080,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Moriconi, Roberto","contributorId":213592,"corporation":false,"usgs":false,"family":"Moriconi","given":"Roberto","email":"","affiliations":[{"id":38812,"text":"Formerly Fugro Oceansismica S.P.A., 268 Viale Lenormant Charles, Roma, RM 00126, Italy","active":true,"usgs":false}],"preferred":false,"id":758081,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Moscardelli, Lorena","contributorId":147083,"corporation":false,"usgs":false,"family":"Moscardelli","given":"Lorena","email":"","affiliations":[],"preferred":false,"id":758082,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Mueller, Christof","contributorId":175298,"corporation":false,"usgs":false,"family":"Mueller","given":"Christof","email":"","affiliations":[{"id":36364,"text":"Institute of Geological and Nuclear Sciences (GNS), Lower Hutt, New Zealand","active":true,"usgs":false}],"preferred":false,"id":758083,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Normandeau, Alexandre","contributorId":213593,"corporation":false,"usgs":false,"family":"Normandeau","given":"Alexandre","email":"","affiliations":[{"id":38813,"text":"Geological Survey of Canada - Atlantic, Bedford Institute of Oceanography, Dartmouth, Canada","active":true,"usgs":false}],"preferred":false,"id":758084,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Patacci, Marco","contributorId":213594,"corporation":false,"usgs":false,"family":"Patacci","given":"Marco","email":"","affiliations":[{"id":38814,"text":"Institute of Applied Geoscience, School of Earth and Environment, University of Leeds, Leeds LS2 9JT","active":true,"usgs":false}],"preferred":false,"id":758085,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Steventon, Michael","contributorId":213595,"corporation":false,"usgs":false,"family":"Steventon","given":"Michael","email":"","affiliations":[{"id":38815,"text":"Basins Research Group (BRG), Department of Earth Science & Engineering, Imperial College, Prince Consort Road, London, SW72BP, UK","active":true,"usgs":false}],"preferred":false,"id":758086,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Urlaub, Morelia","contributorId":213596,"corporation":false,"usgs":false,"family":"Urlaub","given":"Morelia","email":"","affiliations":[{"id":38816,"text":"GEOMAR Helmholtz Centre for Ocean Research Kiel, 24148 Kiel, Germany","active":true,"usgs":false}],"preferred":false,"id":758087,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Volker, David","contributorId":213597,"corporation":false,"usgs":false,"family":"Volker","given":"David","email":"","affiliations":[{"id":38817,"text":"David Völker, Marum - Zentrum für Marine Umweltwissenschaften, der Universität Bremen, Postfach 330 440, 28334, Bremen","active":true,"usgs":false}],"preferred":false,"id":758088,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Wood, Lesli","contributorId":213886,"corporation":false,"usgs":false,"family":"Wood","given":"Lesli","email":"","affiliations":[],"preferred":false,"id":758089,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Jobe, Zane R.","contributorId":207547,"corporation":false,"usgs":false,"family":"Jobe","given":"Zane","email":"","middleInitial":"R.","affiliations":[{"id":37560,"text":"Department of Geology and Geological Engineering, Colorado School of Mines, Golden, Colorado 80401, USA","active":true,"usgs":false}],"preferred":false,"id":758090,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70216337,"text":"70216337 - 2018 - Hierarchical modeling assessment of the influence of watershed stressors on fish and invertebrate species in Gulf of Mexico estuaries","interactions":[],"lastModifiedDate":"2020-11-12T15:39:40.108738","indexId":"70216337","displayToPublicDate":"2018-03-28T09:35:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical modeling assessment of the influence of watershed stressors on fish and invertebrate species in Gulf of Mexico estuaries","docAbstract":"The northern Gulf of Mexico (GoM) spans five U.S. states and encompasses estuaries that vary greatly in size, shape, upstream river input, eutrophication status, and biotic communities. Given the variability among these estuaries, assessing their biological condition relative to anthropogenic stressors is challenging, but important to regional fisheries management and habitat conservation initiatives. Here, a hierarchical generalized linear modeling approach was developed to predict species presence in bottom trawl samples, using data from 33 estuaries over a nineteen-year study period. This is the first GoM estuary assessment to leverage Gulf-wide trawl data to develop species-level indicators and a quantitative index of estuary disturbance. After controlling for sources of variability at the sampling event, estuary, state, and sampling program levels, our approach screened for statistically significant relationships between watershed-level anthropogenic stressors and fish and invertebrate species presence. Modeling results indicate species level indicators with sensitivities to landscape stressor gradients. The most influential stressors include total anthropogenic land use, crop land use, and the number of toxic release sites in upstream watersheds, as well as agriculture in the shoreline buffer, each of which was significantly related to between 21% and 39% of the 57 species studied. Averaging the effects of these influential stressors across species, we develop a quantitative estuary stress index that can be compared against benchmark conditions. In general, disturbance levels were greatest in estuaries west of the Mississippi delta and in highly developed estuaries in southwest Florida. Estuaries from the Florida panhandle to the eastern Mississippi delta had less anthropogenic stress.
Habitat models using lidar-derived variables that quantify fine-scale variation in vegetation structure can improve the accuracy of occupancy estimates for canopy-dwelling species over models that use variables derived from other remote sensing techniques. However, the ability of models developed at such a fine spatial scale to maintain accuracy at regional or larger spatial scales has not been tested. We tested the transferability of a lidar-based habitat model for the threatened Marbled Murrelet (Brachyramphus marmoratus) between two management districts within a larger regional conservation zone in coastal western Oregon. We compared the performance of the transferred model against models developed with data from the application location. The transferred model had good discrimination (AUC = 0.73) at the application location, and model performance was further improved by fitting the original model with coefficients from the application location dataset (AUC = 0.79). However, the model selection procedure indicated that neither of these transferred models were considered competitive with a model trained on local data. The new model trained on data from the application location resulted in the selection of a slightly different set of lidar metrics from the original model, but both transferred and locally trained models consistently indicated positive relationships between the probability of occupancy and lidar measures of canopy structural complexity. We conclude that while the locally trained model had superior performance for local application, the transferred model could reasonably be applied to the entire conservation zone.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181035","usgsCitation":"Hagar, J.C., Perez, R.A., Haggerty, P., and Hollenbeck, J.P., 2018, Modeling habitat for Marbled Murrelets on the Siuslaw National Forest, Oregon, using lidar data: U.S. Geological Survey Open-File Report 2018–1035, 21 p., https://doi.org/10.3133/ofr20181035.","productDescription":"iv, 21 p.","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-088393","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":352857,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1035/ofr20181035.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1035"},{"id":352856,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1035/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Siuslaw National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.68383789062499,\n 41.9921602333763\n ],\n [\n -123.28857421875,\n 41.9921602333763\n ],\n [\n -123.28857421875,\n 45.62172169252446\n ],\n [\n -124.68383789062499,\n 45.62172169252446\n ],\n [\n -124.68383789062499,\n 41.9921602333763\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
Few studies exist on the long-term geomorphic effects of floods. However, the U.S. Geological Survey (USGS) was able to begin such a study after a 50-year recurrence interval flood in 1978 because 20 channel cross sections along a 100-kilometer reach of river were established in 1975 and 1977 as part of a study for a proposed dam on Powder River in southeastern Montana. These cross-section measurements (data for each channel cross section are available at the USGS ScienceBase website) have been repeated about 30 times during four decades (1975–2016) and provide a unique dataset for understanding long-term changes in channel morphology caused by an extreme flood and a spectrum of annual floods.
Changes in channel morphology of a 100-kilometer reach of Powder River are documented in a series of narratives for each channel cross section that include a time series of photographs as a record of these changes. The primary change during the first decade (1975–85) was the rapid vertical growth of a new inset flood plain within the flood-widened channel. Changes during the second decade (1985–95) were characterized by slower growth of the flood plain, and the effects of ice-jam floods typical of a northward-flowing river. Changes during the third decade (1995–2005) showed little vertical growth of the inset flood plain, which had reached a height that limited overbank deposition. And changes during the final decade (2005–16) covered in this report showed that, because the new inset flood plain had reached a limiting height, the effects of the large annual flood of 2008 (largest flood since 1978) were relatively small compared to smaller floods in previous decades. Throughout these four decades, the riparian vegetation, which interacts with the river, has undergone a gradual but substantial change that may have lasting effects on the channel morphology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181012","usgsCitation":"Moody, J.A., and Meade, R.H., 2018, Decadal changes in channel morphology of a freely meandering river—Powder River, Montana, 1975–2016: U.S. Geological Survey Open-File Report 2018–1012, 143 p., https://doi.org/10.3133/ofr20181012.","productDescription":"Report: viii, 143 p.; Data Release","numberOfPages":"152","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-090628","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":352547,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TQ5ZRN","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Channel Cross-section Data for Powder River between Moorhead and Broadus, Montana from 1975 to 2016"},{"id":352545,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1012/coverthb2.jpg"},{"id":352546,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1012/ofr20181012.pdf","text":"Report","size":"35.6 MB"}],"country":"United States","state":"Montana","otherGeospatial":"Powder River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.25,\n 45\n ],\n [\n -106,\n 45\n ],\n [\n -106,\n 45.5\n ],\n [\n -105.25,\n 45.5\n ],\n [\n -105.25,\n 45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"The U.S. Geological Survey (USGS) in cooperation with the city of West Branch and the Herbert Hoover National Historic Site of the National Park Service assessed flood-mitigation scenarios within the West Branch Wapsinonoc Creek watershed. The scenarios are intended to demonstrate several means of decreasing peak streamflows and improving the conveyance of overbank flows from the West Branch Wapsinonoc Creek and its tributary Hoover Creek where they flow through the city and the Herbert Hoover National Historic Site located within the city.
Hydrologic and hydraulic models of the watershed were constructed to assess the flood-mitigation scenarios. To accomplish this, the models used the U.S. Army Corps of Engineers Hydrologic Engineering Center-Hydrologic Modeling System (HEC–HMS) version 4.2 to simulate the amount of runoff and streamflow produced from single rain events. The Hydrologic Engineering Center-River Analysis System (HEC–RAS) version 5.0 was then used to construct an unsteady-state model that may be used for routing streamflows, mapping areas that may be inundated during floods, and simulating the effects of different measures taken to decrease the effects of floods on people and infrastructure.
Both models were calibrated to three historic rainfall events that produced peak streamflows ranging between the 2-year and 10-year flood-frequency recurrence intervals at the USGS streamgage (05464942) on Hoover Creek. The historic rainfall events were calibrated by using data from two USGS streamgages along with surveyed high-water marks from one of the events. The calibrated HEC–HMS model was then used to simulate streamflows from design rainfall events of 24-hour duration ranging from a 20-percent to a 1-percent annual exceedance probability. These simulated streamflows were incorporated into the HEC–RAS model.
The unsteady-state HEC–RAS model was calibrated to represent existing conditions within the watershed. HEC–RAS model simulations with the existing conditions and streamflows from the design rainfall events were then done to serve as a baseline for evaluating flood-mitigation scenarios. After these simulations were completed, three different flood-mitigation scenarios were developed with HEC–RAS: a detention-storage scenario, a conveyance improvement scenario, and a combination of both. In the detention-storage scenario, four in-channel detention structures were placed upstream from the city of West Branch to attenuate peak streamflows. To investigate possible improvements to conveying floodwaters through the city of West Branch, a section of abandoned railroad embankment and an old truss bridge were removed in the model, because these structures were producing backwater areas during flooding events. The third scenario combines the detention and conveyance scenarios so their joint efficiency could be evaluated. The scenarios with the design rainfall events were run in the HEC–RAS model so their flood-mitigation effects could be analyzed across a wide range of flood magnitudes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185002","collaboration":"Prepared in cooperation with the city of West Branch and the National Park Service","usgsCitation":"Cigrand, C.V., 2018, Flood-inundation and flood-mitigation modeling of the West Branch Wapsinonoc Creek Watershed in West Branch, Iowa: U.S. Geological Survey Scientific Investigations Report 2018–5002, 36 p., https://doi.org/10.3133/sir20185002.","productDescription":"viii, 36 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-090129","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":352733,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5002/sir20185002.pdf","text":"Report","size":"3.24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5002"},{"id":352732,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5002/coverthb.jpg"}],"country":"United States","state":"Iowa","city":"West Branch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.40693664550781,\n 41.64264409952472\n ],\n [\n -91.32488250732422,\n 41.64264409952472\n ],\n [\n -91.32488250732422,\n 41.72289932945416\n ],\n [\n -91.40693664550781,\n 41.72289932945416\n ],\n [\n -91.40693664550781,\n 41.64264409952472\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 S. Clinton Street
Iowa City, IA 52240
This map product contains a map sheet at 1:1,506,000 scale that shows the geology of the Nepenthes Planum region of Mars, which is located between the cratered highlands that dominate the southern hemisphere and the less-cratered sedimentary plains that dominate the northern hemisphere. The map region contains cone- and mound-shaped landforms as well as lobate materials that are morphologically similar to terrestrial igneous or mud vents and flows. This map is part of an informal series of small-scale (large-area) maps aimed at refining current understanding of the geologic units and structures that make up the highland-to-lowland transition zone. The map base consists of a controlled Thermal Emission Imaging System (THEMIS) daytime infrared image mosaic (100 meters per pixel resolution) supplemented by a Mars Orbiter Laser Altimeter (MOLA) digital elevation model (463 meters per pixel resolution). The map includes a Description of Map Units and a Correlation of Map Units that describes and correlates units identified across the entire map region. The geologic map was assembled using ArcGIS software by Environmental Systems Research Institute (http://www.esri.com). The ArcGIS project, geodatabase, base map, and all map components are included online as supplemental data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3389","usgsCitation":"Skinner, J.A., Jr., and Tanaka, K.L., 2018, Geologic map of the Nepenthes Planum Region, Mars: U.S. Geological Survey Scientific Investigations Map 3389, pamphlet 11 p., scale 1:1,506,000, https://doi.org/10.3133/sim3389.","productDescription":"Map: 45.60 x 38.82 inches; Pamphlet: i, 11 p.; Metadata, Spatial Data; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-078987","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":437979,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95837GN","text":"USGS data release","linkHelpText":"Interactive Map: USGS SIM 3389 Geologic Map of the Nepenthes Planum Region, Mars"},{"id":352459,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3389/coverthb.jpg"},{"id":352467,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_gis.zip","text":"GIS Files","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3389"},{"id":352463,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_readme.txt","text":"Read Me","size":"4 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3389"},{"id":352462,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_pamphlet.pdf","text":"Pamphlet","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3389"},{"id":352461,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_mapsheet.pdf","text":"Map","size":"74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3389"},{"id":352460,"rank":2,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3389/sim3389_geomap_metadata.xml","size":"7 KB","description":"SIM 3389 Metadata"},{"id":400823,"rank":7,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://doi.org/10.5066/P95837GN","text":"Interactive map","linkHelpText":"- Geologic map of the Nepenthes Planum Region, Mars, 1:1,506,000, Skinner et al. (2018)"}],"contact":"Astrogeology Research Program staff
Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
The accurate prediction of extreme wave run-up is important for effective coastal engineering design and coastal hazard management. While run-up processes on open sandy coasts have been reasonably well-studied, very few studies have focused on understanding and predicting wave run-up at coral reef-fronted coastlines. This paper applies the short-wave resolving, Nonhydrostatic (XB-NH) and short-wave averaged, Surfbeat (XB-SB) modes of the XBeach numerical model to validate run-up using data from two 1D (alongshore uniform) fringing-reef profiles without roughness elements, with two objectives: i) to provide insight into the physical processes governing run-up in such environments; and ii) to evaluate the performance of both modes in accurately predicting run-up over a wide range of conditions. XBeach was calibrated by optimizing the maximum wave steepness parameter (maxbrsteep) in XB-NH and the dissipation coefficient (alpha) in XB-SB) using the first dataset; and then applied to the second dataset for validation. XB-NH and XB-SB predictions of extreme wave run-up (Rmax and R2%) and its components, infragravity- and sea-swell band swash (SIG and SSS) and shoreline setup (<η>), were compared to observations. XB-NH more accurately simulated wave transformation but under-predicted shoreline setup due to its exclusion of parameterized wave-roller dynamics. XB-SB under-predicted sea-swell band swash but overestimated shoreline setup due to an over-prediction of wave heights on the reef flat. Run-up (swash) spectra were dominated by infragravity motions, allowing the short-wave (but not wave group) averaged model (XB-SB) to perform comparably well to its more complete, short-wave resolving (XB-NH) counterpart. Despite their respective limitations, both modes were able to accurately predict Rmax and R2%.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2018.03.007","usgsCitation":"Lashley, C.H., Roelvink, D., van Dongeren, A.R., Buckley, M.L., and Lowe, R.J., 2018, Nonhydrostatic and surfbeat model predictions of extreme wave run-up in fringing reef environments: Coastal Engineering, v. 137, p. 11-27, https://doi.org/10.1016/j.coastaleng.2018.03.007.","productDescription":"17 p.","startPage":"11","endPage":"27","ipdsId":"IP-092741","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468894,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2018.03.007","text":"Publisher Index Page"},{"id":352760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"137","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6f8e4b0da30c1bfbfe2","contributors":{"authors":[{"text":"Lashley, Christopher H.","contributorId":203483,"corporation":false,"usgs":false,"family":"Lashley","given":"Christopher","email":"","middleInitial":"H.","affiliations":[{"id":36631,"text":"IHE-Delft Institute for Water Education","active":true,"usgs":false}],"preferred":false,"id":731601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roelvink, Dano","contributorId":139950,"corporation":false,"usgs":false,"family":"Roelvink","given":"Dano","email":"","affiliations":[{"id":13328,"text":"UNESCO-IHE","active":true,"usgs":false}],"preferred":false,"id":731602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Dongeren, Ap R.","contributorId":203482,"corporation":false,"usgs":false,"family":"van Dongeren","given":"Ap","email":"","middleInitial":"R.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":731600,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":731599,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":731603,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196198,"text":"70196198 - 2018 - Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands","interactions":[],"lastModifiedDate":"2018-03-26T10:12:45","indexId":"70196198","displayToPublicDate":"2018-03-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands","docAbstract":"Water-limited ecosystems often recover slowly following anthropogenic or natural disturbance. Multitemporal remote sensing can be used to monitor ecosystem recovery after disturbance; however, dryland vegetation cover can be challenging to accurately measure due to sparse cover and spectral confusion between soils and non-photosynthetic vegetation. With the goal of optimizing a monitoring approach for identifying both abrupt and gradual vegetation changes, we evaluated the ability of Landsat-derived spectral variables to characterize surface variability of vegetation cover and bare ground across a range of vegetation community types. Using three year composites of Landsat data, we modeled relationships between spectral information and field data collected at monitoring sites near Canyonlands National Park, UT. We also developed multiple regression models to assess improvement over single variables. We found that for all vegetation types, percent cover bare ground could be accurately modeled with single indices that included a combination of red and shortwave infrared bands, while near infrared-based vegetation indices like NDVI worked best for quantifying tree cover and total live vegetation cover in woodlands. We applied four models to characterize the spatial distribution of putative grassland ecological states across our study area, illustrating how this approach can be implemented to guide dryland ecosystem management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2017.12.008","usgsCitation":"Poitras, T.B., Villarreal, M.L., Waller, E.K., Nauman, T.W., Miller, M.E., and Duniway, M.C., 2018, Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands: Journal of Arid Environments, v. 153, p. 76-87, https://doi.org/10.1016/j.jaridenv.2017.12.008.","productDescription":"12 p.","startPage":"76","endPage":"87","ipdsId":"IP-084812","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":468897,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jaridenv.2017.12.008","text":"Publisher Index Page"},{"id":437977,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SWDWLS","text":"USGS data release","linkHelpText":"Grassland State and Transition Map of Canyonlands National Park Needles District and Indian Creek Grazing Allotment"},{"id":352759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.20797729492188,\n 37.81737834565083\n ],\n [\n -109.58862304687499,\n 37.81737834565083\n ],\n [\n -109.58862304687499,\n 38.494443887725055\n ],\n [\n -110.20797729492188,\n 38.494443887725055\n ],\n [\n -110.20797729492188,\n 37.81737834565083\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"153","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6f7e4b0da30c1bfbfe0","contributors":{"authors":[{"text":"Poitras, Travis B. 0000-0001-8677-1743 tpoitras@usgs.gov","orcid":"https://orcid.org/0000-0001-8677-1743","contributorId":195168,"corporation":false,"usgs":true,"family":"Poitras","given":"Travis","email":"tpoitras@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":731644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":731643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waller, Eric K. 0000-0002-9169-9210","orcid":"https://orcid.org/0000-0002-9169-9210","contributorId":203496,"corporation":false,"usgs":true,"family":"Waller","given":"Eric","email":"","middleInitial":"K.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"preferred":true,"id":731645,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":731646,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Mark E.","contributorId":91580,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":731648,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":731647,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196200,"text":"70196200 - 2018 - Archie’s saturation exponent for natural gas hydrate in coarse-grained reservoirs","interactions":[],"lastModifiedDate":"2018-04-27T16:37:31","indexId":"70196200","displayToPublicDate":"2018-03-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Archie’s saturation exponent for natural gas hydrate in coarse-grained reservoirs","docAbstract":"Accurately quantifying the amount of naturally occurring gas hydrate in marine and permafrost environments is important for assessing its resource potential and understanding the role of gas hydrate in the global carbon cycle. Electrical resistivity well logs are often used to calculate gas hydrate saturations, Sh, using Archie's equation. Archie's equation, in turn, relies on an empirical saturation parameter, n. Though n = 1.9 has been measured for ice‐bearing sands and is widely used within the hydrate community, it is highly questionable if this n value is appropriate for hydrate‐bearing sands. In this work, we calibrate n for hydrate‐bearing sands from the Canadian permafrost gas hydrate research well, Mallik 5L‐38, by establishing an independent downhole Sh profile based on compressional‐wave velocity log data. Using the independently determined Sh profile and colocated electrical resistivity and bulk density logs, Archie's saturation equation is solved for n, and uncertainty is tracked throughout the iterative process. In addition to the Mallik 5L‐38 well, we also apply this method to two marine, coarse‐grained reservoirs from the northern Gulf of Mexico Gas Hydrate Joint Industry Project: Walker Ridge 313‐H and Green Canyon 955‐H. All locations yield similar results, each suggesting n ≈ 2.5 ± 0.5. Thus, for the coarse‐grained hydrate bearing (Sh > 0.4) of greatest interest as potential energy resources, we suggest that n = 2.5 ± 0.5 should be applied in Archie's equation for either marine or permafrost gas hydrate settings if independent estimates of n are not available.
","language":"English","publisher":"AGU","doi":"10.1002/2017JB015138","usgsCitation":"Cook, A.E., and Waite, W., 2018, Archie’s saturation exponent for natural gas hydrate in coarse-grained reservoirs: Journal of Geophysical Research B: Solid Earth, v. 123, no. 3, p. 2069-2089, https://doi.org/10.1002/2017JB015138.","productDescription":"21 p.","startPage":"2069","endPage":"2089","ipdsId":"IP-078323","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468893,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jb015138","text":"Publisher Index Page"},{"id":352757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"3","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-11","publicationStatus":"PW","scienceBaseUri":"5afee6f7e4b0da30c1bfbfdc","contributors":{"authors":[{"text":"Cook, Ann E.","contributorId":18218,"corporation":false,"usgs":true,"family":"Cook","given":"Ann","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":731654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waite, William F. 0000-0002-9436-4109 wwaite@usgs.gov","orcid":"https://orcid.org/0000-0002-9436-4109","contributorId":625,"corporation":false,"usgs":true,"family":"Waite","given":"William F.","email":"wwaite@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":731653,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70196199,"text":"70196199 - 2018 - Inferring species interactions through joint mark–recapture analysis","interactions":[],"lastModifiedDate":"2018-04-02T13:38:50","indexId":"70196199","displayToPublicDate":"2018-03-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Inferring species interactions through joint mark–recapture analysis","docAbstract":"Introduced species are frequently implicated in declines of native species. In many cases, however, evidence linking introduced species to native declines is weak. Failure to make strong inferences regarding the role of introduced species can hamper attempts to predict population viability and delay effective management responses. For many species, mark–recapture analysis is the more rigorous form of demographic analysis. However, to our knowledge, there are no mark–recapture models that allow for joint modeling of interacting species. Here, we introduce a two‐species mark–recapture population model in which the vital rates (and capture probabilities) of one species are allowed to vary in response to the abundance of the other species. We use a simulation study to explore bias and choose an approach to model selection. We then use the model to investigate species interactions between endangered humpback chub (Gila cypha) and introduced rainbow trout (Oncorhynchus mykiss) in the Colorado River between 2009 and 2016. In particular, we test hypotheses about how two environmental factors (turbidity and temperature), intraspecific density dependence, and rainbow trout abundance are related to survival, growth, and capture of juvenile humpback chub. We also project the long‐term effects of different rainbow trout abundances on adult humpback chub abundances. Our simulation study suggests this approach has minimal bias under potentially challenging circumstances (i.e., low capture probabilities) that characterized our application and that model selection using indicator variables could reliably identify the true generating model even when process error was high. When the model was applied to rainbow trout and humpback chub, we identified negative relationships between rainbow trout abundance and the survival, growth, and capture probability of juvenile humpback chub. Effects on interspecific interactions on survival and capture probability were strongly supported, whereas support for the growth effect was weaker. Environmental factors were also identified to be important and in many cases stronger than interspecific interactions, and there was still substantial unexplained variation in growth and survival rates. The general approach presented here for combining mark–recapture data for two species is applicable in many other systems and could be modified to model abundance of the invader via other modeling approaches.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2166","usgsCitation":"Yackulic, C.B., Korman, J., Yard, M., and Dzul, M.C., 2018, Inferring species interactions through joint mark–recapture analysis: Ecology, v. 99, no. 4, p. 812-821, https://doi.org/10.1002/ecy.2166.","productDescription":"10 p.","startPage":"812","endPage":"821","ipdsId":"IP-086832","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":437980,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZC81T9","text":"USGS data release","linkHelpText":"Humpback Chub (Gila cypha) and Rainbow Trout Joint Mark-Recapture Data and Model, Colorado River, Arizona"},{"id":352758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-21","publicationStatus":"PW","scienceBaseUri":"5afee6f7e4b0da30c1bfbfde","contributors":{"authors":[{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":731649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Korman, Josh","contributorId":139960,"corporation":false,"usgs":false,"family":"Korman","given":"Josh","email":"","affiliations":[{"id":13333,"text":"Ecometric Research Inc.","active":true,"usgs":false}],"preferred":false,"id":731652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yard, Michael D. 0000-0002-6580-6027 myard@usgs.gov","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":2889,"corporation":false,"usgs":true,"family":"Yard","given":"Michael D.","email":"myard@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":731651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dzul, Maria C. 0000-0002-4798-5930 mdzul@usgs.gov","orcid":"https://orcid.org/0000-0002-4798-5930","contributorId":5469,"corporation":false,"usgs":true,"family":"Dzul","given":"Maria","email":"mdzul@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":731650,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210225,"text":"70210225 - 2018 - Long-term population dynamics and conservation risk of migratory bull trout in the upper Columbia River basin","interactions":[],"lastModifiedDate":"2020-05-21T14:39:43.455562","indexId":"70210225","displayToPublicDate":"2018-03-24T09:35:52","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Long-term population dynamics and conservation risk of migratory bull trout in the upper Columbia River basin","docAbstract":"We used redd count data from 88 bull trout (Salvelinus confluentus) populations in the upper Columbia River basin to quantify local and regional patterns in population dynamics, including adult abundance, long-term trend, and population synchrony. We further used this information to assess conservation risk of metapopulations using eight population dynamic metrics associated with persistence. Local population abundances were generally low (<20 redds annually) and the majority of trends were either stable (85%) or declining (13%). Evidence of synchrony among populations was apparent but not related to fluvial distance between streams. Variability in annual abundances was 1.4–2.5 times lower in metapopulations than local populations, indicating moderate portfolio effects across the regional stock complex. Importantly, most metrics of conservation risk were uncorrelated with one another, emphasizing that multiple statistics describing population dynamics at various scales are needed for monitoring and assessing recovery. We provide a composite description of conservation risk based on local and regional population dynamics that can help inform conservation management decisions for bull trout and other freshwater fishes.","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2017-0466","usgsCitation":"Kovach, R., Armstrong, J., David Schmetterling, Al-Chokhachy, R., and Muhlfeld, C.C., 2018, Long-term population dynamics and conservation risk of migratory bull trout in the upper Columbia River basin: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 11, p. 1960-1968, https://doi.org/10.1139/cjfas-2017-0466.","productDescription":"9 p.","startPage":"1960","endPage":"1968","ipdsId":"IP-091943","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":374989,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana","otherGeospatial":"Upper Columbia River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.24609374999999,\n 44.84029065139799\n ],\n [\n -110.61035156249999,\n 44.84029065139799\n ],\n [\n -110.61035156249999,\n 48.8936153614802\n ],\n [\n -117.24609374999999,\n 48.8936153614802\n ],\n [\n -117.24609374999999,\n 44.84029065139799\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kovach, Ryan 0000-0001-5402-2123 rkovach@usgs.gov","orcid":"https://orcid.org/0000-0001-5402-2123","contributorId":145914,"corporation":false,"usgs":true,"family":"Kovach","given":"Ryan","email":"rkovach@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":789641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Armstrong, Jonathan","contributorId":224821,"corporation":false,"usgs":false,"family":"Armstrong","given":"Jonathan","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":789642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"David Schmetterling","contributorId":224822,"corporation":false,"usgs":false,"family":"David Schmetterling","affiliations":[{"id":40948,"text":"Montana Fish Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":789643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Al-Chokhachy, Robert 0000-0002-2136-5098","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":216703,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":789644,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":789645,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196186,"text":"70196186 - 2018 - The role of frozen soil in groundwater discharge predictions for warming alpine watersheds","interactions":[],"lastModifiedDate":"2018-04-27T16:38:29","indexId":"70196186","displayToPublicDate":"2018-03-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"The role of frozen soil in groundwater discharge predictions for warming alpine watersheds","docAbstract":"Climate warming may alter the quantity and timing of groundwater discharge to streams in high alpine watersheds due to changes in the timing of the duration of seasonal freezing in the subsurface and snowmelt recharge. It is imperative to understand the effects of seasonal freezing and recharge on groundwater discharge to streams in warming alpine watersheds as streamflow originating from these watersheds is a critical water resource for downstream users. This study evaluates how climate warming may alter groundwater discharge due to changes in seasonally frozen ground and snowmelt using a 2‐D coupled flow and heat transport model with freeze and thaw capabilities for variably saturated media. The model is applied to a representative snowmelt‐dominated watershed in the Rocky Mountains of central Colorado, USA, with snowmelt time series reconstructed from a 12 year data set of hydrometeorological records and satellite‐derived snow covered area. Model analyses indicate that the duration of seasonal freezing in the subsurface controls groundwater discharge to streams, while snowmelt timing controls groundwater discharge to hillslope faces. Climate warming causes changes to subsurface ice content and duration, rerouting groundwater flow paths but not altering the total magnitude of future groundwater discharge outside of the bounds of hydrologic parameter uncertainties. These findings suggest that frozen soil routines play an important role for predicting the future location of groundwater discharge in watersheds underlain by seasonally frozen ground.
","language":"English","publisher":"AGU","doi":"10.1002/2017WR022098","usgsCitation":"Evans, S.G., Ge, S., Voss, C.I., and Molotch, N.P., 2018, The role of frozen soil in groundwater discharge predictions for warming alpine watersheds: Water Resources Research, v. 54, no. 3, p. 1599-1615, https://doi.org/10.1002/2017WR022098.","productDescription":"17 p.","startPage":"1599","endPage":"1615","ipdsId":"IP-093839","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":468898,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr022098","text":"Publisher Index Page"},{"id":352744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.64702033996582,\n 40.03182061333687\n ],\n [\n -105.57663917541504,\n 40.03182061333687\n ],\n [\n -105.57663917541504,\n 40.05902304741144\n ],\n [\n -105.64702033996582,\n 40.05902304741144\n ],\n [\n -105.64702033996582,\n 40.03182061333687\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-07","publicationStatus":"PW","scienceBaseUri":"5afee6f8e4b0da30c1bfbff2","contributors":{"authors":[{"text":"Evans, Sarah G.","contributorId":203464,"corporation":false,"usgs":false,"family":"Evans","given":"Sarah","email":"","middleInitial":"G.","affiliations":[{"id":36626,"text":"Appalachian State University","active":true,"usgs":false}],"preferred":false,"id":731568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ge, Shemin","contributorId":203465,"corporation":false,"usgs":false,"family":"Ge","given":"Shemin","email":"","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":731569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":731567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Molotch, Noah P. 0000-0003-4733-8060","orcid":"https://orcid.org/0000-0003-4733-8060","contributorId":203466,"corporation":false,"usgs":false,"family":"Molotch","given":"Noah","email":"","middleInitial":"P.","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":731570,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196012,"text":"ofr20171165 - 2018 - The sedimentological characteristics and geochronology of the marshes of Dauphin Island, Alabama","interactions":[],"lastModifiedDate":"2025-05-13T16:24:00.938754","indexId":"ofr20171165","displayToPublicDate":"2018-03-22T13:45:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1165","title":"The sedimentological characteristics and geochronology of the marshes of Dauphin Island, Alabama","docAbstract":"In August 2015, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center collected 11 push cores from the marshes of Dauphin Island and Little Dauphin Island, Alabama. Sample site environments included high marshes, low salt marshes, and salt flats, and varied in distance from the shoreline. The sampling efforts were part of a larger study to assess the feasibility and sustainability of proposed restoration efforts for Dauphin Island, Alabama, and to identify trends in shoreline erosion and accretion. The data presented in this publication can provide a basis for assessing organic and inorganic sediment accumulation rates and temporal changes in accumulation rates over multiple decades at multiple locations across the island. This study was funded by the National Fish and Wildlife Foundation, via the Gulf Environmental Benefit Fund. This report serves as an archive for the sedimentological and geochemical data derived from the marsh cores. Downloadable data are available and include Microsoft Excel spreadsheets (.xlsx), comma-separated values (.csv) text files, JPEG files, and formal Federal Geographic Data Committee metadata in a U.S. Geological Survey data release.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171165","usgsCitation":"Ellis, A.M., Smith, C.G., and Marot, M.E., 2018, The sedimentological characteristics and geochronology of the marshes of Dauphin Island, Alabama: U.S. Geological Survey Open-File Report 2017–1165, https://doi.org/10.3133/ofr20171165.","productDescription":"HTML Document; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085345","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":352515,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1165/index.html","text":"Report HTML"},{"id":352514,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1165/coverthb.jpg"},{"id":352516,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VM49J0","text":"USGS data release","description":"USGS data release","linkHelpText":"The Sedimentological Characteristics and Geochronology of the Marshes of Dauphin Island, Alabama"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.20854187011719,\n 30.221101852485987\n ],\n [\n -88.06709289550781,\n 30.221101852485987\n ],\n [\n -88.06709289550781,\n 30.282491622409413\n ],\n [\n -88.20854187011719,\n 30.282491622409413\n ],\n [\n -88.20854187011719,\n 30.221101852485987\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
This report describes a new methodology for using sparse (weekly or less frequent observations) and potentially highly censored pesticide monitoring data to simulate daily pesticide concentrations and associated quantities used for acute and chronic exposure assessments, such as the annual maximum daily concentration. The new methodology is based on a statistical model that expresses log-transformed daily pesticide concentration in terms of a seasonal wave, flow-related variability, long-term trend, and serially correlated errors. Methods are described for estimating the model parameters, generating conditional simulations of daily pesticide concentration given sparse (weekly or less frequent) and potentially highly censored observations, and estimating concentration extremes based on the conditional simulations. The model can be applied to datasets with as few as 3 years of record, as few as 30 total observations, and as few as 10 uncensored observations. The model was applied to atrazine, carbaryl, chlorpyrifos, and fipronil data for U.S. Geological Survey pesticide sampling sites with sufficient data for applying the model. A total of 112 sites were analyzed for atrazine, 38 for carbaryl, 34 for chlorpyrifos, and 33 for fipronil. The results are summarized in this report; and, R functions, described in this report and provided in an accompanying model archive, can be used to fit the model parameters and generate conditional simulations of daily concentrations for use in investigations involving pesticide exposure risk and uncertainty.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175159","collaboration":"National Water Quality Program","usgsCitation":"Vecchia, A.V., 2018, Model methodology for estimating pesticide concentration extremes based on sparse monitoring data: U.S. Geological Survey Scientific Investigations Report 2017–5159, 47 p., https://doi.org/10.3133/sir20175159.","productDescription":"Report: viii, 47 p.; Appendix; Data release","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-090885","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":352536,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NV9H50","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data Files to Support SEAWAVE-QEX Model for Simulating Concentrations of Selected Pesticides in the Continental United States, 1992–2012"},{"id":352529,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/science/mission-areas/water/national-water-quality-program?qt-programs_l2_landing_page=0#qt-programs_l2_landing_page","text":"National Water Quality Program"},{"id":352528,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5159/downloads/","text":"Model Archive","description":"SIR 2017–5159 Model Archive"},{"id":352526,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5159/coverthb.jpg"},{"id":352527,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5159/sir20175159.pdf","text":"Report","size":"2.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5159"}],"contact":"Director, Dakota Water Science Center, North Dakota Office
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
This report describes (1) work done between January 2015 and May 2017 as part of the U.S. Geological Survey (USGS) hexavalent chromium, Cr(VI), background study and (2) the summative-scale approach to be used to estimate the extent of anthropogenic (man-made) Cr(VI) and background Cr(VI) concentrations near the Pacific Gas and Electric Company (PG&E) natural gas compressor station in Hinkley, California. Most of the field work for the study was completed by May 2017. The summative-scale approach and calculation of Cr(VI) background were not well-defined at the time the USGS proposal for the background Cr(VI) study was prepared but have since been refined as a result of data collected as part of this study. The proposed summative scale consists of multiple items, formulated as questions to be answered at each sampled well. Questions that compose the summative scale were developed to address geologic, hydrologic, and geochemical constraints on Cr(VI) within the study area. Each question requires a binary (yes or no) answer. A score of 1 will be assigned for an answer that represents data consistent with anthropogenic Cr(VI); a score of –1 will be assigned for an answer that represents data inconsistent with anthropogenic Cr(VI). The areal extent of anthropogenic Cr(VI) estimated from the summative-scale analyses will be compared with the areal extent of anthropogenic Cr(VI) estimated on the basis of numerical groundwater flow model results, along with particle-tracking analyses. On the basis of these combined results, background Cr(VI) values will be estimated for “Mojave-type” deposits, and other deposits, in different parts of the study area outside the summative-scale mapped extent of anthropogenic Cr(VI).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181045","collaboration":"Prepared in cooperation with the Lahontan Regional Water Quality Control Board and the State Water Resources Control Board","usgsCitation":"Izbicki, J.A., and Groover, K., 2018, Natural and man-made hexavalent chromium, Cr(VI), in groundwater near a mapped plume, Hinkley, California—study progress as of May 2017, and a summative-scale approach to estimate background Cr(VI) concentrations: U.S. Geological Survey Open-File Report 2018–1045, 28 p., https://doi.org/10.3133/ofr20181045.","productDescription":"vi, 28 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-095489","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":352720,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1045/ofr20181045.pdf","text":"Report","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1045"},{"id":352719,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1045/coverthb.jpg"}],"country":"United States","state":"California","city":"Hinkley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.2333,\n 34.8667\n ],\n [\n -117.0667,\n 34.8667\n ],\n [\n -117.0667,\n 35.0333\n ],\n [\n -117.2333,\n 35.0333\n ],\n [\n -117.2333,\n 34.8667\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
Tributyltin (TBT) has been recognized as an endocrine disrupting chemical (EDC) for several decades. However, only in the last decade, was its primary endocrine mechanism of action (MeOA) elucidated—interactions with the nuclear retinoid-X receptor (RXR), peroxisome proliferator-activated receptor γ (PPARγ), and their heterodimers. This molecular initiating event (MIE) alters a range of reproductive, developmental, and metabolic pathways at the organism level. It is noteworthy that a variety of MeOAs have been proposed over the years for the observed endocrine-type effects of TBT; however, convincing data for the MIE was provided only recently and now several researchers have confirmed and refined the information on this MeOA. One of the most important lessons learned from years of research on TBT concerns apparent species sensitivity. Several aspects such as the rates of uptake and elimination, chemical potency, and metabolic capacity are all important for identifying the most sensitive species for a given chemical, including EDCs. For TBT, much of this was discovered by trial and error, hence important relationships and important sensitive taxa were not identified until several decades after its introduction to the environment. As recognized for many years, TBT-induced responses are known to occur at very low concentrations for molluscs, a fact that has more recently also been observed in fish species. This review explores the MeOA and effects of TBT in different species (aquatic molluscs and other invertebrates, fish, amphibians, birds, and mammals) according to the OECD Conceptual Framework for Endocrine Disruptor Testing and Assessment (CFEDTA). The information gathered on biological effects that are relevant for populations of aquatic animals was used to construct Species Sensitivity Distributions (SSDs) based on No Observed Effect Concentrations (NOECs) and Lowest Observed Effect Concentrations (LOECs). Fish appear at the lower end of these distributions, showing that they are as sensitive as molluscs, and for some species, even more sensitive. Concentrations in the range of 1 ng/L for water exposure (10 ng/g for whole-body burden) have been shown to elicit endocrine-type responses, whereas mortality occurs at water concentrations ten times higher. Current screening and assessment methodologies as compiled in the OECD CFEDTA are able to identify TBT as a potent endocrine disruptor with a high environmental risk for the original use pattern. If those approaches had been available when TBT was introduced to the market, it is likely that its use would have been regulated sooner, thus avoiding the detrimental effects on marine gastropod populations and communities as documented over several decades.
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