Nitrogen-fixing lichens (cyanolichens) are an important source of nitrogen (N) in Pacific Northwest forests, but limitation of lichen growth by elements essential for N fixation is poorly understood. To investigate how nutrient limitation may affect cyanolichen growth rates, we fertilized a tripartite cyanobacterial lichen (Lobaria pulmonaria) and a green algal non-nitrogen fixing lichen (Usnea longissima) with the micronutrients molybdenum (Mo) and vanadium (V), both known cofactors for enzymes involved in N fixation, and the macronutrient phosphorus (P). We then grew treated lichens in the field for one year in western Oregon, USA. Lichen growth was very rapid for both species and did not differ across treatments, despite a previous demonstration of P-limitation in L. pulmonaria at a nearby location. To reconcile these disparate findings, we analyzed P, Mo, and V concentrations, natural abundance δ15N isotopes, %N and change in thallus N in Lobaria pulmonaria from both growth experiments. Nitrogen levels in deposition and in lichens could not explain the large difference in growth or P limitation observed between the two studies. Instead, we provide evidence that local differences in P availability may have caused site-specific responses of Lobaria to P fertilization. In the previous experiment, Lobaria had low background levels of P, and treatment with P more than doubled growth. In contrast, Lobaria from the current experiment had much higher background P concentrations, similar to P-treated lichens in the previous experiment, consistent with the idea that ambient variation in P availability influences the degree of P limitation in cyanolichens. We conclude that insufficient P, Mo, and V did not limit the growth of either cyanolichens or chlorolichens at the site of the current experiment. Our findings point to the need to understand landscape-scale variation in P availability to cyanolichens, and its effect on spatial patterns of cyanolichen nutrient limitation and N fixation.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1890/ES15-00140.1","usgsCitation":"Marks, J.A., Pett-Ridge, J., Perakis, S.S., Allen, J.L., and McCune, B., 2015, Response of the nitrogen-fixing lichen Lobaria pulmonaria to phosphorus, molybdenum, and vanadium: Ecosphere, v. 6, no. 9, Art 155: 17 p., https://doi.org/10.1890/ES15-00140.1.","productDescription":"Art 155: 17 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064227","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":471731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es15-00140.1","text":"Publisher Index Page"},{"id":309578,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","county":"Douglas County, Polk County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.6,\n 43\n ],\n [\n -123.6,\n 43.1\n ],\n [\n -123.5,\n 43.1\n ],\n [\n -123.5,\n 43\n ],\n [\n -123.6,\n 43\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.6,\n 44.7\n ],\n [\n -123.6,\n 44.8\n ],\n [\n -123.5,\n 44.8\n ],\n [\n -123.5,\n 44.7\n ],\n [\n -123.6,\n 44.7\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-25","publicationStatus":"PW","scienceBaseUri":"56139126e4b0ba4884c60f6c","contributors":{"authors":[{"text":"Marks, Jade A","contributorId":146930,"corporation":false,"usgs":false,"family":"Marks","given":"Jade","email":"","middleInitial":"A","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":576576,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pett-Ridge, Julie","contributorId":146932,"corporation":false,"usgs":false,"family":"Pett-Ridge","given":"Julie","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":576577,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perakis, Steven S. sperakis@usgs.gov","contributorId":3117,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":576578,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, Jessica L","contributorId":149053,"corporation":false,"usgs":false,"family":"Allen","given":"Jessica","email":"","middleInitial":"L","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":576579,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCune, Bruce","contributorId":149054,"corporation":false,"usgs":false,"family":"McCune","given":"Bruce","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":576580,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70158676,"text":"70158676 - 2015 - Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios","interactions":[],"lastModifiedDate":"2015-12-07T11:17:03","indexId":"70158676","displayToPublicDate":"2015-10-05T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2925,"text":"Ocean Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios","docAbstract":"Hindcast and 21st century winds, simulated by General Circulation Models (GCMs), were used to drive global- and regional-scale spectral wind-wave generation models in the Pacific Ocean Basin to assess future wave conditions along the margins of the North American west coast and Hawaiian Islands. Three-hourly winds simulated by four separate GCMs were used to generate an ensemble of wave conditions for a recent historical time-period (1976–2005) and projections for the mid and latter parts of the 21st century under two radiative forcing scenarios (RCP 4.5 and RCP 8.5), as defined by the fifth phase of the Coupled Model Inter-comparison Project (CMIP5) experiments. Comparisons of results from historical simulations with wave buoy and ERA-Interim wave reanalysis data indicate acceptable model performance of wave heights, periods, and directions, giving credence to generating projections. Mean and extreme wave heights are projected to decrease along much of the North American west coast. Extreme wave heights are projected to decrease south of ∼50°N and increase to the north, whereas extreme wave periods are projected to mostly increase. Incident wave directions associated with extreme wave heights are projected to rotate clockwise at the eastern end of the Aleutian Islands and counterclockwise offshore of Southern California. Local spatial patterns of the changing wave climate are similar under the RCP 4.5 and RCP 8.5 scenarios, but stronger magnitudes of change are projected under RCP 8.5. Findings of this study are similar to previous work using CMIP3 GCMs that indicates decreasing mean and extreme wave conditions in the Eastern North Pacific, but differ from other studies with respect to magnitude and local patterns of change. This study contributes toward a larger ensemble of global and regional climate projections needed to better assess uncertainty of potential future wave climate change, and provides model boundary conditions for assessing the impacts of climate change on coastal systems.
","language":"English","publisher":"Elsevier Science Ltd","publisherLocation":"Oxford, United Kingdom","doi":"10.1016/j.ocemod.2015.07.004","collaboration":"Christie Hegermiller, UCSC; Peter Ruggiero, Oregon State University; Maarten van Ormondt, Deltares,","usgsCitation":"Erikson, L., Hegermiller, C., Barnard, P., Ruggiero, P., and van Ormondt, M., 2015, Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios: Ocean Modelling, v. 96, no. 1, p. 171-185, https://doi.org/10.1016/j.ocemod.2015.07.004.","productDescription":"15 p.","startPage":"171","endPage":"185","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051162","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":309542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -180,\n -3.513421045640032\n ],\n [\n -180,\n 65.2198939361321\n ],\n [\n -78.046875,\n 65.2198939361321\n ],\n [\n -78.046875,\n -3.513421045640032\n ],\n [\n -180,\n -3.513421045640032\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"96","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56139126e4b0ba4884c60f6a","contributors":{"authors":[{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":147149,"corporation":false,"usgs":true,"family":"Erikson","given":"Li H.","email":"lerikson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":576458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hegermiller, Christie 0000-0002-6383-7508 chegermiller@usgs.gov","orcid":"https://orcid.org/0000-0002-6383-7508","contributorId":149010,"corporation":false,"usgs":true,"family":"Hegermiller","given":"Christie","email":"chegermiller@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruggiero, Peter","contributorId":15709,"corporation":false,"usgs":false,"family":"Ruggiero","given":"Peter","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":576461,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Ormondt, Martin","contributorId":149011,"corporation":false,"usgs":false,"family":"van Ormondt","given":"Martin","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":576462,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157362,"text":"ofr20151176 - 2015 - Preliminary estimates of annual agricultural pesticide use for counties of the conterminous United States, 2013","interactions":[],"lastModifiedDate":"2016-06-29T13:17:10","indexId":"ofr20151176","displayToPublicDate":"2015-10-05T09:45:00","publicationYear":"2015","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":"2015-1176","title":"Preliminary estimates of annual agricultural pesticide use for counties of the conterminous United States, 2013","docAbstract":"This report provides preliminary estimates of annual agricultural use of 387 pesticide compounds in counties of the conterminous United States in 2013, compiled by means of methods described in Thelin and Stone (2013) and Baker and Stone (2015). U.S. Department of Agriculture county-level data for harvested-crop acreage were used in conjunction with proprietary Crop Reporting District-level pesticide-use data to estimate county-level pesticide use. Where Crop Reporting District data were not available or were incomplete, estimated pesticide use values were calculated with two different methods, resulting in a low and a high estimate based on different assumptions about missing survey data (Thelin and Stone, 2013). Preliminary estimates in this report are expected to be revised upon availability of updated crop acreages in the 2017 Agricultural Census, to be published by the U.S. Department of Agriculture in 2019. Estimates of annual agricultural pesticide use are provided as downloadable, tab-delimited files, which are organized by compound, year, state Federal Information Processing Standard (FIPS) code, county Federal Information Processing Standard code, and amount in kilograms (kg). The files, listed below, are a continuation of the 1992–2009 and 2008–2012 pesticide-use estimates reported by Stone (2013) and Baker and Stone (2015), respectively:
\nHigh estimates of county pesticide use, arranged by pesticide name:
\nTable 1. 1-Methyl Cyclopropene through Chlorantraniliprole
Table 2. Chlorethoxyfos through Diflufenzopyr
Table 3. Dimethenamid through Gibberellic Acid
Table 4. Glufosinate through Metiram
Table 5. Metolachlor through Propazine
Table 6. Propiconazole through Triasulfuron
Table 7. Tribenuron Methyl through Zoxamide
Low estimates of county pesticide use, arranged by pesticide name:
\nTable 8. 1-Methyl Cyclopropene through Chlorantraniliprole
Table 9. Chlorethoxyfos through Diflufenzopyr
Table 10. Dimethenamid through Gibberellic Acid
Table 11. Glufosinate through Metiram
Table 12. Metolachlor through Propazine
Table 13. Propiconazole through Triasulfuron
Table 14. Tribenuron Methyl through Zoxamide
Baker, N.T., and Stone, W.W., 2015, Estimated annual agricultural pesticide use for counties of the conterminous United States, 2008–12: U.S. Geological Survey Data Series 907, 9 p., accessed July, 12, 2015, at http://dx.doi.org/10.3133/ds907.
\nStone, W.W., 2013, Estimated annual agricultural pesticide use for counties of the conterminous United States, 1992–2009: U.S. Geological Survey Data Series 752, 1 p., 14 tables
\nThelin, G.P., and Stone, W.W., 2013, Estimation of annual agricultural pesticide use for counties of the conterminous United States,
1992–2009: U.S. Geological Survey Scientific Investigations Report 2013–5009, 54 p.
Director, Indiana Water Science Center
5957 Lakeside Blvd.
Indianapolis, IN 46278
http://in.water.usgs.gov/
Introduction
\nPesticide-Use Estimates
\nAcknowledgments
\nEmpirical relationships between field-derived Leaf Area Index (LAI) and Leaf Angle Distribution (LAD) and polarimetric synthetic aperture radar (PolSAR) based biophysical indicators were created and applied to map S. alterniflora marsh canopy structure. PolSAR and field data were collected near concurrently in the summers of 2010, 2011, and 2012 in coastal marshes, and PolSAR data alone were acquired in 2009. Regression analyses showed that LAI correspondence with the PolSAR biophysical indicator variables equaled or exceeded those of vegetation water content (VWC) correspondences. In the final six regressor model, the ratio HV/VV explained 49% of the total 77% explained LAI variance, and the HH-VV coherence and phase information accounted for the remainder. HV/HH dominated the two regressor LAD relationship, and spatial heterogeneity and backscatter mechanism followed by coherence information dominated the final three regressor model that explained 74% of the LAD variance. Regression results applied to 2009 through 2012 PolSAR images showed substantial changes in marsh LAI and LAD. Although the direct cause was not substantiated, following a release of freshwater in response to the 2010 Deepwater Horizon oil spill, the fairly uniform interior marsh structure of 2009 was more vertical and dense shortly after the oil spill cessation. After 2010, marsh structure generally progressed back toward the 2009 uniformity; however, the trend was more disjointed in oil impact marshes.
","language":"English","publisher":"Molecular Diversity Preservation International","publisherLocation":"Basel, Switzerland","doi":"10.3390/rs70911295","collaboration":"Amina Rangoonwala USGS, Cathleen E Jones NASA-CalTech","usgsCitation":"Ramsey, E.W., Rangoonwala, A., and Jones, C.E., 2015, Structural classification of marshes with Polarimetric SAR highlighting the temporal mapping of marshes exposed to oil: Remote Sensing, v. 7, no. 9, p. 11295-11321, https://doi.org/10.3390/rs70911295.","productDescription":"27 p.","startPage":"11295","endPage":"11321","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063104","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471732,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs70911295","text":"Publisher Index Page"},{"id":309543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.5,\n 29\n ],\n [\n -92.5,\n 30\n ],\n [\n -89.5,\n 30\n ],\n [\n -89.5,\n 29\n ],\n [\n -92.5,\n 29\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"9","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-02","publicationStatus":"PW","scienceBaseUri":"56139126e4b0ba4884c60f6e","contributors":{"authors":[{"text":"Ramsey, Elijah W. III 0000-0002-4518-5796 ramseye@usgs.gov","orcid":"https://orcid.org/0000-0002-4518-5796","contributorId":2883,"corporation":false,"usgs":true,"family":"Ramsey","given":"Elijah","suffix":"III","email":"ramseye@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":576455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rangoonwala, Amina 0000-0002-0556-0598 rangoonwalaa@usgs.gov","orcid":"https://orcid.org/0000-0002-0556-0598","contributorId":3455,"corporation":false,"usgs":true,"family":"Rangoonwala","given":"Amina","email":"rangoonwalaa@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":576456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Cathleen E.","contributorId":11890,"corporation":false,"usgs":true,"family":"Jones","given":"Cathleen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":576457,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70158670,"text":"70158670 - 2015 - The influence of coral reefs and climate change on wave-driven flooding of tropical coastlines","interactions":[],"lastModifiedDate":"2019-12-11T13:24:59","indexId":"70158670","displayToPublicDate":"2015-10-05T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"The influence of coral reefs and climate change on wave-driven flooding of tropical coastlines","docAbstract":"A numerical model, XBeach, calibrated and validated on field data collected at Roi-Namur Island on Kwajalein Atoll in the Republic of Marshall Islands, was used to examine the effects of different coral reef characteristics on potential coastal hazards caused by wave-driven flooding and how these effects may be altered by projected climate change. The results presented herein suggest that coasts fronted by relatively narrow reefs with steep fore reef slopes (~1:10 and steeper) and deeper, smoother reef flats are expected to experience the highest wave runup. Wave runup increases for higher water levels (sea level rise), higher waves, and lower bed roughness (coral degradation), which are all expected effects of climate change. Rising sea levels and climate change will therefore have a significant negative impact on the ability of coral reefs to mitigate the effects of coastal hazards in the future.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2015GL064861","usgsCitation":"Quataert, E., Storlazzi, C.D., van Rooijen, A., van Dongeren, A., and Cheriton, O., 2015, The influence of coral reefs and climate change on wave-driven flooding of tropical coastlines: Geophysical Research Letters, v. 42, no. 15, p. 6407-6415, https://doi.org/10.1002/2015GL064861.","productDescription":"9 p.","startPage":"6407","endPage":"6415","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064753","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471733,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl064861","text":"Publisher Index Page"},{"id":309544,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Republic of the Marshall Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 167.8271484375,\n 7.798078531355303\n ],\n [\n 169.63989257812497,\n 7.798078531355303\n ],\n [\n 169.63989257812497,\n 10.077037154404719\n ],\n [\n 167.8271484375,\n 10.077037154404719\n ],\n [\n 167.8271484375,\n 7.798078531355303\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"15","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-04","publicationStatus":"PW","scienceBaseUri":"56139126e4b0ba4884c60f70","chorus":{"doi":"10.1002/2015gl064861","url":"http://dx.doi.org/10.1002/2015gl064861","publisher":"Wiley-Blackwell","authors":"Quataert Ellen, Storlazzi Curt, van Rooijen Arnold, Cheriton Olivia, van Dongeren Ap","journalName":"Geophysical Research Letters","publicationDate":"8/4/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Quataert, Ellen","contributorId":149000,"corporation":false,"usgs":false,"family":"Quataert","given":"Ellen","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":576425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576424,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Rooijen, Arnold","contributorId":149001,"corporation":false,"usgs":false,"family":"van Rooijen","given":"Arnold","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":576426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Dongeren, Ap","contributorId":149002,"corporation":false,"usgs":false,"family":"van Dongeren","given":"Ap","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":576427,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cheriton, Olivia 0000-0003-3011-9136 ocheriton@usgs.gov","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":149003,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","email":"ocheriton@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576428,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70158664,"text":"70158664 - 2015 - Fish assemblages in the Upper Esopus Creek, NY: Current status, variability, and controlling factors","interactions":[],"lastModifiedDate":"2019-12-11T13:20:58","indexId":"70158664","displayToPublicDate":"2015-10-05T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Fish assemblages in the Upper Esopus Creek, NY: Current status, variability, and controlling factors","docAbstract":"The Upper Esopus Creek receives water diversions from a neighboring basin through the Shandaken Tunnel (the portal) from the Schoharie Reservoir. Although the portal is closed during floods, mean flows and turbidity of portal waters are generally greater than in Esopus Creek above their confluence. These conditions could potentially affect local fish assemblages, yet such effects have not been assessed in this highly regulated stream. We studied water quality, hydrology, temperature, and fish assemblages at 18 sites in the Upper Esopus Creek during 2009–2011 to characterize the effects of the portal input on resident-fish assemblages and to document the status of the fishery resource. In general, fish-community richness increased by 2–3 species at mainstem sites near the portal, and median density and biomass of fish communities at sites downstream of the portal were significantly lower than they were at sites upstream of the portal. Median densities of Salmo trutta (Brown Trout) and all trout species were significantly lower than at mainstem sites downstream from the portal—25.1 fish/0.1 ha and 148.9 fish/0.1 ha, respectively—than at mainstem sites upstream from the portal—68.8 fish/0.1 ha and 357.7 fish/0.1 ha, respectively—yet median biomass for Brown Trout and all trout did not differ between sites from both reaches. The median density of young-of-year Brown Trout at downstream sites (9.3 fish/0.1 ha) was significantly lower than at upstream sites (33.9 fish/0.1 ha). Waters from the portal appeared to adversely affect the density and biomass of young-of-year Brown Trout, but lower temperatures and increased flows also improved habitat quality for mature trout at downstream sites during summer. These findings, and those from companion studies, indicate that moderately turbid waters from the portal had few if any adverse impacts on trout populations and overall fish communities in the Upper Esopus Creek during this study.
","language":"English","publisher":"Eagle Hill Institute","publisherLocation":"Steuben, ME","doi":"10.1656/045.022.0209","collaboration":"Cornell Cooperative Extension of Ulster County; USGS","usgsCitation":"Baldigo, B.P., George, S.D., and Keller, W.T., 2015, Fish assemblages in the Upper Esopus Creek, NY: Current status, variability, and controlling factors: Northeastern Naturalist, v. 22, no. 2, p. 345-371, https://doi.org/10.1656/045.022.0209.","productDescription":"27 p.","startPage":"345","endPage":"371","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042999","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":309548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Upper Esopus Creek, Catskill Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.16571044921875,\n 41.748775021355044\n ],\n [\n -73.9874267578125,\n 41.748775021355044\n ],\n [\n -73.9874267578125,\n 42.409262623071186\n ],\n [\n -75.16571044921875,\n 42.409262623071186\n ],\n [\n -75.16571044921875,\n 41.748775021355044\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56139122e4b0ba4884c60f64","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":576413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":576414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keller, Walter T","contributorId":148996,"corporation":false,"usgs":false,"family":"Keller","given":"Walter","email":"","middleInitial":"T","affiliations":[{"id":17612,"text":"Retired Fisheries Manager, NYS Dept of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":576415,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70156829,"text":"70156829 - 2015 - Borehole strainmeter measurements spanning the 2014, Mw6.0 South Napa Earthquake, California: The effect from instrument calibration","interactions":[],"lastModifiedDate":"2015-11-18T16:19:37","indexId":"70156829","displayToPublicDate":"2015-10-05T06:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Borehole strainmeter measurements spanning the 2014, Mw6.0 South Napa Earthquake, California: The effect from instrument calibration","docAbstract":"The 24 August 2014 Mw6.0 South Napa, California earthquake produced significant offsets on 12 borehole strainmeters in the San Francisco Bay area. These strainmeters are located between 24 and 80 km from the source and the observed offsets ranged up to 400 parts-per-billion (ppb), which exceeds their nominal precision by a factor of 100. However, the observed offsets of tidally calibrated strains differ by up to 130 ppb from predictions based on a moment tensor derived from seismic data. The large misfit can be attributed to a combination of poor instrument calibration and better modeling of the strain fit from the earthquake. Borehole strainmeters require in-situ calibration, which historically has been accomplished by comparing their measurements of Earth tides with the strain-tides predicted by a model. Although the borehole strainmeter accurately measure the deformation within the borehole, the long-wavelength strain signals from tides or other tectonic processes recorded in the borehole are modified by the presence of the borehole and the elastic properties of the grout and the instrument. Previous analyses of surface-mounted, strainmeter data and their relationship with the predicted tides suggest that tidal models could be in error by 30%. The poor fit of the borehole strainmeter data from this earthquake can be improved by simultaneously varying the components of the model tides up to 30% and making small adjustments to the point-source model of the earthquake, which reduces the RMS misfit from 130 ppb to 18 ppb. This suggests that relying on tidal models to calibrate borehole strainmeters significantly reduces their accuracy.
","language":"English","publisher":"William Byrd Press for John Hopkins Press","publisherLocation":"Richmond, VA","doi":"10.1002/2015JB012278","usgsCitation":"Langbein, J.O., 2015, Borehole strainmeter measurements spanning the 2014, Mw6.0 South Napa Earthquake, California: The effect from instrument calibration: Journal of Geophysical Research, v. 120, no. 10, p. 7190-7202, https://doi.org/10.1002/2015JB012278.","productDescription":"13 p.","startPage":"7190","endPage":"7202","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065802","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471734,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012278","text":"Publisher Index Page"},{"id":311547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Napa","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.54425048828125,\n 37.903032319353656\n ],\n [\n -122.54425048828125,\n 38.48261976950729\n ],\n [\n -122.00729370117188,\n 38.48261976950729\n ],\n [\n -122.00729370117188,\n 37.903032319353656\n ],\n [\n -122.54425048828125,\n 37.903032319353656\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"120","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-05","publicationStatus":"PW","scienceBaseUri":"564daf45e4b0112df6c62df0","contributors":{"authors":[{"text":"Langbein, John O. 0000-0002-7821-8101 langbein@usgs.gov","orcid":"https://orcid.org/0000-0002-7821-8101","contributorId":3293,"corporation":false,"usgs":true,"family":"Langbein","given":"John","email":"langbein@usgs.gov","middleInitial":"O.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":570734,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70072588,"text":"70072588 - 2015 - A review of the recent geochemical evolution of Piton de la Fournaise volcano (1927-2010)","interactions":[],"lastModifiedDate":"2015-10-27T16:25:39","indexId":"70072588","displayToPublicDate":"2015-10-04T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"A review of the recent geochemical evolution of Piton de la Fournaise volcano (1927-2010)","docAbstract":"Between 1927 and 2010, more than one hundred eruptions of Piton de la Fournaise produced ~1 km3 of lava, and the volcano’s summit collapsed twice (in 1931 and 2007). These lavas display, respectively, 20 and 65 % of the Sr–Nd and the Pb isotope ranges reported for La Réunion volcanoes over their known eruptive record (3.8 Ma). Variations in major and trace element concentrations and Sr–Pb isotopes do not define a temporal trend at the scale of the century, but display systematic short-term cyclic fluctuations. The positive correlation between 87Sr/86Sr and ratios of trace elements that are more versus less incompatible during partial melting of the mantle (e.g., Nd/Sm, La/Sm) probably results from the sampling of small-scale heterogeneities within the plume source. Changes in the degree of melting and/or crystallization are debated, but these appear ultimately linked to source properties. Lead isotopes do not co-vary with Sr isotopes, in part because of the partitioning of Pb into dense metallic phases that are preferentially sampled during high-flux eruptions. Taken together, Sr–Nd–Pb–Os–Th isotopes do not support contamination of magma with genetically unrelated components, such as the underlying Indian oceanic crust, mantle lithosphere, seawater, or seawater-altered lavas. Yet, in some rare cases (e.g. the 1998 Hudson eruption), the compositional patterns suggest that the parental magma assimilated older volcanic products within the edifice, such as crystal cumulates and/or interstitial differentiated melts. The geochemical fluctuations over the 1927–2010 time period constrain the residence time of magma in the shallow reservoir to 10–30 years and its size to 0.1–0.3 km3. The magma residence time during the course of the long-lived 1998 eruption is estimated to be an order of magnitude shorter, but the reservoir was probably of similar size. Instead, the shorter magma residence for the 1998 eruption was probably due to a higher magma flux.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Active volcanoes of the southwest Indian Ocean","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-642-31395-0_11","usgsCitation":"Pietruszka, A., and Vlastelic, I., 2015, A review of the recent geochemical evolution of Piton de la Fournaise volcano (1927-2010), chap. of Active volcanoes of the southwest Indian Ocean, p. 185-201, https://doi.org/10.1007/978-3-642-31395-0_11.","productDescription":"17 p.","startPage":"185","endPage":"201","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045693","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":310690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Piton de la Fournaise, Réunion island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 55.66841125488281,\n -21.188893398817655\n ],\n [\n 55.81535339355469,\n -21.204257977694652\n ],\n [\n 55.80230712890625,\n -21.2836161525487\n ],\n [\n 55.68214416503906,\n -21.290653925975697\n ],\n [\n 55.64094543457031,\n -21.218340770952555\n ],\n [\n 55.65605163574218,\n -21.188893398817655\n ],\n [\n 55.66841125488281,\n -21.188893398817655\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2015-10-04","publicationStatus":"PW","scienceBaseUri":"5630a02be4b093cee78203e1","contributors":{"authors":[{"text":"Pietruszka, Aaron J.","contributorId":97024,"corporation":false,"usgs":true,"family":"Pietruszka","given":"Aaron J.","affiliations":[],"preferred":false,"id":518465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vlastelic, Ivan","contributorId":149458,"corporation":false,"usgs":false,"family":"Vlastelic","given":"Ivan","email":"","affiliations":[],"preferred":false,"id":578494,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70158030,"text":"ofr20151189 - 2015 - Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2014","interactions":[],"lastModifiedDate":"2015-10-05T11:04:29","indexId":"ofr20151189","displayToPublicDate":"2015-10-02T17:00:00","publicationYear":"2015","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":"2015-1189","title":"Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2014","docAbstract":"Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were re-encountered on remote underwater antennas deployed throughout sucker spawning areas. Captures and remote encounters during the spawning season in spring 2014 were incorporated into capture-recapture analyses of population dynamics.
\nCormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish were examined to provide corroborating evidence of recruitment. Model estimates of survival and recruitment were used to derive estimates of changes in population size over time and to determine the status of the populations through 2013. Separate analyses were conducted for each species and also for each subpopulation of Lost River suckers (LRS). Shortnose suckers (SNS) and one subpopulation of LRS migrate into tributary rivers to spawn, whereas the other LRS subpopulation spawns at groundwater upwelling areas along the eastern shoreline of the lake.
\nIn 2014, we captured, tagged, and released 496 LRS at four lakeshore spawning areas and recaptured an additional 970 individuals that had been tagged in previous years. Across all four areas, the remote antennas detected 6,370 individual LRS during the spawning season. Spawning activity peaked in April and most individuals were encountered at Cinder Flats and Sucker Springs. In the Williamson River, we captured, tagged, and released 3,038 LRS and 267 SNS, and recaptured 762 LRS and 156 SNS that had been tagged in previous years. Remote PIT tag antennas in the traps at the weir on the Williamson River and remote antenna systems that spanned the river at three different locations on the Williamson and Sprague Rivers detected a total of 23,446 LRS and 6,259 SNS. Most LRS passed upstream in the first and second weeks of April when water temperatures were increasing and greater than 10 °C. In contrast, upstream passage for SNS occurred in two pulses, one in early April and one in late April to early May, when water temperatures were increasing and near or greater than 12 °C. Finally, an additional 375 LRS and 884 SNS were captured in trammel net sampling at pre-spawn staging areas in the northeastern part of the lake. Of these, 111 of the LRS and 390 of the SNS had been PIT-tagged in previous years. For LRS captured at the staging areas that had encounter histories that were informative about their spawning location, 79 percent of the fish were members of the subpopulation that spawns in the rivers.
\nCapture-recapture analyses for the LRS subpopulation that spawns at the shoreline areas included encounter histories for more than 13,200 individuals, and analyses for the subpopulation that spawns in the rivers included more than 36,400 encounter histories. With a few exceptions, the survival of males and females in both subpopulations was high (greater than 0.88) between 1999 and 2012. Notably lower survival occurred for both sexes from the rivers in 2000, for males from the shoreline areas in 2002, and for males from the rivers in 2006 and 2012. Between 2001 and 2013, the abundance of males in the lakeshore spawning subpopulation decreased by at least 55 percent and the abundance of females decreased by at least 42 percent. Capture-recapture models suggested that the abundance of both sexes in the river spawning subpopulation of LRS had increased substantially since 2006; increases were mostly due to large estimated recruitment events in 2006 and 2008. We know that the estimates in 2006 are substantially biased in favor of recruitment because of a sampling issue. We are skeptical of the magnitude of recruitment indicated by the 2008 estimates as well because (1) few small individuals that would indicate the presence of new recruits were captured in that year, and (2) recapture probabilities in recruitment models based on just physical recaptures of fish were lower than desired for robust inferences from capture-recapture models. If we assume instead that little or no recruitment occurred for this subpopulation, the abundance of both sexes in the river spawning subpopulation likely has decreased at rates similar to the rates for the lakeshore spawning subpopulation between 2002 and 2013.
\nCapture-recapture analyses for SNS included encounter histories for more than 19,200 individuals. Most annual survival estimates between 2001 and 2012 were high (greater than 0.80), but SNS experienced more years of low survival than either LRS subpopulation. Annual survival of both sexes was relatively low in 2004, 2010, and 2012. In addition, male survival was low in 2002. Capture-recapture models and size composition data indicate that recruitment of new individuals into the SNS spawning population was trivial between 2001 and 2005. Models indicate that more than 10 percent of the population was new recruits in a number of more recent years. As a result, capture-recapture modeling suggests that the abundance of adult spawning SNS was relatively stable between 2006 and 2010. We are skeptical of the estimated recruitment in 2006 because of the known sampling issue. We also are skeptical of the estimated recruitment in other recent years because few small individuals that would indicate the presence of new recruits were captured in any of those years, and recapture probabilities in recruitment models were low. The best-case scenario for SNS, based on capture-recapture recruitment modeling, indicates that the abundance of males in the spawning population decreased by 77 percent and the abundance of females decreased by 73 percent between 2001 and 2013. Decreases in abundance for both sexes likely are greater than these estimates indicate.
\nDespite relatively high survival in most years, we conclude that both species have experienced substantial decreases in the abundance of spawning adults because losses from mortality have not been balanced by recruitment of new individuals. Although capture-recapture data indicate substantial recruitment of new individuals into the spawning populations for SNS and river spawning LRS in some years, size data do not corroborate these estimates. As a result, the status of the endangered sucker populations in Upper Klamath Lake remains worrisome, especially for shortnose suckers. Our monitoring program provides a robust platform for estimating vital population parameters, evaluating the status of the populations, and assessing the effectiveness of conservation and recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151189","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., Janney, E.C., Hayes, B.S., and Harris, A.C., 2015, Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2014: U.S. Geological Survey Open-File Report 2015-1189, 36 p., https://dx.doi.org/10.3133/ofr20151189.","productDescription":"iv, 36 p.","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065787","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":309534,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1189/ofr20151189.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1189 PDF"},{"id":309533,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1189/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.80610656738281,\n 42.23512673690766\n ],\n [\n -121.81297302246092,\n 42.26511445833756\n ],\n [\n -121.82876586914061,\n 42.279848959767385\n ],\n [\n -121.82258605957031,\n 42.29711950573175\n ],\n [\n -121.81365966796874,\n 42.30879983710443\n ],\n [\n -121.82052612304688,\n 42.34382782918463\n ],\n [\n -121.82327270507812,\n 42.35296235855687\n ],\n [\n -121.80679321289062,\n 42.383401202818526\n ],\n [\n -121.83563232421875,\n 42.42142901536395\n ],\n [\n -121.86447143554686,\n 42.44372793752476\n ],\n [\n -121.87339782714844,\n 42.453354564875475\n ],\n [\n -121.88987731933594,\n 42.449301428414955\n ],\n [\n -121.90086364746094,\n 42.461460050936715\n ],\n [\n -121.91665649414062,\n 42.47361631282951\n ],\n [\n -121.93244934082031,\n 42.47007098029904\n ],\n [\n -121.95716857910155,\n 42.46855149059522\n ],\n [\n -121.97776794433594,\n 42.48323834594139\n ],\n [\n -122.00592041015626,\n 42.49792175437361\n ],\n [\n -122.04711914062499,\n 42.50197174319114\n ],\n [\n -122.05810546875,\n 42.488808320425846\n ],\n [\n -122.06565856933592,\n 42.46753847696729\n ],\n [\n -122.07252502441406,\n 42.46652544694582\n ],\n [\n -122.07870483398436,\n 42.48627657532141\n ],\n [\n -122.08831787109375,\n 42.482731960032936\n ],\n [\n -122.09449768066405,\n 42.46804498583046\n ],\n [\n -122.08145141601561,\n 42.455381034748896\n ],\n [\n -122.04299926757812,\n 42.42548395494743\n ],\n [\n -122.04505920410156,\n 42.416359972082866\n ],\n [\n -122.03201293945311,\n 42.39810802339276\n ],\n [\n -122.00523376464842,\n 42.39151573685182\n ],\n [\n -121.99356079101562,\n 42.40368557113506\n ],\n [\n -122.00042724609374,\n 42.41179748277328\n ],\n [\n -121.98257446289062,\n 42.40622065620649\n ],\n [\n -121.981201171875,\n 42.39405131362432\n ],\n [\n -121.97708129882812,\n 42.37934354245872\n ],\n [\n -121.95854187011717,\n 42.381879610913195\n ],\n [\n -121.95167541503906,\n 42.39455841668649\n ],\n [\n -121.95716857910155,\n 42.42092212947584\n ],\n [\n -121.94618225097656,\n 42.39912215986002\n ],\n [\n -121.94000244140624,\n 42.38035798213233\n ],\n [\n -121.91940307617188,\n 42.370720143531955\n ],\n [\n -121.90086364746094,\n 42.354992073710456\n ],\n [\n -121.92008972167969,\n 42.34941019930749\n ],\n [\n -121.94549560546875,\n 42.34433533786168\n ],\n [\n -121.94961547851562,\n 42.33519955487233\n ],\n [\n -121.94686889648438,\n 42.31590854308647\n ],\n [\n -121.93588256835938,\n 42.28950073090457\n ],\n [\n -121.92283630371092,\n 42.28035698458569\n ],\n [\n -121.92558288574217,\n 42.29711950573175\n ],\n [\n -121.9207763671875,\n 42.30676863078423\n ],\n [\n -121.904296875,\n 42.31083097788356\n ],\n [\n -121.89193725585936,\n 42.31540080499991\n ],\n [\n -121.88987731933594,\n 42.30321386201705\n ],\n [\n -121.87889099121092,\n 42.293056273848215\n ],\n [\n -121.86927795410156,\n 42.277816819534955\n ],\n [\n -121.8548583984375,\n 42.266638876842244\n ],\n [\n -121.84730529785155,\n 42.25495072629938\n ],\n [\n -121.84730529785155,\n 42.245801966774025\n ],\n [\n -121.83769226074219,\n 42.23766862211923\n ],\n [\n -121.8109130859375,\n 42.23105950761338\n ],\n [\n -121.80610656738281,\n 42.23512673690766\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
Three aeromagnetic surveys were flown to improve understanding of the geology and structure in the Sacramento Valley. The resulting data serve as a basis for geophysical interpretations, and support geological mapping, water and mineral resource investigations, and other topical studies. Local spatial variations in the Earth's magnetic field (evident as anomalies on aeromagnetic maps) reflect the distribution of magnetic minerals, primarily magnetite, in the underlying rocks. In many cases the volume content of magnetic minerals can be related to rock type, and abrupt spatial changes in the amount of magnetic minerals commonly mark lithologic or structural boundaries. Bodies of serpentinite and other mafic and ultramafic rocks tend to produce the most intense positive magnetic anomalies (for example, in the northwest part of the map). These rock types are the inferred sources, concealed beneath weakly magnetic, valley-fill deposits, of the most prominent magnetic features in the map area, the magnetic highs that extend along the valley axis. Cenozoic volcanic rocks are also an important source of magnetic anomalies and coincide with short-wavelength anomalies that can be either positive (strong central positive anomaly flanked by lower-amplitude negative anomalies) or negative (strong central negative anomaly flanked by lower-amplitude positive anomalies), reflecting the contribution of remanent magnetization. Rocks with more felsic compositions or even some sedimentary units also can cause measurable magnetic anomalies. For example, the long, linear, narrow north-trending anomalies (with amplitudes of <50 nanoteslas [nT]) along the western margin of the valley coincide with exposures of the Mesozoic Great Valley sequence. Note that isolated, short-wavelength anomalies, such as those in the city of Sacramento and along some of the major roads, are caused by manmade features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151186","usgsCitation":"Langenheim, V.E., 2015, Aeromagnetic survey map of Sacramento Valley, California: U.S. Geological Survey Open-File Report 2015-1186, Map: 32.40 x 44.91 inches; Datasets; Metadata; Read Me, https://doi.org/10.3133/ofr20151186.","productDescription":"Map: 32.40 x 44.91 inches; Datasets; Metadata; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065763","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":309022,"rank":11,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2015/1186/ofr20151186_metadata_sacramento_new.txt","text":"Sacramento","size":"13 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2015-1186 Sacramento 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zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":148146,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria","email":"zulanger@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":574063,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70146877,"text":"tm6D3 - 2015 - Documentation of a restart option for the U.S. Geological Survey coupled Groundwater and Surface-Water Flow (GSFLOW) model","interactions":[],"lastModifiedDate":"2017-08-01T12:43:52","indexId":"tm6D3","displayToPublicDate":"2015-10-02T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-D3","title":"Documentation of a restart option for the U.S. Geological Survey coupled Groundwater and Surface-Water Flow (GSFLOW) model","docAbstract":"A new option to write and read antecedent conditions (also referred to as initial conditions) has been developed for the U.S. Geological Survey (USGS) Groundwater and Surface-Water Flow (GSFLOW) numerical, hydrologic simulation code. GSFLOW is an integration of the USGS Precipitation-Runoff Modeling System (PRMS) and USGS Modular Groundwater-Flow Model (MODFLOW), and provides three simulation modes: MODFLOW-only, PRMS-only, and GSFLOW (or coupled). The new capability, referred to as the restart option, can be used for all three simulation modes, such that the results from a pair (or set) of spin-up and restart simulations are nearly identical to results produced from a continuous simulation for the same time period. The restart option writes all results to files at the end of a spin-up simulation that are required to initialize a subsequent restart simulation. Previous versions of GSFLOW have had some capability to save model results for use as antecedent condiitions in subsequent simulations; however, the existing capabilities were not comprehensive or easy to use. The new restart option supersedes the previous methods. The restart option was developed in collaboration with the National Oceanic and Atmospheric Administration, National Weather Service as part of the Integrated Water Resources Science and Services Partnership. The primary focus for the development of the restart option was to support medium-range (7- to 14-day) forecasts of low streamflow conditions made by the National Weather Service for critical water-supply basins in which groundwater plays an important role.
\nThe spin-up simulation should be run for a sufficient length of time necessary to establish antecedent conditions throughout a model domain. Each GSFLOW application can require different lengths of time to account for the hydrologic stresses to propagate through a coupled groundwater and surface-water system. Typically, groundwater hydrologic processes require many years to come into equilibrium with dynamic climate and other forcing (or stress) data, such as precipitation and well pumping, whereas runoff-dominated surface-water processes respond relatively quickly. Use of a spin-up simulation can substantially reduce execution-time requirements for applications where the time period of interest is small compared to the time for hydrologic memory; thus, use of the restart option can be an efficient strategy for forecast and calibration simulations that require multiple simulations starting from the same day.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section D: Ground-water/Surface-water in Book 6U.S. Geological Survey
Office of Groundwater
411 National Center
Reston, VA 20192
Internet: http://water.usgs.gov/ogw/
The U.S. Geological Survey (USGS) researches Earth science to help address complex issues affecting society and the environment. In 2006, the USGS held the first Scientific Information Management Workshop to bring together staff from across the organization to discuss the data and information management issues affecting the integration and delivery of Earth science research and investigate the use of “communities of practice” as mechanisms to share expertise about these issues. Out of this effort emerged the Council for Data Integration, which was conceived as an official organizational function that would help guide data integration activities and formalize communities of practice into working groups; however, by 2009 it became evident that many members of the Council for Data Integration had an interest in developing data integration solutions and sharing expertise in a less formal, grassroots manner, which transformed the Council into a Community for Data Integration (CDI). As of 2014, the CDI represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the USGS and the CDI community.
\nThe CDI fosters an environment for collaboration and sharing by bringing together expertise from external partners and representatives across the USGS who are involved in research, data management, and information technology. Membership is voluntary and open to USGS employees and other individuals and organizations willing to contribute to the community (if interested, contact cdi@usgs.gov). The purpose of the CDI is to do the following:
• advance understanding of Earth systems through enhanced use of data and information including associated tools and techniques,
• provide a forum for people doing work with data integration to come together to share ideas and learn new skills and techniques, and
• grow overall USGS capabilities with data and information by increasing visibility of the work of many people throughout the USGS and the CDI community.
To achieve these goals, the CDI operates within four applied areas: monthly forums, annual workshop/webinar series, working groups, and projects. The monthly forums, also known as the Opportunity/Challenge of the Month, provide an open dialogue to share and learn about data integration efforts or to present problems that invite the community to offer solutions, advice, and support. Since 2010, the CDI has also sponsored annual workshops/webinar series to encourage the exchange of ideas, sharing of activities, presentations of current projects, and networking among members. Stemming from common interests, the working groups are focused on efforts to address data management and technical challenges including the development of standards and tools, improving interoperability and information infrastructure, and data preservation within USGS and its partners. The growing support for the activities of the working groups led to the CDI’s first formal request for proposals (RFP) process in 2013 to fund projects that produced tangible products. As of 2014, the CDI continues to hold an annual RFP that creates data management tools and practices, collaboration tools, and training in support of data integration and delivery.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151184","usgsCitation":"Langseth, M.L., Chang, M.Y., Carlino, Jennifer, Birch, D.D., Bradley, Joshua, Bristol, R.S., Conzelmann, Craig, Diehl, R.H., Earle, Paul, Ellison, L.E., Everette, A.L., Fuller, Pam, Gordon, J.M., Govoni, D.L., Guy, M.R., Henkel, H.S., Hutchison, V.B., Kern, Tim, Lightsom, F.L., Long, J.W., Longhenry, Ryan, Preston, T.M., Smith, Stan, Viger, R.J., Wesenberg, Katherine, and Wood, Eric, 2015, Community for Data Integration 2014 annual report: U.S. Geological Survey Open-File Report 2015–1184, 40 p., https://dx.doi.org/10.3133/ofr20151184.","productDescription":"vi, 40 p.","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066330","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":309412,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1184/ofr20151184.pdf","text":"Report","size":"7.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1184"},{"id":309411,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1184/coverthb.jpg"}],"contact":"Director, Core Science Analytics and Synthesis
U.S. Geological Survey
108 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
http://www.usgs.gov/core_science_systems/
It is unknown how the current Asian origin highly pathogenic avian influenza H5 viruses arrived, but these viruses are now poised to become endemic in North America. Wild birds harbor these viruses and have dispersed them at regional scales. What is unclear is how the viruses may be moving from the wild bird reservoir into poultry holdings. Active surveillance of live wild birds is likely the best way to determine the true distribution of these viruses. We also suggest that sampling be focused on regions with the greatest risk for poultry losses and attempt to define the mechanisms of transfer to enhance biosecurity. Responding to the recent outbreaks of highly pathogenic avian influenza in North America requires an efficient plan with clear objectives and potential management outcomes.
","language":"English","publisher":"Elsevier","doi":"10.1186/s12985-015-0377-2","usgsCitation":"Flint, P.L., Pearce, J.M., Franson, J.C., and Derksen, D.V., 2015, Wild bird surveillance for highly pathogenic avian influenza H5 in North America: Virology Journal, v. 12, p. 1-6, https://doi.org/10.1186/s12985-015-0377-2.","productDescription":"Article 151; 6 p.","startPage":"1","endPage":"6","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065542","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471735,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12985-015-0377-2","text":"Publisher Index Page"},{"id":309503,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.90625,\n 82.44876405595812\n ],\n [\n -137.8125,\n 76.76054111175668\n ],\n [\n -164.53125,\n 72.71190310803662\n ],\n [\n -167.6953125,\n 68.65655498475735\n ],\n [\n -168.046875,\n 63.704722429433225\n ],\n [\n -171.2109375,\n 58.63121664342478\n ],\n [\n -182.109375,\n 53.33087298301704\n ],\n [\n -153.6328125,\n 49.38237278700955\n ],\n [\n -139.21874999999997,\n 45.82879925192134\n ],\n [\n -129.375,\n 28.613459424004414\n ],\n [\n -114.9609375,\n 7.013667927566642\n ],\n [\n -97.734375,\n 3.8642546157214213\n ],\n [\n -84.375,\n 2.811371193331128\n ],\n [\n -80.85937499999999,\n 5.61598581915534\n ],\n [\n -76.640625,\n 9.102096738726456\n ],\n [\n -69.2578125,\n 14.604847155053898\n ],\n [\n -59.0625,\n 17.308687886770034\n ],\n [\n -55.1953125,\n 34.88593094075317\n ],\n [\n -43.2421875,\n 51.83577752045248\n ],\n [\n -36.5625,\n 60.58696734225869\n ],\n [\n -31.289062500000004,\n 64.92354174306496\n ],\n [\n -19.6875,\n 69.28725695167886\n ],\n [\n -12.3046875,\n 74.77584300649235\n ],\n [\n -6.6796875,\n 80.53207112232734\n ],\n [\n -7.03125,\n 82.63133285369297\n ],\n [\n -15.468749999999998,\n 83.71554430601263\n ],\n [\n -46.40625,\n 84.12497319391095\n ],\n [\n -96.6796875,\n 83.71554430601263\n ],\n [\n -113.90625,\n 82.44876405595812\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-28","publicationStatus":"PW","scienceBaseUri":"560f9cb3e4b0ba4884c5ee9a","chorus":{"doi":"10.1186/s12985-015-0377-2","url":"http://dx.doi.org/10.1186/s12985-015-0377-2","publisher":"Springer Nature","authors":"Flint Paul L., Pearce John M., Franson J. Christian, Derksen Dirk V.","journalName":"Virology Journal","publicationDate":"9/28/2015"},"contributors":{"authors":[{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":576298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearce, John M. 0000-0002-8503-5485 jpearce@usgs.gov","orcid":"https://orcid.org/0000-0002-8503-5485","contributorId":181766,"corporation":false,"usgs":true,"family":"Pearce","given":"John","email":"jpearce@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":576299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Franson, J. Christian 0000-0002-0251-4238 jfranson@usgs.gov","orcid":"https://orcid.org/0000-0002-0251-4238","contributorId":140358,"corporation":false,"usgs":true,"family":"Franson","given":"J.","email":"jfranson@usgs.gov","middleInitial":"Christian","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":576300,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Derksen, Dirk V. dderksen@usgs.gov","contributorId":2269,"corporation":false,"usgs":true,"family":"Derksen","given":"Dirk","email":"dderksen@usgs.gov","middleInitial":"V.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":576301,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159639,"text":"70159639 - 2015 - Microbiological oxidation of antimony(III) with oxygen or nitrate by bacteria isolated from contaminated mine sediments","interactions":[],"lastModifiedDate":"2017-01-12T10:57:52","indexId":"70159639","displayToPublicDate":"2015-10-02T07:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Microbiological oxidation of antimony(III) with oxygen or nitrate by bacteria isolated from contaminated mine sediments","docAbstract":"Bacterial oxidation of arsenite [As(III)] is a well-studied and important biogeochemical pathway that directly influences the mobility and toxicity of arsenic in the environment. In contrast, little is known about microbiological oxidation of the chemically similar anion antimonite [Sb(III)]. In this study, two bacterial strains, designated IDSBO-1 and IDSBO-4, which grow on tartrate compounds and oxidize Sb(III) using either oxygen or nitrate, respectively, as a terminal electron acceptor, were isolated from contaminated mine sediments. Both isolates belonged to the Comamonadaceae family and were 99% similar to previously described species. We identify these novel strains as Hydrogenophagataeniospiralis strain IDSBO-1 and Variovorax paradoxus strain IDSBO-4. Both strains possess a gene with homology to the aioA gene, which encodes an As(III)-oxidase, and both oxidize As(III) aerobically, but only IDSBO-4 oxidized Sb(III) in the presence of air, while strain IDSBO-1 could achieve this via nitrate respiration. Our results suggest that expression of aioA is not induced by Sb(III) but may be involved in Sb(III) oxidation along with an Sb(III)-specific pathway. Phylogenetic analysis of proteins encoded by the aioA genes revealed a close sequence similarity (90%) among the two isolates and other known As(III)-oxidizing bacteria, particularly Acidovorax sp. strain NO1. Both isolates were capable of chemolithoautotrophic growth using As(III) as a primary electron donor, and strain IDSBO-4 exhibited incorporation of radiolabeled [14C]bicarbonate while oxidizing Sb(III) from Sb(III)-tartrate, suggesting possible Sb(III)-dependent autotrophy. Enrichment cultures produced the Sb(V) oxide mineral mopungite and lesser amounts of Sb(III)-bearing senarmontite as precipitates.
","language":"English","publisher":"American Society for Microbiology","publisherLocation":"Washington, D.C.","doi":"10.1128/AEM.01970-15","usgsCitation":"Terry, L.R., Kulp, T., Wiatrowski, H.A., Miller, L., and Oremland, R.S., 2015, Microbiological oxidation of antimony(III) with oxygen or nitrate by bacteria isolated from contaminated mine sediments: Applied and Environmental Microbiology, v. 81, no. 24, p. 8478-8488, https://doi.org/10.1128/AEM.01970-15.","productDescription":"11 p.","startPage":"8478","endPage":"8488","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066137","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471736,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1128/aem.01970-15","text":"External Repository"},{"id":311360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Stibnite/Yellow Pine mining area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.94146728515625,\n 44.813018740612776\n ],\n [\n -115.94146728515625,\n 45.729191061299936\n ],\n [\n -114.63958740234375,\n 45.729191061299936\n ],\n [\n -114.63958740234375,\n 44.813018740612776\n ],\n [\n -115.94146728515625,\n 44.813018740612776\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","issue":"24","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564b0c4fe4b0ebfbef0d3167","contributors":{"authors":[{"text":"Terry, Lee R.","contributorId":149865,"corporation":false,"usgs":false,"family":"Terry","given":"Lee","email":"","middleInitial":"R.","affiliations":[{"id":17843,"text":"Department of Geological Sciences and Environmental Studies, Binghamton University, SUNY, Binghamton NY 13902","active":true,"usgs":false}],"preferred":false,"id":579843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kulp, Thomas R.","contributorId":58364,"corporation":false,"usgs":true,"family":"Kulp","given":"Thomas R.","affiliations":[],"preferred":false,"id":579844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiatrowski, Heather A.","contributorId":85527,"corporation":false,"usgs":true,"family":"Wiatrowski","given":"Heather","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":579845,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Laurence G. 0000-0002-7807-3475 lgmiller@usgs.gov","orcid":"https://orcid.org/0000-0002-7807-3475","contributorId":2460,"corporation":false,"usgs":true,"family":"Miller","given":"Laurence G.","email":"lgmiller@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":579846,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oremland, Ronald S. 0000-0001-7382-0147 roremlan@usgs.gov","orcid":"https://orcid.org/0000-0001-7382-0147","contributorId":931,"corporation":false,"usgs":true,"family":"Oremland","given":"Ronald","email":"roremlan@usgs.gov","middleInitial":"S.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":579842,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70156559,"text":"ds958 - 2015 - Baseline coastal oblique aerial photographs collected from the Virginia/North Carolina border to Montauk Point, New York,The U.S. Geological Survey (USGS) conducts baseline and storm response photography missions to document and understand the changes in vulnerability of the Nation's coasts to extreme storms (Morgan, 2009). On October 5-6, 2014, the USGS conducted an oblique aerial photographic survey from the Virginia/North Carolina border to Montauk Point, New York, aboard a Cessna 182 at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was flown to collect baseline data to assess incremental changes since the last survey, flown in November 2012, and the data can be used in the assessment of future coastal change.
\nThe images provided in this report are Joint Photographic Experts Group (JPEG) images. ExifTool was used to add the following to the header of each photo: time of collection, Global Positioning System (GPS) latitude, GPS longitude, keywords, credit, artist (photographer), caption, copyright, and contact information. The photograph locations are an estimate of the position of the aircraft and do not indicate the location of any feature in the images (see the Navigation Data page). These photographs document the state of the barrier islands and other coastal features at the time of the survey. Pages containing thumbnail images of the photographs, referred to as contact sheets, were created in five-minute segments of flight time. These segments can be found on the Photos and Maps page. Photographs can be opened directly with any JPEG-compatible image viewer by clicking on a thumbnail on the contact sheet.
\nIn addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML files were created using the photographic navigation files.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds958","usgsCitation":"Morgan, K.L.M., 2015, Baseline coastal oblique aerial photographs collected from the Virginia/North Carolina Border to Montauk Point, New York,St. Petersburg Coastal and Marine Science Center
600 4th Street South
St. Petersburg, FL 33701
(727) 502-8000
http://coastal.er.usgs.gov/
Dam removal is increasingly being recognized as a viable river restoration action. Although the main beneficiaries of restored connectivity are often migratory fish populations, little is known regarding recovery of other parts of the freshwater food web, particularly terrestrial components. We measured stable isotopes in key components to the freshwater food web: salmon, freshwater macroinvertebrates and a river specialist bird, American dipper (Cinclus mexicanus), before and after removal of the Elwha Dam, WA, USA. Less than a year after dam removal, salmon returned to the system and released marine-derived nutrients (MDN). In that same year we documented an increase in stable-nitrogen and carbon isotope ratios in American dippers. These results indicate that MDN from anadromous fish, an important nutrient subsidy that crosses the aquatic–terrestrial boundary, can return rapidly to food webs after dams are removed which is an important component of ecosystem recovery.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2015.09.009","usgsCitation":"Tonra, C.M., Sager-Fradkin, K.A., Morley, S.A., Duda, J.J., and Marra, P., 2015, The rapid return of marine-derived nutrients to a freshwater food web following dam removal: Biological Conservation, v. 192, p. 130-134, https://doi.org/10.1016/j.biocon.2015.09.009.","productDescription":"5 p.","startPage":"130","endPage":"134","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067105","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":309524,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha dam, Glines Canyon dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.57009887695312,\n 48.14363976215909\n ],\n [\n -123.5639190673828,\n 48.12553866602601\n ],\n [\n -123.56666564941406,\n 48.089775986542044\n ],\n [\n -123.59550476074217,\n 48.049627977799595\n ],\n [\n -123.60305786132812,\n 48.011056420797836\n ],\n [\n -123.60889434814453,\n 47.979580862893755\n ],\n [\n -123.58211517333984,\n 47.951305426762616\n ],\n [\n -123.57044219970702,\n 47.96280137366943\n ],\n [\n -123.56803894042969,\n 48.036085303327546\n ],\n [\n -123.5635757446289,\n 48.0771614158644\n ],\n [\n -123.55121612548828,\n 48.09917756303404\n ],\n [\n -123.54434967041016,\n 48.11499584761036\n ],\n [\n -123.54778289794922,\n 48.13264238851409\n ],\n [\n -123.5577392578125,\n 48.14959568930188\n ],\n [\n -123.56838226318358,\n 48.14524334899598\n ],\n [\n -123.57044219970702,\n 48.14111973876637\n ],\n [\n -123.57009887695312,\n 48.14363976215909\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"192","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"560f9cb3e4b0ba4884c5ee98","contributors":{"authors":[{"text":"Tonra, Christopher M","contributorId":148955,"corporation":false,"usgs":false,"family":"Tonra","given":"Christopher","email":"","middleInitial":"M","affiliations":[{"id":17600,"text":"Migratory Bird Center, Smithsonian Conservation Biology Institute, National Zoological Park, Washington, DC","active":true,"usgs":false}],"preferred":false,"id":576256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sager-Fradkin, Kimberly A.","contributorId":87103,"corporation":false,"usgs":true,"family":"Sager-Fradkin","given":"Kimberly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":576257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morley, Sarah A.","contributorId":148956,"corporation":false,"usgs":false,"family":"Morley","given":"Sarah","email":"","middleInitial":"A.","affiliations":[{"id":17601,"text":"NOAA Fisheries, Northwest Fisheries Science Center, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":576258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":576255,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marra, Peter P.","contributorId":108030,"corporation":false,"usgs":true,"family":"Marra","given":"Peter P.","affiliations":[],"preferred":false,"id":576259,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70129390,"text":"70129390 - 2015 - Inland valley wetland cultivation and preservation for africa’s green and blue revolution using multi-sensor remote sensing","interactions":[],"lastModifiedDate":"2015-11-02T15:56:31","indexId":"70129390","displayToPublicDate":"2015-10-02T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Inland valley wetland cultivation and preservation for africa’s green and blue revolution using multi-sensor remote sensing","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Remote Sensing of Water Resources, Disasters, and Urban Studies","language":"English","publisher":"CRC Press","usgsCitation":"Thenkabail, P.S., and Teluguntla, P.G., 2015, Inland valley wetland cultivation and preservation for africa’s green and blue revolution using multi-sensor remote sensing, chap. of Remote Sensing of Water Resources, Disasters, and Urban Studies, p. 227-259.","productDescription":"33 p.","startPage":"227","endPage":"259","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057670","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":310965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56389756e4b0d6133fe72fc0","contributors":{"authors":[{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":519859,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teluguntla, Pardhasaradhi G. 0000-0001-8060-9841 pteluguntla@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":5275,"corporation":false,"usgs":true,"family":"Teluguntla","given":"Pardhasaradhi","email":"pteluguntla@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":519860,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70138032,"text":"70138032 - 2015 - Water productivity studies from earth observation data: characterization, modeling and mapping water use and water productivity","interactions":[],"lastModifiedDate":"2015-10-19T14:40:32","indexId":"70138032","displayToPublicDate":"2015-10-02T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Water productivity studies from earth observation data: characterization, modeling and mapping water use and water productivity","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Remote sensing of water resources, disasters, and urban studies","language":"English","publisher":"CRC Press","collaboration":"Antônio de C. Teixeira1,*, Fernando B. T. Hernandez2, Morris Scherer-Warren3, Ricardo G. Andrade1, Janice F. Leivas1, Daniel C. Victoria1, Edson L. Bolfe1, Prasad S. Thenkabail4 and Renato A. M. Franco2","usgsCitation":"de C. Teixeira, A., Hernandez, F.B., Scherer-Warren, M., Andrade, R.G., Leivas, J.F., Victoria, D.C., Bolfe, E.L., Thenkabail, P.S., and Franco, R.A., 2015, Water productivity studies from earth observation data: characterization, modeling and mapping water use and water productivity, chap. of Remote sensing of water resources, disasters, and urban studies, p. 101-127.","productDescription":"27 p.","startPage":"101","endPage":"127","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058357","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":310067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56261499e4b0fb9a11dd7665","contributors":{"authors":[{"text":"de C. Teixeira, Antonio","contributorId":138722,"corporation":false,"usgs":false,"family":"de C. 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SAGE teaches the principles and applications of refraction and reflection seismology, magnetics, gravity, GPS, heat flow, several electromagnetic (EM) methods, and ground-penetrating radar (GPR) in a field-based, hands-on setting. More than 850 students and qualified professionals have attended SAGE, many of whom have gone on to become leaders in academia, industry, and government. SAGE students are exposed to the exciting challenges that face earth scientists today, and they develop skills that are necessary to address the world's growing energy demands. Examples of SAGE research projects include mapping archaeological sites and tectonic structure and investigating water and geothermal resources in the Rio Grande rift.
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2015 - Landfill leachate as a mirror of today's disposable society: Pharmaceuticals and other contaminants of emerging concern in final leachate from landfills in the conterminous United States","interactions":[],"lastModifiedDate":"2021-06-01T14:43:31.062569","indexId":"70154751","displayToPublicDate":"2015-10-01T17:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Landfill leachate as a mirror of today's disposable society: Pharmaceuticals and other contaminants of emerging concern in final leachate from landfills in the conterminous United States","docAbstract":"Final leachates (leachate after storage or treatment processes) from 22 landfills in 12 states were analyzed for 190 pharmaceuticals and other contaminants of emerging concern (CECs), which were detected in every sample, with the number of CECs ranging from 1 to 58 (median = 22). In total, 101 different CECs were detected in leachate samples, including 43 prescription pharmaceuticals, 22 industrial chemicals, 15 household chemicals, 12 nonprescription pharmaceuticals, 5 steroid hormones, and 4 animal/plant sterols. The most frequently detected CECs were lidocaine (91%, local anesthetic), cotinine (86%, nicotine degradate), carisoprodol (82%, muscle relaxant), bisphenol A (77%, component of plastics and thermal paper), carbamazepine (77%, anticonvulsant), and N,N-diethyltoluamide (68%, insect repellent). Concentrations of CECs spanned 7 orders of magnitude, ranging from 2.0 ng/L (estrone) to 17 200 000 ng/L (bisphenol A). Concentrations of household and industrial chemicals were the greatest (∼1000-1 000 000 ng/L), followed by plant/animal sterols (∼1000-100 000 ng/L), nonprescription pharmaceuticals (∼100-10 000 ng/L), prescription pharmaceuticals (∼10-10 000 ng/L), and steroid hormones (∼10-100 ng/L). The CEC concentrations in leachate from active landfills were significantly greater than those in leachate from closed, unlined landfills (p = 0.05). The CEC concentrations were significantly greater (p < 0.01) in untreated leachate compared with treated leachate. The CEC concentrations were significantly greater in leachate disposed to wastewater treatment plants from modern lined landfills than in leachate released to groundwater from closed, unlined landfills (p = 0.04). The CEC concentrations were significantly greater (p = 0.06) in the fresh leachate (leachate before storage or treatment) reported in a previous study compared with the final leachate sampled for the present study.
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Landsat ETM+, and MODIS vegetation indices in crop biomass estimation","docAbstract":"Crop biomass is increasingly being measured with surface reflectance data derived from multispectral broadband (MSBB) and hyperspectral narrowband (HNB) space-borne remotely sensed data to increase the accuracy and efficiency of crop yield models used in a wide array of agricultural applications. However, few studies compare the ability of MSBBs versus HNBs to capture crop biomass variability. Therefore, we used standard data mining techniques to identify a set of MSBB data from the IKONOS, GeoEye-1, Landsat ETM+, MODIS, WorldView-2 sensors and compared their performance with HNB data from the EO-1 Hyperion sensor in explaining crop biomass variability of four important field crops (rice, alfalfa, cotton, maize). The analysis employed two-band (ratio) vegetation indices (TBVIs) and multiband (additive) vegetation indices (MBVIs) derived from Singular Value Decomposition (SVD) and stepwise regression. Results demonstrated that HNB-derived TBVIs and MBVIs performed better than MSBB-derived TBVIs and MBVIs on a per crop basis and for the pooled data: overall, HNB TBVIs explained 5–31% greater variability when compared with various MSBB TBVIs; and HNB MBVIs explained 3–33% greater variability when compared with various MSBB MBVIs. The performance of MSBB MBVIs and TBVIs improved mildly, by combining spectral information across multiple sensors involving IKONOS, GeoEye-1, Landsat ETM+, MODIS, and WorldView-2. A number of HNBs that advance crop biomass modeling were determined. Based on the highest factor loadings on the first component of the SVD, the “red-edge” spectral range (700–740 nm) centered at 722 nm (bandwidth = 10 nm) stood out prominently, while five additional and distinct portions of the recorded spectral range (400–2500 nm) centered at 539 nm, 758 nm, 914 nm, 1130 nm, 1320 nm (bandwidth = 10 nm) were also important. The best HNB vegetation indices for crop biomass estimation involved 549 and 752 nm for rice (R2 = 0.91); 925 and 1104 nm for alfalfa (R2 = 0.81); 722 and 732 nm for cotton (R2 = 0.97); and 529 and 895 nm for maize (R2 = 0.94). The higher spectral resolution of the EO-1 Hyperion hyperspectral sensor and the ability of users to choose distinct HNBs for improved crop biomass estimation outweigh the benefits that come with higher spatial resolution of MSBBs.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.isprsjprs.2015.08.001","usgsCitation":"Marshall, M.T., and Thenkabail, P.S., 2015, Advantage of hyperspectral EO-1 Hyperion over multispectral IKONOS, GeoEye-1, WorldView-2, Landsat ETM+, and MODIS vegetation indices in crop biomass estimation: ISPRS Journal of Photogrammetry and Remote Sensing, v. 108, p. 205-218, https://doi.org/10.1016/j.isprsjprs.2015.08.001.","productDescription":"14 p.","startPage":"205","endPage":"218","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060745","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471737,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.isprsjprs.2015.08.001","text":"Publisher Index Page"},{"id":313981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.05810546875,\n 40.730608477796636\n ],\n [\n -122.82714843749999,\n 40.3130432088809\n ],\n [\n -122.56347656249999,\n 39.90973623453719\n ],\n [\n -122.62939453125001,\n 39.38526381099774\n ],\n [\n -122.23388671874999,\n 38.496593518947556\n ],\n [\n -121.70654296874999,\n 37.78808138412046\n ],\n [\n -121.17919921875001,\n 37.43997405227057\n ],\n [\n -121.00341796874999,\n 36.96744946416934\n ],\n [\n -120.60791015625,\n 36.4566360115962\n ],\n [\n -120.16845703125,\n 36.01356058518153\n ],\n [\n -119.7509765625,\n 35.35321610123821\n ],\n [\n -119.39941406249999,\n 34.95799531086792\n ],\n [\n -118.93798828125,\n 34.97600151317591\n ],\n [\n -118.63037109375,\n 35.15584570226544\n ],\n [\n -118.63037109375,\n 35.764343479667176\n ],\n [\n -118.89404296875,\n 36.24427318493909\n ],\n [\n -119.39941406249999,\n 36.84446074079564\n ],\n [\n -119.88281249999999,\n 37.23032838760387\n ],\n [\n -120.41015624999999,\n 37.80544394934274\n ],\n [\n -120.84960937499999,\n 38.34165619279595\n ],\n [\n -121.28906250000001,\n 38.89103282648849\n ],\n [\n -121.61865234375,\n 39.52099229357195\n ],\n [\n -121.9921875,\n 39.9434364619742\n ],\n [\n -122.05810546875,\n 40.730608477796636\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"108","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"568e48dee4b0e7a44bc4186b","contributors":{"authors":[{"text":"Marshall, Michael T. mmarshall@usgs.gov","contributorId":5480,"corporation":false,"usgs":true,"family":"Marshall","given":"Michael","email":"mmarshall@usgs.gov","middleInitial":"T.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":581537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":581536,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168726,"text":"70168726 - 2015 - Black-tailed and white-tailed jackrabbits in the American West: History, ecology, ecological significance, and survey methods","interactions":[],"lastModifiedDate":"2016-07-11T13:01:36","indexId":"70168726","displayToPublicDate":"2015-10-01T16:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Black-tailed and white-tailed jackrabbits in the American West: History, ecology, ecological significance, and survey methods","docAbstract":"Across the western United States, Leporidae are the most important prey item in the diet of Golden Eagles (Aquila chrysaetos). Leporids inhabiting the western United States include black-tailed (Lepus californicus) and white-tailed jackrabbits (Lepus townsendii) and various species of cottontail rabbit (Sylvilagus spp.). Jackrabbits (Lepus spp.) are particularly important components of the ecological and economic landscape of western North America because their abundance influences the reproductive success and population trends of predators such as coyotes (Canis latrans), bobcats (Lynx rufus), and a number of raptor species. Here, we review literature pertaining to black-tailed and white-tailed jackrabbits comprising over 170 published journal articles, notes, technical reports, conference proceedings, academic theses and dissertations, and other sources dating from the late 19th century to the present. Our goal is to present information to assist those in research and management, particularly with regard to protected raptor species (e.g., Golden Eagles), mammalian predators, and ecological monitoring. We classified literature sources as (1) general information on jackrabbit species, (2) black-tailed or (3) white-tailed jackrabbit ecology and natural history, or (4) survey methods. These categories, especially 2, 3, and 4, were further subdivided as appropriate. The review also produced several tables on population trends, food habits, densities within various habitats, and jackrabbit growth and development. Black-tailed and white-tailed jackrabbits are ecologically similar in general behaviors, use of forms, parasites, and food habits, and they are prey to similar predators; but they differ in their preferred habitats. While the black-tailed jackrabbit inhabits agricultural land, deserts, and shrublands, the white-tailed jackrabbit is associated with prairies, alpine tundra, and sagebrush-steppe. Frequently considered abundant, jackrabbit numbers in western North America fluctuate temporally and spatially. We also reviewed methods used to investigate jackrabbit populations, including spotlight line transects, flushing transects, drive counts, pellet plot counts, collections, roadside counts, mark-recapture studies, and radio-telemetry studies. Our review of jackrabbit literature illustrates a number of deficiencies in our understanding of jackrabbits in general. As an example, a detailed quantitative description of habitat preferences is lacking, as is a thorough understanding of sympatric jackrabbit species interactions. Even the existence of the oft-cited jackrabbit “cycle” is a matter of debate. Survey methods generally do not address efficacy or accuracy in measuring jackrabbit density or abundance. In addition, there is a paucity of information about jackrabbits in the Mojave Desert, with no real understanding of home ranges, habitat preferences, and population dynamics or demographics in this region.
","language":"English","publisher":"Brigham Young University","publisherLocation":"Provo, UT","doi":"10.3398/064.075.0406","usgsCitation":"Simes, M., Longshore, K.M., Nussear, K.E., Beatty, G.L., Brown, D.E., and Esque, T., 2015, Black-tailed and white-tailed jackrabbits in the American West: History, ecology, ecological significance, and survey methods: Western North American Naturalist, v. 75, no. 4, p. 491-519, https://doi.org/10.3398/064.075.0406.","productDescription":"19 p.","startPage":"491","endPage":"519","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068600","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488410,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarsarchive.byu.edu/wnan/vol75/iss4/8","text":"External 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L.","contributorId":167232,"corporation":false,"usgs":false,"family":"Beatty","given":"Greg","email":"","middleInitial":"L.","affiliations":[{"id":24651,"text":"USFWS, Phoenix, AZ","active":true,"usgs":false}],"preferred":false,"id":621434,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, David E.","contributorId":49421,"corporation":false,"usgs":true,"family":"Brown","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":621435,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":145679,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":621430,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70158912,"text":"70158912 - 2015 - Groundwater recharge assessment at local and episodic scale in a soil mantled perched karst aquifer in southern Italy","interactions":[],"lastModifiedDate":"2015-10-07T11:11:03","indexId":"70158912","displayToPublicDate":"2015-10-01T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater recharge assessment at local and episodic scale in a soil mantled perched karst aquifer in southern Italy","docAbstract":"Groundwater recharge assessment of karst aquifers, at various spatial and temporal scales, is a major scientific topic of current importance, since these aquifers play an essential role for both socio-economic development and fluvial ecosystems.
\nIn this study, groundwater recharge was estimated at local and episodic scales in a representative perched karst aquifer in a region of southern Italy with a Mediterranean climate. The research utilized measurements of precipitation, air temperature, soil water content, and water-table depth, obtained in 2008 at the Acqua della Madonna test area (Terminio Mount karst aquifer, Campania region). At this location the aquifer is overlain by ash-fall pyroclastic soils. The Episodic Master Recession (EMR) method, an improved version of the Water Table Fluctuation (WTF) method, was applied to estimate the amount of recharge generated episodically by individual rainfall events. The method also quantifies the amount of precipitation generating each recharge episode, thus permitting calculation of the Recharge to the Precipitation Ratio (RPR) on a storm-by-storm basis.
\nDepending on the seasonally varying air temperature, evapotranspiration, and precipitation patterns, calculated values of RPR varied between 35% and 97% among the individual episodes. A multiple linear correlation of the RPR with both the average intensity of recharging rainfall events and the antecedent soil water content was calculated. Given the relatively easy measurability of precipitation and soil water content, such an empirical model would have great hydrogeological and practical utility. It would facilitate short-term forecasting of recharge in karst aquifers of the Mediterranean region and other aquifers with similar hydrogeological characteristics. By establishing relationships between the RPR and climate-dependent variables such as average storm intensity, it would facilitate prediction of climate-change effects on groundwater recharge. The EMR methodology could further be applied to other aquifers for evaluating the relationship of recharge to various hydrometeorological and hydrogeological processes.
","language":"English","publisher":"European Geophysical Society","publisherLocation":"New York, NY","doi":"10.1016/j.jhydrol.2015.08.032","usgsCitation":"Allocca, V., De Vita, P., Manna, F., and Nimmo, J.R., 2015, Groundwater recharge assessment at local and episodic scale in a soil mantled perched karst aquifer in southern Italy: Journal of Hydrology, v. 529, no. 3, p. 843-853, https://doi.org/10.1016/j.jhydrol.2015.08.032.","productDescription":"11 p.","startPage":"843","endPage":"853","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068702","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":309722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"529","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5616423ee4b0ba4884c61494","contributors":{"authors":[{"text":"Allocca, V.","contributorId":149077,"corporation":false,"usgs":false,"family":"Allocca","given":"V.","email":"","affiliations":[{"id":17631,"text":"Department of Earth, Environment and Resources Sciences, University of Naples “Federico II”, Naples, Italy.","active":true,"usgs":false}],"preferred":false,"id":576822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Vita, P.","contributorId":26207,"corporation":false,"usgs":true,"family":"De Vita","given":"P.","affiliations":[],"preferred":false,"id":576821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Manna, F.","contributorId":149078,"corporation":false,"usgs":false,"family":"Manna","given":"F.","email":"","affiliations":[{"id":17631,"text":"Department of Earth, Environment and Resources Sciences, University of Naples “Federico II”, Naples, Italy.","active":true,"usgs":false}],"preferred":false,"id":576823,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":576820,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148003,"text":"70148003 - 2015 - Ground motion-simulations of 1811-1812 New Madrid earthquakes, central United States","interactions":[],"lastModifiedDate":"2016-01-29T10:55:09","indexId":"70148003","displayToPublicDate":"2015-10-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Ground motion-simulations of 1811-1812 New Madrid earthquakes, central United States","docAbstract":"We performed a suite of numerical simulations based on the 1811–1812 New Madrid seismic zone (NMSZ) earthquakes, which demonstrate the importance of 3D geologic structure and rupture directivity on the ground‐motion response throughout a broad region of the central United States (CUS) for these events. Our simulation set consists of 20 hypothetical earthquakes located along two faults associated with the current seismicity trends in the NMSZ. The hypothetical scenarios range in magnitude from M 7.0 to 7.7 and consider various epicenters, slip distributions, and rupture characterization approaches. The low‐frequency component of our simulations was computed deterministically up to a frequency of 1 Hz using a regional 3D seismic velocity model and was combined with higher‐frequency motions calculated for a 1D medium to generate broadband synthetics (0–40 Hz in some cases). For strike‐slip earthquakes located on the southwest–northeast‐striking NMSZ axial arm of seismicity, our simulations show 2–10 s period energy channeling along the trend of the Reelfoot rift and focusing strong shaking northeast toward Paducah, Kentucky, and Evansville, Indiana, and southwest toward Little Rock, Arkansas. These waveguide effects are further accentuated by rupture directivity such that an event with a western epicenter creates strong amplification toward the northeast, whereas an eastern epicenter creates strong amplification toward the southwest. These effects are not as prevalent for simulations on the reverse‐mechanism Reelfoot fault, and large peak ground velocities (>40 cm/s) are typically confined to the near‐source region along the up‐dip projection of the fault. Nonetheless, these basin response and rupture directivity effects have a significant impact on the pattern and level of the estimated intensities, which leads to additional uncertainty not previously considered in magnitude estimates of the 1811–1812 sequence based only on historical reports.
\nThe region covered by our simulation domain encompasses a large portion of the CUS centered on the NMSZ, including several major metropolitan areas. Based on our simulations, more than eight million people living and working near the NMSZ would experience potentially damaging ground motion and modified Mercalli intensities ranging from VI to VIII if a repeat of the 1811–1812 earthquakes occurred today. Moreover, the duration of strong ground shaking in the greater Memphis metropolitan area could last from 30 to more than 60 s, depending on the magnitude and epicenter.
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