{"pageNumber":"684","pageRowStart":"17075","pageSize":"25","recordCount":165773,"records":[{"id":70206188,"text":"70206188 - 2019 - 13C and 15N NMR identification of product compound classes from aqueous and solid phase photodegradation of 2,4,6-trinitrotoluene","interactions":[],"lastModifiedDate":"2019-10-25T07:16:09","indexId":"70206188","displayToPublicDate":"2019-10-22T07:15:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"13C and 15N NMR identification of product compound classes from aqueous and solid phase photodegradation of 2,4,6-trinitrotoluene","docAbstract":"Abstract \nPhotolysis is one of the main transformation pathways for 2,4,6-trinitrotoluene (TNT) released into the environment. Upon exposure to sunlight, TNT is known to undergo both oxidation and reduction reactions with release of nitrite, nitrate, and ammonium ions, followed by condensation reactions of the oxidation and reduction products. In this study, compound classes of transformation products from the aqueous and solid phase photodegradation of 2,4,6-trinitrotoluene (TNT) have been identified by liquid and solid state 13C and 15N NMR. Aqueous phase experiments were performed on saturated solutions of T15NT in deionized water, natural pond water (pH = 8.3, DOC = 3.0 mg/L), pH 8.0 buffer solution, and in the presence of Suwannee River Natural Organic Matter (SRNOM; pH = 3.7), using a Pyrex-filtered medium pressure mercury lamp. Natural sunlight irradiations were performed on TNT in the solid phase and dissolved in the pond water. In deionized water, carboxylic acid, aldehyde, aromatic amine, primary amide, azoxy, nitrosophenol, and azo compounds were formed. 15N NMR spectra exhibited major peaks centered at 128 to 138 ppm, which are in the range of phenylhydroxylamine and secondary amide nitrogens. The secondary amides are proposed to represent benzanilides, which would arise from photochemical rearrangement of nitrones formed from the condensation of benzaldehyde and phenylhydroxylamine derivatives of TNT. The same compound classes were formed from sunlight irradiation of TNT in the solid phase. Whereas carboxylic acids, aldehydes, aromatic amines, phenylhydroxylamines, and amides were also formed from irradiation of TNT in pond water and in pH 8 buffer solution, azoxy and azo compound formation was inhibited. Solid state 15N NMR spectra of photolysates from the lamp irradiation of unlabeled 2,6-dinitrotoluene in deionized water also demonstrated the formation of aromatic amine, phenylhydroxylamine/ 2° amide, azoxy, and azo nitrogens.","language":"English","publisher":"PLoS One","doi":"10.1371/journal.pone.0224112","usgsCitation":"Thorn, K., 2019, 13C and 15N NMR identification of product compound classes from aqueous and solid phase photodegradation of 2,4,6-trinitrotoluene: PLoS ONE, v. 14, no. 10, 61 p., https://doi.org/10.1371/journal.pone.0224112.","productDescription":"61 p.","ipdsId":"IP-106160","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":459421,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0224112","text":"Publisher Index Page"},{"id":368595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Thorn, Kevin A. 0000-0003-2236-5193","orcid":"https://orcid.org/0000-0003-2236-5193","contributorId":220016,"corporation":false,"usgs":true,"family":"Thorn","given":"Kevin A.","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":773794,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70206294,"text":"70206294 - 2019 - Optical properties of water for prediction of wastewater contamination in surface water","interactions":[],"lastModifiedDate":"2019-10-30T07:03:35","indexId":"70206294","displayToPublicDate":"2019-10-22T07:03:28","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Optical properties of water for prediction of wastewater contamination in surface water","docAbstract":"

No abstract available.

","language":"English","publisher":"Water Environment Federation","collaboration":"Great Lakes Protection Fund, Milwaukee Metropolitan Sewerage District, U.S. EPA","usgsCitation":"Corsi, S., and McLellan, S., 2019, Optical properties of water for prediction of wastewater contamination in surface water, 4 p.","productDescription":"4 p.","startPage":"8","endPage":"11","ipdsId":"IP-108709","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":368733,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368721,"type":{"id":15,"text":"Index Page"},"url":"https://wef.org/link/d2e5a6a4c96345fc8ec091a02387b8cd.aspx"}],"publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Corsi, Steven","contributorId":220105,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":774104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLellan, Sandra","contributorId":220106,"corporation":false,"usgs":false,"family":"McLellan","given":"Sandra","email":"","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":774105,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70207190,"text":"70207190 - 2019 - Improvements in seismic resolution and current limitations in the Global Seismographic Network","interactions":[],"lastModifiedDate":"2019-12-11T15:11:03","indexId":"70207190","displayToPublicDate":"2019-10-21T15:09:48","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Improvements in seismic resolution and current limitations in the Global Seismographic Network","docAbstract":"Station noise levels play a fundamental limitation in our ability to detect seismic signals. These noise levels are frequency-dependent and arise from a number of physically different drivers. At periods greater than 100 s, station noise levels are often limited by the self-noise of the instrument as well as the sensitivity of the instrument to non-seismic noise sources. Recently, station operators in the Global Seismographic Network (GSN) have deployed several Streckeisen STS-6A very broadband borehole seismometers. These sensors provide a potential replacement for the no-longer-produced Streckeisen STS-1 seismometer and the GeoTech KS-54000 borehole seismometer. Along with showing some of the initial observational improvements from installing modern very broadband seismometers at depth, we look at current limitations in the seismic resolution from Earth tide periods 100,000 s (0.01 mHz) to Nyquist at most GSN sites (0.02 s or 50 Hz). Finally, we show the potential for improved observations of continuously excited horizontal Earth hum as well as the splitting of very long-period torsional modes as a result of installing instruments at depth. Both of these observations make use of the low horizontal noise levels which are obtained by installing very broadband borehole seismometers at depth with noise levels similar to the Streckeisen STS-1.","language":"English","publisher":"Oxford University Press","doi":"10.1093/gji/ggz473","usgsCitation":"Ringler, A.T., Steim, J., Wilson, D.C., Widmer-Schnidrig, R., and Anthony, R.E., 2019, Improvements in seismic resolution and current limitations in the Global Seismographic Network: Geophysical Journal International, v. 220, no. 1, p. 508-521, https://doi.org/10.1093/gji/ggz473.","productDescription":"14 p.","startPage":"508","endPage":"521","ipdsId":"IP-112506","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":459424,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggz473","text":"Publisher Index Page"},{"id":370185,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"220","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steim, J.","contributorId":221152,"corporation":false,"usgs":false,"family":"Steim","given":"J.","affiliations":[{"id":40337,"text":"Quanterra Inc.","active":true,"usgs":false}],"preferred":false,"id":777211,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777212,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Widmer-Schnidrig, R.","contributorId":221153,"corporation":false,"usgs":false,"family":"Widmer-Schnidrig","given":"R.","email":"","affiliations":[{"id":40338,"text":"Black Forest Observatory, Institute of Geodesy, Stuttgart University, Wolfach, Germany","active":true,"usgs":false}],"preferred":false,"id":777213,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":777214,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206508,"text":"70206508 - 2019 - Challenges for monitoring the extent and land use/cover changes in monarch butterflies’ migratory habitat across the United States and Mexico","interactions":[],"lastModifiedDate":"2019-11-07T13:48:14","indexId":"70206508","displayToPublicDate":"2019-10-21T13:46:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Challenges for monitoring the extent and land use/cover changes in monarch butterflies’ migratory habitat across the United States and Mexico","docAbstract":"This paper presents a synopsis of the challenges and limitations presented by existing and emerging land use/ land cover (LULC) digital data sets when used to analyze the extent, habitat quality, and LULC changes of the monarch (Danaus plexippus) migratory habitat across the United States of America (US) and Mexico. First, the characteristics, state of the knowledge, and issues related to this habitat are presented. Then, the characteristics of the existing and emerging LULC digital data sets with global or cross-border coverage are listed, followed by the data sets that cover only the US or Mexico. Later, we discuss the challenges for determining the extent, habitat quality, and LULC changes in the monarchs’ migratory habitat when using these LULC data sets in conjunction with the current state of the knowledge of the monarchs’ ecology, behavior, and foraging/roosting plants used during their migration. We point to approaches to address some of these challenges, which can be categorized into: (a) LULC data set characteristics and availability; (b) availability of ancillary land management information; (c) ability to construct accurate forage suitability indices for their migration habitat; and (d) level of knowledge of the ecological and behavioral patterns of the monarchs during their journey.","language":"English","publisher":"MDPI","doi":"10.3390/land8100156","usgsCitation":"Moreno-Sanchez, R., Raines, J., Diffendorfer, J., Drummond, M.A., and Manko, J., 2019, Challenges for monitoring the extent and land use/cover changes in monarch butterflies’ migratory habitat across the United States and Mexico: Land, v. 10, no. 8, 156, 17 p., https://doi.org/10.3390/land8100156.","productDescription":"156, 17 p.","ipdsId":"IP-112731","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research 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PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Moreno-Sanchez, Rafael","contributorId":220357,"corporation":false,"usgs":false,"family":"Moreno-Sanchez","given":"Rafael","email":"","affiliations":[{"id":40160,"text":"UC Denver","active":true,"usgs":false}],"preferred":false,"id":774840,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Raines, James","contributorId":220358,"corporation":false,"usgs":false,"family":"Raines","given":"James","email":"","affiliations":[],"preferred":false,"id":774841,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":774839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drummond, Mark A. 0000-0001-7420-3503 madrummond@usgs.gov","orcid":"https://orcid.org/0000-0001-7420-3503","contributorId":3053,"corporation":false,"usgs":true,"family":"Drummond","given":"Mark","email":"madrummond@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":774842,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Manko, Jessica","contributorId":220359,"corporation":false,"usgs":false,"family":"Manko","given":"Jessica","email":"","affiliations":[{"id":40160,"text":"UC Denver","active":true,"usgs":false}],"preferred":false,"id":774843,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206089,"text":"70206089 - 2019 - Assessing plant production responses to climate across water-limited regions using Google Earth Engine","interactions":[],"lastModifiedDate":"2019-10-22T06:32:15","indexId":"70206089","displayToPublicDate":"2019-10-21T13:41:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Assessing plant production responses to climate across water-limited regions using Google Earth Engine","docAbstract":"(Munson) Climate variability and change acting at broad scales can lead to divergent changes in plant production at local scales. Quantifying how production responds to variation in climate at local scales is essential to understand underlying ecological processes and inform land management decision-making, but has historically been limited in spatiotemporal scale based on the use of discrete ground-based measurements or coarse resolution satellite observations. With the advent of cloud-based computing through Google Earth Engine (GEE), production responses to climate can be evaluated across broad landscapes though time at a resolution useful for ecological and land management applications. Here, GEE was employed to synthesize a multi-platform Landsat time series (1988 – 2014) and evaluate relationships between the soil-adjusted vegetation index (a proxy for plant production) and climate across deserts and plant communities of the southwestern U.S. A “climate pivot point” approach was adopted in GEE to assess the trade-off between production responses to increasing wetness and resistances to drought at 30-m resolution. Consistent with a long-term seasonal climate gradient, production was most related to climate variance during the cool-season in the western deserts, during the warm-season in the eastern deserts, and equally related to both seasons within several desert areas. Communities dominated by grasses and deciduous trees displayed large production responses to an increase in wetness and low resistances to water deficit, while shrublands and evergreen woodlands had variable responses and high drought resistances. Production in plant communities that spanned multiple deserts responded differently to seasonal climate variability in each desert. Defining these plant production sensitivities to climate at 30-m resolution in GEE advances forecasts of how long-term climate trajectories may affect carbon storage, wildlife habitat, and the vulnerability of water-limited ecosystems.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2019.111379","collaboration":"None.","usgsCitation":"Bunting, E., Munson, S.M., and Bradford, J., 2019, Assessing plant production responses to climate across water-limited regions using Google Earth Engine: Remote Sensing of Environment, v. 233, p. 1-15, https://doi.org/10.1016/j.rse.2019.111379.","productDescription":"1113792, 15p.","startPage":"1","endPage":"15","ipdsId":"IP-093613","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":459429,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2019.111379","text":"Publisher Index Page"},{"id":437297,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98ZCJBI","text":"USGS data release","linkHelpText":"Dataset for plant production responses to climate across water-limited regions"},{"id":368461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368458,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0034425719303980?via%3Dihub"}],"country":"United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Texas, Utah","otherGeospatial":"Chihuahuan, Colorado Plateau, Great Basin, Mojave, Sonoran ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.09374999999999,\n 41.705728515237524\n ],\n [\n -119.88281249999999,\n 41.376808565702355\n ],\n [\n -120.84960937499999,\n 38.685509760012\n ],\n [\n -115.83984375,\n 35.60371874069731\n ],\n [\n -115.6640625,\n 32.62087018318113\n ],\n [\n -114.78515624999999,\n 32.91648534731439\n ],\n [\n -110.21484375,\n 31.50362930577303\n ],\n [\n -110.56640625,\n 33.797408767572485\n ],\n [\n -113.64257812499999,\n 34.74161249883172\n ],\n [\n -111.70898437499999,\n 35.88905007936091\n ],\n [\n -108.19335937499999,\n 34.08906131584994\n ],\n [\n -105.29296874999999,\n 30.826780904779774\n ],\n [\n -103.0078125,\n 29.305561325527698\n ],\n [\n -102.12890625,\n 30.221101852485987\n ],\n [\n -107.40234375,\n 36.31512514748051\n ],\n [\n -106.5234375,\n 37.50972584293751\n ],\n [\n -107.22656249999999,\n 38.34165619279595\n ],\n [\n -108.80859375,\n 37.23032838760387\n ],\n [\n -108.369140625,\n 41.11246878918088\n ],\n [\n -111.09374999999999,\n 41.705728515237524\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"233","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bunting, Erin L.","contributorId":208169,"corporation":false,"usgs":false,"family":"Bunting","given":"Erin L.","affiliations":[{"id":37758,"text":"Michigan State University, East Lansing, MI USA","active":true,"usgs":false}],"preferred":false,"id":773528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":773527,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":773529,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215485,"text":"70215485 - 2019 - Hysteretic response of solutes and turbidity at the event scale across forested tropical montane watersheds","interactions":[],"lastModifiedDate":"2020-10-22T12:20:47.44952","indexId":"70215485","displayToPublicDate":"2019-10-21T12:00:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Hysteretic response of solutes and turbidity at the event scale across forested tropical montane watersheds","docAbstract":"Concentration-discharge relationships are a key tool for understanding the sourcing and transport of material from watersheds to fluvial networks. Storm events in particular provide insight into variability in the sources of solutes and sediment within watersheds, and the hydrologic pathways that connect hillslope to stream channel. Here we examine high-frequency sensor-based specific conductance and turbidity data from multiple storm events across two watersheds (Quebrada Sonadora and Rio Icacos) with different lithology in the Luquillo Mountains of Puerto Rico, a forested tropical ecosystem. Our analyses include Hurricane Maria, a category 5 hurricane. To analyze hysteresis, we used a recently developed set of metrics to describe and quantify storm events including the hysteresis index (HI), which describes the directionality of hysteresis loops, and the flushing index (FI), which can be used to infer whether the mobilization of material is source or transport limited. We also examine the role of antecedent discharge to predict hysteretic behavior during storms. Overall, specific conductance and turbidity showed contrasting responses to storms. The hysteretic behavior of specific conductance was very similar across sites, displaying clockwise hysteresis and a negative flushing index indicating proximal sources of solutes and consistent source limitation. In contrast, the directionality of turbidity hysteresis was significantly different between watersheds, although both had strong flushing behavior indicative of transport limitation. Overall, models that included antecedent discharge did not perform any better than models with peak discharge alone, suggesting that the magnitude and trajectory of an individual event was the strongest driver of material flux and hysteretic behavior. Hurricane Maria produced unique hysteresis metrics within both watersheds, indicating a distinctive response to this major hydrological event. The similarity in response of specific conductance to storms suggests that solute sources and pathways are similar in the two watersheds. The divergence in behavior for turbidity suggests that sources and pathways of particulate matter vary between the two watersheds. The use of high-frequency sensor data allows the quantification of storm events while index-based metrics of hysteresis allow for the direct comparison of complex storm events across a heterogeneous landscape and variable flow conditions.","language":"English","publisher":"Frontiers Research Foundation","doi":"10.3389/feart.2019.00126","usgsCitation":"Wymore, A.S., Leon, M.C., Shanley, J.B., and McDowell, W.C., 2019, Hysteretic response of solutes and turbidity at the event scale across forested tropical montane watersheds: Frontiers in Earth Science, v. 7, 126, 13 p., https://doi.org/10.3389/feart.2019.00126.","productDescription":"126, 13 p.","ipdsId":"IP-106557","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":459432,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2019.00126","text":"Publisher Index Page"},{"id":379599,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Puerto Rico","otherGeospatial":"Luquillo Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.47802734375,\n 17.518344187852218\n ],\n [\n -65.54443359375,\n 17.518344187852218\n ],\n [\n -65.54443359375,\n 18.999802829053262\n ],\n [\n -67.47802734375,\n 18.999802829053262\n ],\n [\n -67.47802734375,\n 17.518344187852218\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","noUsgsAuthors":false,"publicationDate":"2019-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Wymore, Adam S.","contributorId":243438,"corporation":false,"usgs":false,"family":"Wymore","given":"Adam","email":"","middleInitial":"S.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":802290,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leon, Miguel C.","contributorId":243439,"corporation":false,"usgs":false,"family":"Leon","given":"Miguel","email":"","middleInitial":"C.","affiliations":[{"id":16979,"text":"University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":802291,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":802292,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDowell, William C.","contributorId":243440,"corporation":false,"usgs":false,"family":"McDowell","given":"William","email":"","middleInitial":"C.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":802293,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215484,"text":"70215484 - 2019 - Identifying credible and diverse GCMs for regional climate change studies—case study: Northeastern United States","interactions":[],"lastModifiedDate":"2020-10-22T12:23:54.199735","indexId":"70215484","displayToPublicDate":"2019-10-21T11:16:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Identifying credible and diverse GCMs for regional climate change studies—case study: Northeastern United States","docAbstract":"Climate data obtained from global climate models (GCMs) form the basis of most studies of regional climate change and its impacts. Using the northeastern US as a test case, we develop a framework to systematically sub-select reliable models for use in climate change studies in the region. We retain 14 of 36 CMIP5 GCMs that (a) have satisfactory historical performance, and (b) provide diverse climate scenarios consistent with uncertainties in the multi-model ensemble (MME). The historical performance is evaluated for a wide variety of standard and process metrics including large-scale atmospheric circulation features that drive regional climate variability. Model performance is then used in conjunction with the assessment of diversity and redundancy in model projections to eliminate models without underrepresenting the uncertainty in the MME. Overall, the models show significant variations in their performance across metrics and seasons with none emerging as the best model. This combined with a lack of a strong relationship between model biases and future projections together highlight the importance of maintaining diversity in projections for risk assessment. The summer mean precipitation projections, in particular, are uncertain but also have considerable redundancy in their spatial patterns within the ensemble, which we use effectively to eliminate models. The better performing models in the retained set do suggest a potential to narrow the ranges in temperature and precipitation projections. But any further refinement should be based on a detailed analysis of the physical processes that drive regional climate variability and extremes to avoid providing overconfident projections.","language":"English","publisher":"Springer","doi":"10.1007/s10584-019-02411-y","usgsCitation":"Karmalkar, A.V., Thibeault, J.M., Bryan, A., and Seth, A., 2019, Identifying credible and diverse GCMs for regional climate change studies—case study: Northeastern United States: Climatic Change, v. 154, p. 367-386, https://doi.org/10.1007/s10584-019-02411-y.","productDescription":"20 p.","startPage":"367","endPage":"386","ipdsId":"IP-097827","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":379598,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont, Delaware, Maryland, West Virginia, Ohio, New Jersey, New York, and Pennsylvania.","otherGeospatial":"Northeastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {\n \"stroke\": \"#555555\",\n \"stroke-width\": 2,\n \"stroke-opacity\": 1,\n \"fill\": \"#555555\",\n \"fill-opacity\": 0.5\n },\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.6171875,\n 41.376808565702355\n ],\n [\n -82.79296874999999,\n 38.47939467327645\n ],\n [\n -81.474609375,\n 37.09023980307208\n ],\n [\n -75.498046875,\n 37.3002752813443\n ],\n [\n -73.65234375,\n 40.44694705960048\n ],\n [\n -69.4775390625,\n 41.27780646738183\n ],\n [\n -69.697265625,\n 42.22851735620852\n ],\n [\n -70.751953125,\n 43.32517767999296\n ],\n [\n -66.884765625,\n 44.715513732021336\n ],\n [\n -67.8515625,\n 47.27922900257082\n ],\n [\n -69.521484375,\n 47.69497434186282\n ],\n [\n -70.83984375,\n 45.460130637921004\n ],\n [\n -74.70703125,\n 45.213003555993964\n ],\n [\n -76.201171875,\n 44.276671273775186\n ],\n [\n -79.189453125,\n 43.51668853502906\n ],\n [\n -79.189453125,\n 42.8115217450979\n ],\n [\n -82.6171875,\n 41.376808565702355\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"154","noUsgsAuthors":false,"publicationDate":"2019-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Karmalkar, Ambarish V.","contributorId":243435,"corporation":false,"usgs":false,"family":"Karmalkar","given":"Ambarish","email":"","middleInitial":"V.","affiliations":[{"id":48712,"text":"Dept of Geosciences, UMass Amherst, Amherst MA","active":true,"usgs":false}],"preferred":false,"id":802286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thibeault, Jeanne M.","contributorId":243436,"corporation":false,"usgs":false,"family":"Thibeault","given":"Jeanne","email":"","middleInitial":"M.","affiliations":[{"id":48713,"text":"Department of Geography, University of Connecticut, Storrs, Connecticut","active":true,"usgs":false}],"preferred":false,"id":802287,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bryan, Alexander 0000-0003-2040-7636","orcid":"https://orcid.org/0000-0003-2040-7636","contributorId":205786,"corporation":false,"usgs":true,"family":"Bryan","given":"Alexander","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":802288,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seth, Anji","contributorId":243437,"corporation":false,"usgs":false,"family":"Seth","given":"Anji","email":"","affiliations":[{"id":48713,"text":"Department of Geography, University of Connecticut, Storrs, Connecticut","active":true,"usgs":false}],"preferred":false,"id":802289,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70205248,"text":"fs20193047 - 2019 - Assessment of continuous gas resources in the Permian Phosphoria Formation of the Southwestern Wyoming Province, Wyoming, 2019","interactions":[],"lastModifiedDate":"2020-04-28T21:31:59.631416","indexId":"fs20193047","displayToPublicDate":"2019-10-21T10:45:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-3047","displayTitle":"Assessment of Continuous Gas Resources in the Permian Phosphoria Formation of the Southwestern Wyoming Province, Wyoming, 2019","title":"Assessment of continuous gas resources in the Permian Phosphoria Formation of the Southwestern Wyoming Province, Wyoming, 2019","docAbstract":"

Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 1.4 trillion cubic feet of continuous gas in the Phosphoria Formation of the Southwestern Wyoming Province, Wyoming.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193047","usgsCitation":"Schenk, C.J., Mercier, T.J., Finn, T.M.,Marra, K.R.,Le, P.A., Leathers-Miller, H.M., Pitman, J.K., Brownfield, M.E., and Drake, R.M., II, 2019, Assessment of continuous gas resources in the Permian Phosphoria Formation of the Southwestern Wyoming Province, Wyoming, 2019: U.S. Geological Survey Fact Sheet 2019–3047, 2 p., https://doi.org/10.3133/fs20193047.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-108326","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":374334,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E38JIL","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Southwestern Wyoming Province, Phosphoria Shale Gas Assessment Unit Boundaries and Assessment Input Data Forms"},{"id":368370,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3047/fs20193047.pdf","text":"Report","size":"884 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3047"},{"id":368369,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3047/coverthb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.0166015625,\n 39.639537564366684\n ],\n [\n -108.67675781249999,\n 39.639537564366684\n ],\n [\n -108.67675781249999,\n 46.255846818480315\n ],\n [\n -112.0166015625,\n 46.255846818480315\n ],\n [\n -112.0166015625,\n 39.639537564366684\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046

","tableOfContents":"","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2019-10-21","noUsgsAuthors":false,"publicationDate":"2019-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Schenk, Christopher J. 0000-0002-0248-7305 schenk@usgs.gov","orcid":"https://orcid.org/0000-0002-0248-7305","contributorId":826,"corporation":false,"usgs":true,"family":"Schenk","given":"Christopher","email":"schenk@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":770518,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mercier, Tracey J. 0000-0002-8232-525X tmercier@usgs.gov","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":2847,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey","email":"tmercier@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":770519,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finn, Thomas M. 0000-0001-6396-9351 finn@usgs.gov","orcid":"https://orcid.org/0000-0001-6396-9351","contributorId":778,"corporation":false,"usgs":true,"family":"Finn","given":"Thomas","email":"finn@usgs.gov","middleInitial":"M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":770520,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marra, Kristen R. 0000-0001-8027-5255 kmarra@usgs.gov","orcid":"https://orcid.org/0000-0001-8027-5255","contributorId":4844,"corporation":false,"usgs":true,"family":"Marra","given":"Kristen","email":"kmarra@usgs.gov","middleInitial":"R.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":770521,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Le, Phuong A. 0000-0003-2477-509X ple@usgs.gov","orcid":"https://orcid.org/0000-0003-2477-509X","contributorId":150418,"corporation":false,"usgs":true,"family":"Le","given":"Phuong","email":"ple@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":770522,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leathers-Miller, Heidi M. 0000-0001-5208-9906 hleathers@usgs.gov","orcid":"https://orcid.org/0000-0001-5208-9906","contributorId":150419,"corporation":false,"usgs":true,"family":"Leathers-Miller","given":"Heidi","email":"hleathers@usgs.gov","middleInitial":"M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":770523,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pitman, Janet K. 0000-0002-0441-779X jpitman@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":767,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet","email":"jpitman@usgs.gov","middleInitial":"K.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":770524,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":770525,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Drake, Ronald M. II 0000-0002-1770-4667","orcid":"https://orcid.org/0000-0002-1770-4667","contributorId":206291,"corporation":false,"usgs":true,"family":"Drake","given":"Ronald M.","suffix":"II","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":770526,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70214521,"text":"70214521 - 2019 - Debris-flow monitoring and warning: Review and examples","interactions":[],"lastModifiedDate":"2020-09-30T14:30:29.965691","indexId":"70214521","displayToPublicDate":"2019-10-21T09:30:15","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1431,"text":"Earth-Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Debris-flow monitoring and warning: Review and examples","docAbstract":"

Debris flows represent one of the most dangerous types of mass movements, because of their high velocities, large impact forces and long runout distances. This review describes the available debris-flow monitoring techniques and proposes recommendations to inform the design of future monitoring and warning/alarm systems. The selection and application of these techniques is highly dependent on site and hazard characterization, which is illustrated through detailed descriptions of nine monitoring sites: five in Europe, three in Asia and one in the USA. Most of these monitored catchments cover less than ∼10 km2 and are topographically rugged with Melton Indices greater than 0.5. Hourly rainfall intensities between 5 and 15 mm/h are sufficient to trigger debris flows at many of the sites, and observed debris-flow volumes range from a few hundred up to almost one million cubic meters. The sensors found in these monitoring systems can be separated into two classes: a class measuring the initiation mechanisms, and another class measuring the flow dynamics. The first class principally includes rain gauges, but also contains of soil moisture and pore-water pressure sensors. The second class involves a large variety of sensors focusing on flow stage or ground vibrations and commonly includes video cameras to validate and aid in the data interpretation. Given the sporadic nature of debris flows, an essential characteristic of the monitoring systems is the differentiation between a continuous mode that samples at low frequency (“non-event mode”) and another mode that records the measurements at high frequency (“event mode”). The event detection algorithm, used to switch into the “event mode” depends on a threshold that is typically based on rainfall or ground vibration. Identifying the correct definition of these thresholds is a fundamental task not only for monitoring purposes, but also for the implementation of warning and alarm systems.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2019.102981","usgsCitation":"Hurlimann, M., Coviello, V., Bel, C., Guo, X., Berti, M., Graf, C., Hubl, J., Miyata, S., Smith, J.B., and Yin, H., 2019, Debris-flow monitoring and warning: Review and examples: Earth-Science Reviews, v. 199, 102981, 26 p., https://doi.org/10.1016/j.earscirev.2019.102981.","productDescription":"102981, 26 p.","ipdsId":"IP-112575","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":459437,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2117/177770","text":"External Repository"},{"id":378905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"199","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hurlimann, Marcel","contributorId":241626,"corporation":false,"usgs":false,"family":"Hurlimann","given":"Marcel","email":"","affiliations":[{"id":48365,"text":"Department Division of Geotechnical Engineering and Geosciences, Department of Civil and Environmental Engineering UPC BarcelonaTECH, Barcelona, Spain","active":true,"usgs":false}],"preferred":false,"id":799791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coviello, Velio","contributorId":241627,"corporation":false,"usgs":false,"family":"Coviello","given":"Velio","email":"","affiliations":[{"id":48366,"text":"Faculty of Science and Technology, Free University of Bozen-Bolzano, Italy","active":true,"usgs":false}],"preferred":false,"id":799792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bel, Coraline","contributorId":241628,"corporation":false,"usgs":false,"family":"Bel","given":"Coraline","email":"","affiliations":[{"id":48367,"text":"Université Grenoble Alpes, Irstea, UR ETNA, St-Martin-d’Hères, France","active":true,"usgs":false}],"preferred":false,"id":799793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guo, Xiaojun","contributorId":241629,"corporation":false,"usgs":false,"family":"Guo","given":"Xiaojun","email":"","affiliations":[{"id":48368,"text":"Key Laboratory of Mountain Surface Process and Hazards/Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China","active":true,"usgs":false}],"preferred":false,"id":799794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berti, Matteo","contributorId":241630,"corporation":false,"usgs":false,"family":"Berti","given":"Matteo","affiliations":[{"id":48369,"text":"Dipartimento di Scienze Biologiche, Geologiche e Ambientali, Università di Bologna, Bologna, Italy","active":true,"usgs":false}],"preferred":false,"id":799795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graf, Christoph","contributorId":241631,"corporation":false,"usgs":false,"family":"Graf","given":"Christoph","email":"","affiliations":[{"id":34058,"text":"Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":799796,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hubl, Johannes","contributorId":241632,"corporation":false,"usgs":false,"family":"Hubl","given":"Johannes","email":"","affiliations":[{"id":48370,"text":"Institute of Mountain Risk engineering, Department of Natural Hazards and Civil Engineering, University of Natural Resources and Life Sciences (BOKU), Vienna, Austria","active":true,"usgs":false}],"preferred":false,"id":799797,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miyata, Shusuke","contributorId":241633,"corporation":false,"usgs":false,"family":"Miyata","given":"Shusuke","email":"","affiliations":[{"id":48371,"text":"Disaster Prevention Research Institute, Kyoto University, Takayama, Japan","active":true,"usgs":false}],"preferred":false,"id":799798,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smith, Joel B. 0000-0001-7219-7875 jbsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-7219-7875","contributorId":4925,"corporation":false,"usgs":true,"family":"Smith","given":"Joel","email":"jbsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799799,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yin, Hsiao-Yuan","contributorId":241634,"corporation":false,"usgs":false,"family":"Yin","given":"Hsiao-Yuan","email":"","affiliations":[{"id":48373,"text":"Soil and Water Conservation Bureau, Council of Agriculture, Nantou, Taiwan","active":true,"usgs":false}],"preferred":false,"id":799800,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70211577,"text":"70211577 - 2019 - Comparisons of stereological and other approaches for quantifying macrophage aggregates in piscine spleens","interactions":[],"lastModifiedDate":"2020-07-31T14:24:22.240415","indexId":"70211577","displayToPublicDate":"2019-10-21T09:19:50","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2177,"text":"Journal of Aquatic Animal Health","active":true,"publicationSubtype":{"id":10}},"title":"Comparisons of stereological and other approaches for quantifying macrophage aggregates in piscine spleens","docAbstract":"

Macrophage aggregates (MA s) are focal accumulations of pigmented macrophages in the spleen and other tissues of fish. A central role of MA s is the clearance and destruction of degenerating cells and recycling of some cellular components. Macrophage aggregates also respond to chemical contaminants and infectious agents and may play a role in the adaptive immune response. Tissue damage or physiological stress can result in increased MA accumulation. As a result, MA s may be sensitive biomarkers of environmental stress in fish. Abundance of MA s in tissues has been reported in a variety of ways—most commonly as density, mean size, and relative area—but the utility of these estimates has not been compared. In this study, four different types of splenic MA abundance estimates (abundance score, density, relative area, and total volume) were compared in two fish populations (Striped Bass Morone saxatilis and White Perch M. americana ) with a wide range in ages. Stereological estimates of total volume indicated an increase in MA abundance with spleen volume, which generally corresponded to fish age, and with splenic infections (mycobacteria or trematode parasites). Abundance scores were generally limited in the ability to detect changes in MA abundance by these factors, whereas density estimates were greatly influenced by changes in spleen volume. In some instances, densities declined while the total volume of MA s and spleen volume increased. Experimentally induced acute stress resulted in a decrease in spleen volume and an increase in MA density, although the total volume of MA s remained unchanged. Relative area estimates accounted for the size and number of MA s but not for changes in organ volume. Total volume is an absolute measure of MA abundance irrespective of changes in organ volume or patterns of accumulation and may provide an improved means of quantifying MA s in the spleens of fish.

","language":"English","publisher":"Wiley","doi":"10.1002/aah.10086","usgsCitation":"Matsche, M.A., Blazer, V., and Mazik, P.M., 2019, Comparisons of stereological and other approaches for quantifying macrophage aggregates in piscine spleens: Journal of Aquatic Animal Health, v. 31, no. 4, p. 328-348, https://doi.org/10.1002/aah.10086.","productDescription":"21 p.","startPage":"328","endPage":"348","ipdsId":"IP-101730","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":376946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Choptank River, Nanticoke River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.2176513671875,\n 38.199338565983844\n ],\n [\n -75.7891845703125,\n 38.199338565983844\n ],\n [\n -75.7891845703125,\n 39.049052206453524\n ],\n [\n -76.2176513671875,\n 39.049052206453524\n ],\n [\n -76.2176513671875,\n 38.199338565983844\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Matsche, Mark A","contributorId":194275,"corporation":false,"usgs":false,"family":"Matsche","given":"Mark","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":794675,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":794677,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215430,"text":"70215430 - 2019 - Total grain size distribution of an intense Hawaiian fountaining event: Case study of the1959 Kīlauea Iki eruption","interactions":[],"lastModifiedDate":"2020-10-20T13:12:18.157354","indexId":"70215430","displayToPublicDate":"2019-10-19T15:19:09","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Total grain size distribution of an intense Hawaiian fountaining event: Case study of the1959 Kīlauea Iki eruption","docAbstract":"

The 1959 eruption of Kīlauea Iki on the Island of Hawai’i is a principal example of powerful Hawaiian fountaining. Over 36 days (including repose periods), 16 fountaining episodes created a small cone, a downwind tephra blanket of approximately 0.003 km3 and a lava lake of about 0.04 km3 volume. During the explosive activity, the maximum fountain heights reached 600 m. Based on a dataset of more than 450 tephra grain size samples, we present both a total grain size distribution (TGSD) of the entire downwind tephra deposit, and also TGSDs for two eruptive subunits (the opening and the closing stages). The opening stage was characterized by persistent fountaining over a period of 8 days with fountain heights averaging ∼ 100 m; in contrast, the closing stage was characterized by two short (hours-long) but powerful fountaining episodes (up to 600 m). The significantly different fountaining intensities are reflected in the characteristics of the TGSDs. For the closing stages, we link bimodality of TGSDs to periods of simultaneous deposition of ballistics and fallout from the convective cloud, both of which are a function of the maximum fountain height. The 1959 Kīlauea Iki case study presents a well-constrained set of TGSD data linked with Hawaiian-style fountaining of two contrasting intensities and can be used as a valuable reference point for eruption source parameters in future modeling of pyroclast dispersal during Hawaiian fountaining eruptions.

","language":"English","publisher":"Springer","doi":"10.1007/s00445-019-1304-y","usgsCitation":"Mueller, S.B., Houghton, B.F., Swanson, D., Poret, M., and Fagents, S.A., 2019, Total grain size distribution of an intense Hawaiian fountaining event: Case study of the1959 Kīlauea Iki eruption: Bulletin of Volcanology, v. 81, 43, 13 p., https://doi.org/10.1007/s00445-019-1304-y.","productDescription":"43, 13 p.","ipdsId":"IP-102777","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":379533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.6103515625,\n 19.129599439736836\n ],\n [\n -154.9896240234375,\n 19.129599439736836\n ],\n [\n -154.9896240234375,\n 19.65810729872147\n ],\n [\n -155.6103515625,\n 19.65810729872147\n ],\n [\n -155.6103515625,\n 19.129599439736836\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","noUsgsAuthors":false,"publicationDate":"2019-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Mueller, Sebastian B","contributorId":243387,"corporation":false,"usgs":false,"family":"Mueller","given":"Sebastian","email":"","middleInitial":"B","affiliations":[{"id":48709,"text":"University of Hawai`i","active":true,"usgs":false}],"preferred":false,"id":802178,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false},{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":802179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swanson, Donald A. 0000-0002-1680-3591","orcid":"https://orcid.org/0000-0002-1680-3591","contributorId":229682,"corporation":false,"usgs":true,"family":"Swanson","given":"Donald A.","affiliations":[],"preferred":true,"id":802180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poret, Matthieu","contributorId":243388,"corporation":false,"usgs":false,"family":"Poret","given":"Matthieu","email":"","affiliations":[{"id":33971,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Bologna, Italy","active":true,"usgs":false}],"preferred":false,"id":802181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fagents, Sarah A.","contributorId":243389,"corporation":false,"usgs":false,"family":"Fagents","given":"Sarah","email":"","middleInitial":"A.","affiliations":[{"id":48709,"text":"University of Hawai`i","active":true,"usgs":false}],"preferred":false,"id":802182,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215421,"text":"70215421 - 2019 - Ecosystem size predicts social dynamics in recreational fisheries","interactions":[],"lastModifiedDate":"2020-10-19T20:16:26.631262","indexId":"70215421","displayToPublicDate":"2019-10-19T15:11:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem size predicts social dynamics in recreational fisheries","docAbstract":"Recreational fisheries are complex adaptive systems that are inherently difficult to manage due to a heterogeneous user group (consumptive vs. non-consumptive) that utilize patchily distributed resources on the landscape (lakes, rivers, coastlines). There is a need to identify which system components can effectively predict and be used to manage nonlinear and cross-scale dynamics within these systems. We examine how ecosystem size or waterbody size can be used to explain complicated and elusive angler-resource dynamics in recreational fisheries. Waterbody size determined angler behavior among 48 Nebraska, U.S.A. waterbodies during an 11-year study period. Angler behavior was often unique and nonlinear across waterbody sizes. For example, anglers spent more time fishing and harvested more fish at larger waterbodies compared to smaller waterbodies. Time fished increased across smaller waterbodies but reached a threshold at larger waterbodies. The number of fish released increased as a function of waterbody size across smaller waterbodies but then plateaued. Subtle changes in waterbody size caused abrupt changes in angler behavior—that is, waterbody size structures angler-resource dynamics in recreational fisheries. We believe that including waterbody size, a simple and easily measured metric, in fisheries management will increase effectiveness of cross-scale actions and minimize unintended consequences for recreational fisheries. Applying uniform management actions (e.g., harvest regulations) across small and large waterbodies may elicit contrasting angler-resource responses. Waterbody size may also be useful for understanding angler typologies. Based on our findings, we expect that ecosystem size is a prominent and valuable system component that will determine and explain coupled user-resource dynamics in other complex adaptive systems.","language":"English","publisher":"Resilience Alliance","doi":"10.5751/ES-10961-240217","usgsCitation":"Kaemingk, M., Chizinski, C.J., Allen, C.R., and Pope, K.L., 2019, Ecosystem size predicts social dynamics in recreational fisheries: Ecology and Society, v. 24, no. 2, 17, 12 p., https://doi.org/10.5751/ES-10961-240217.","productDescription":"17, 12 p.","ipdsId":"IP-097509","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":459443,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-10961-240217","text":"Publisher Index Page"},{"id":379532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kaemingk, M. A.","contributorId":243357,"corporation":false,"usgs":false,"family":"Kaemingk","given":"M. A.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":802131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chizinski, C. J.","contributorId":243358,"corporation":false,"usgs":false,"family":"Chizinski","given":"C.","email":"","middleInitial":"J.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":802132,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":802133,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pope, Kevin L. 0000-0003-1876-1687 kpope@usgs.gov","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":1574,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"kpope@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":802134,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215418,"text":"70215418 - 2019 - Prey fish communities of the Laurentian Great Lakes: A cross-basin overview of status and trends based on bottom trawl surveys, 1978-2016","interactions":[],"lastModifiedDate":"2023-01-19T16:16:25.05494","indexId":"70215418","displayToPublicDate":"2019-10-19T14:56:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":865,"text":"Aquatic Ecosystem Health & Management","active":true,"publicationSubtype":{"id":10}},"title":"Prey fish communities of the Laurentian Great Lakes: A cross-basin overview of status and trends based on bottom trawl surveys, 1978-2016","docAbstract":"

Annual bottom trawl surveys were initiated in the 1970s in Laurentian Great Lakes Superior, Huron, Michigan and Ontario and in 1990 in Erie to provide annual assessments of the status and trends of prey fish communities. Native Cisco Coregonus artedi and Bloater C. hoyi dominated the prey fish community of Lake Superior. Prey fish communities in lakes Huron and Michigan were dominated by nonnative Rainbow Smelt Osmerus mordax and Alewife Alosa pseudoharengus for much of 1978-2016, but Bloater was an important species during the 1980-1990s and more recently has become the dominant prey species in these lakes. Alewife dominated the prey fish community of Lake Ontario during all 1978-2016. While nonnatives dominated the prey fish community in Lake Erie, native Emerald Shiner Notropis atherinoides was an important species and occasionally the dominant prey fish after the establishment of Round Goby Neogobius melanostomus in the late 1990s. During the 1980s-1990s Bythotrephes cederstroemi, Dreissena polymorpha, and Dreissena bugensis caused profound changes in Laurentian Great Lakes ecosystems and likely contributed to declines in fish community biomass in lakes Michigan and Huron. The impacts of these invaders were more muted in lakes Erie and Ontario. Lake Superior stands out as the Laurentian Great Lakes success story: Lake Trout Salvelinus namaycush was restored, and native prey fishes dominate and support a viable fishery. Although the abundance of Bloater has increased recently in lakes Huron and Michigan, recovery of native prey fishes remains uncertain. The absence of native species among the principal prey fish in Lake Ontario indicates a lack of progress in native fish recovery. Recovery of native prey fishes remains unclear in Lake Erie. The ever-changing state of the Laurentian Great Lakes caused by the impacts of invasive species and ongoing climate and ecosystem change will continue to challenge restoration of native fish communities in the 21st Century.

","language":"English","publisher":"Aquatic Ecosystem Health & Management Society","doi":"10.1080/14634988.2019.1674012","usgsCitation":"Gorman, O., 2019, Prey fish communities of the Laurentian Great Lakes: A cross-basin overview of status and trends based on bottom trawl surveys, 1978-2016: Aquatic Ecosystem Health & Management, v. 22, no. 3, p. 263-279, https://doi.org/10.1080/14634988.2019.1674012.","productDescription":"17 p.","startPage":"263","endPage":"279","ipdsId":"IP-107179","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":379531,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.59374999999999,\n 49.03786794532644\n ],\n [\n -92.98828125,\n 46.98025235521883\n ],\n [\n -90.263671875,\n 46.07323062540835\n ],\n [\n -87.62695312499999,\n 46.195042108660154\n ],\n [\n -88.41796875,\n 44.653024159812\n ],\n [\n -88.505859375,\n 41.96765920367816\n ],\n [\n -86.396484375,\n 41.64007838467894\n ],\n [\n -85.95703125,\n 42.68243539838623\n ],\n [\n -86.1328125,\n 45.089035564831036\n ],\n [\n -84.0234375,\n 44.59046718130883\n ],\n [\n -84.287109375,\n 43.26120612479979\n ],\n [\n -83.671875,\n 41.57436130598913\n ],\n [\n -82.177734375,\n 41.11246878918088\n ],\n [\n -78.57421875,\n 42.74701217318067\n ],\n [\n -75.76171875,\n 43.51668853502906\n ],\n [\n -76.81640625,\n 44.465151013519616\n ],\n [\n -79.013671875,\n 44.276671273775186\n ],\n [\n -80.244140625,\n 45.82879925192134\n ],\n [\n -83.49609375,\n 46.437856895024204\n ],\n [\n -84.375,\n 47.517200697839414\n ],\n [\n -83.671875,\n 48.16608541901253\n ],\n [\n -86.923828125,\n 49.15296965617042\n ],\n [\n -88.59374999999999,\n 49.03786794532644\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gorman, Owen 0000-0003-0451-110X","orcid":"https://orcid.org/0000-0003-0451-110X","contributorId":216889,"corporation":false,"usgs":true,"family":"Gorman","given":"Owen","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":802112,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70215417,"text":"70215417 - 2019 - Historical land use and land cover for assessing the northern Colorado Front Range urban landscape","interactions":[],"lastModifiedDate":"2020-10-20T13:15:57.557465","indexId":"70215417","displayToPublicDate":"2019-10-19T14:46:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2375,"text":"Journal of Maps","active":true,"publicationSubtype":{"id":10}},"title":"Historical land use and land cover for assessing the northern Colorado Front Range urban landscape","docAbstract":"We describe historical land-use and land-cover (LULC) maps for the northern Colorado urban Front Range. The Front Range urban landscape is diverse and interspersed with highly productive agriculture as well as natural land cover types including evergreen forest in the Rocky Mountain foothills and Great Plains grassland. To understand the dynamics of urban growth, raster maps were created at a 1 meter resolution for each of four time steps, nominally 1937, 1957, 1977, and 1997. In total, 38 detailed LULC classes were identified using manual interpretation techniques, aerial photographs, historical maps, and other available information. The maps provide high resolution spatial data for understanding the historical progression of urbanization and will allow further analysis of the effects of urban growth on social and ecological systems.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/17445647.2018.1548383","usgsCitation":"Drummond, M.A., Stier, M.P., and Diffendorfer, J., 2019, Historical land use and land cover for assessing the northern Colorado Front Range urban landscape: Journal of Maps, v. 15, no. 2, p. 89-93, https://doi.org/10.1080/17445647.2018.1548383.","productDescription":"5 p.","startPage":"89","endPage":"93","ipdsId":"IP-093283","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":459446,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17445647.2018.1548383","text":"Publisher Index Page"},{"id":437298,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P995RGC9","text":"USGS data release","linkHelpText":"Data release for the Historical land use and land cover for assessing the northern Colorado Front Range urban landscape"},{"id":379530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Northern Colorado Front Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.49072265625,\n 39.317300373271024\n ],\n [\n -104.501953125,\n 39.317300373271024\n ],\n [\n -104.501953125,\n 40.9964840143779\n ],\n [\n -105.49072265625,\n 40.9964840143779\n ],\n [\n -105.49072265625,\n 39.317300373271024\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Drummond, Mark A. 0000-0001-7420-3503 madrummond@usgs.gov","orcid":"https://orcid.org/0000-0001-7420-3503","contributorId":3053,"corporation":false,"usgs":true,"family":"Drummond","given":"Mark","email":"madrummond@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":802109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stier, Michael P. 0000-0002-8518-9855 mpstier@usgs.gov","orcid":"https://orcid.org/0000-0002-8518-9855","contributorId":3121,"corporation":false,"usgs":true,"family":"Stier","given":"Michael","email":"mpstier@usgs.gov","middleInitial":"P.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":802110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":802111,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215416,"text":"70215416 - 2019 - Comparing and improving methods for reconstructing peatland water-table depth from testate amoebae","interactions":[],"lastModifiedDate":"2020-10-19T19:40:15.940198","indexId":"70215416","displayToPublicDate":"2019-10-19T14:19:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1905,"text":"Holocene","active":true,"publicationSubtype":{"id":10}},"title":"Comparing and improving methods for reconstructing peatland water-table depth from testate amoebae","docAbstract":"Proxies that use changes in the composition of ecological communities to reconstruct temporal changes in an environmental covariate are commonly used in paleoclimatology and paleolimnology. Existing methods, such as weighted averaging and modern analog technique,\nrelate compositional data to the covariate in very simple ways, and different methods are seldom compared systematically. We present a new Bayesian model that better represents the underlying data and the complexity in the relationships between species’ abundances and a paleoenvironmental covariate. Using testate amoeba-based reconstructions of water-table depth as a test case, we systematically compare new and existing models in a cross-validation experiment on a large training dataset from North America. We then apply the different\nmodels to a new 7500-year record of testate amoeba assemblages from Caribou Bog in Maine and compare the resulting water-table depth reconstructions. We find that Bayesian models represent an improvement over existing methods in three key ways: more complete use of the underlying compositional data, full and meaningful treatment of uncertainty, and clear paths toward methodological improvements. Furthermore, we highlight how developing and systematically comparing methods leads to an improved understanding of the proxy system.\nThis paper focuses on testate amoebae and water-table depth, but the framework and ideas are widely applicable to other proxies based on compositional data.","language":"English","publisher":"SAGE Publications","doi":"10.1177/0959683619846969","usgsCitation":"Nolan, C., Tipton, J., Booth, R., Hooten, M., and Jackson, S., 2019, Comparing and improving methods for reconstructing peatland water-table depth from testate amoebae: Holocene, v. 29, no. 8, p. 1350-1361, https://doi.org/10.1177/0959683619846969.","productDescription":"12 p.","startPage":"1350","endPage":"1361","ipdsId":"IP-098724","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":459448,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/0959683619846969","text":"Publisher Index 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John","contributorId":166999,"corporation":false,"usgs":false,"family":"Tipton","given":"John","affiliations":[],"preferred":false,"id":802105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Booth, Robert K.","contributorId":243345,"corporation":false,"usgs":false,"family":"Booth","given":"Robert K.","affiliations":[{"id":16160,"text":"Lehigh University","active":true,"usgs":false}],"preferred":false,"id":802106,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":802107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, Stephen 0000-0002-1487-4652","orcid":"https://orcid.org/0000-0002-1487-4652","contributorId":219995,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":802108,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215415,"text":"70215415 - 2019 - Differential effects of temperature and salinity on growth and mortality of oysters (Crassostrea virginica) in Barataria Bay and Breton Sound, Louisiana","interactions":[],"lastModifiedDate":"2020-10-19T19:17:19.843075","indexId":"70215415","displayToPublicDate":"2019-10-19T14:12:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2455,"text":"Journal of Shellfish Research","active":true,"publicationSubtype":{"id":10}},"title":"Differential effects of temperature and salinity on growth and mortality of oysters (Crassostrea virginica) in Barataria Bay and Breton Sound, Louisiana","docAbstract":"Temperature and salinity and their interaction exert a major control on the life cycle of the eastern oyster (Crassostrea virginica), affecting reproduction, development, growth, and mortality. Quantifying specific temperature and salinity relationships on oyster growth and mortality has however proven difficult, with data suggesting potentially region-specific responses. Legacy and recent data from field tray studies from public oyster grounds in Barataria Bay and Breton Sound were used to estimate growth and mortality rates as a function of temperature and salinity. Previous studies conducted in Barataria Bay and Breton Sound reported differences in growth and mortality between the basins. In the present study, environmental conditions were synchronized to compare growth and mortality between basins at similar combinations of temperature and salinity. Results indicate that when temperature and salinity are the same (synchronized), seasonal oyster growth and mortality rates still differ between Barataria Bay and Breton Sound. Given the same salinity and temperature conditions, differences in growth and mortality rates between estuaries may persist due to differences in other environmental conditions (i.e., food quality and composition, hydrology, site history, salinity variation) or localized genetic adaptations to environmental conditions.","language":"English","publisher":"BioOne","doi":"10.2983/035.038.0212","usgsCitation":"Sehlinger, T., Lowe, M., LaPeyre, M.K., and Soniat, T., 2019, Differential effects of temperature and salinity on growth and mortality of oysters (Crassostrea virginica) in Barataria Bay and Breton Sound, Louisiana: Journal of Shellfish Research, v. 38, no. 2, p. 317-326, https://doi.org/10.2983/035.038.0212.","productDescription":"10 p.","startPage":"317","endPage":"326","ipdsId":"IP-105718","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":379528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Lousianna","otherGeospatial":"Barataria Bay and Brenton Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.8349609375,\n 28.714678586705976\n ],\n [\n -89.033203125,\n 28.714678586705976\n ],\n [\n -89.033203125,\n 30.32547125932808\n ],\n [\n -90.8349609375,\n 30.32547125932808\n ],\n [\n -90.8349609375,\n 28.714678586705976\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sehlinger, T.","contributorId":243342,"corporation":false,"usgs":false,"family":"Sehlinger","given":"T.","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":802099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, M.R.","contributorId":243343,"corporation":false,"usgs":false,"family":"Lowe","given":"M.R.","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":802100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":802101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Soniat, T.M.","contributorId":243344,"corporation":false,"usgs":false,"family":"Soniat","given":"T.M.","email":"","affiliations":[{"id":37245,"text":"University of New Orleans","active":true,"usgs":false}],"preferred":false,"id":802102,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215413,"text":"70215413 - 2019 - A Generalized Additive Model approach to evaluating water quality: Chesapeake Bay Case Study","interactions":[],"lastModifiedDate":"2020-10-20T13:24:52.488251","indexId":"70215413","displayToPublicDate":"2019-10-19T14:01:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"A Generalized Additive Model approach to evaluating water quality: Chesapeake Bay Case Study","docAbstract":"Nutrient-reduction efforts have been undertaken in recent decades to mitigate the impacts of eutrophication in coastal and estuarine systems worldwide. To track progress in response to one of these efforts we use Generalized Additive Models (GAMs) to evaluate a diverse suite of water quality constituents over a 32-year period in the Chesapeake Bay, an estuary on the east coast of the United States. Model development included selecting a GAM structure to describe nonlinear seasonally-varying changes over time, incorporating hydrologic variability via either river flow or salinity, and using interventions to model method or laboratory changes suspected to impact data. This approach, transferable to other systems, allows for evaluation of water quality data in a statistically rigorous way, while being suitable for application to many sites and variables. This enables consistent generation of annual updates, while providing a tool for developing insights to a range of management- and research-focused questions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2019.03.027","usgsCitation":"Murphy, R., Perry, E., Harcum, J., and Keisman, J.L., 2019, A Generalized Additive Model approach to evaluating water quality: Chesapeake Bay Case Study: Environmental Modelling & Software, v. 118, 13 p., https://doi.org/10.1016/j.envsoft.2019.03.027.","productDescription":"13 p.","ipdsId":"IP-105288","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":379527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.40966796875,\n 36.756490329505176\n ],\n [\n -75.5419921875,\n 36.756490329505176\n ],\n [\n -75.5419921875,\n 39.57182223734374\n ],\n [\n -77.40966796875,\n 39.57182223734374\n ],\n [\n -77.40966796875,\n 36.756490329505176\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"118","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Rebecca 0000-0003-3391-1823","orcid":"https://orcid.org/0000-0003-3391-1823","contributorId":199777,"corporation":false,"usgs":false,"family":"Murphy","given":"Rebecca","email":"","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":true,"id":802095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Elgin","contributorId":243340,"corporation":false,"usgs":false,"family":"Perry","given":"Elgin","affiliations":[{"id":48694,"text":"Statistics Consultant","active":true,"usgs":false}],"preferred":false,"id":802096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harcum, Jon","contributorId":243341,"corporation":false,"usgs":false,"family":"Harcum","given":"Jon","email":"","affiliations":[{"id":48695,"text":"Tetra Tech, Inc.","active":true,"usgs":false}],"preferred":false,"id":802097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keisman, Jennifer L. 0000-0001-6808-9193 jkeisman@usgs.gov","orcid":"https://orcid.org/0000-0001-6808-9193","contributorId":198107,"corporation":false,"usgs":true,"family":"Keisman","given":"Jennifer","email":"jkeisman@usgs.gov","middleInitial":"L.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":802098,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215412,"text":"70215412 - 2019 - Where was the 31 October 1895, Charleston, Missouri Earthquake?","interactions":[],"lastModifiedDate":"2020-10-20T13:27:29.499153","indexId":"70215412","displayToPublicDate":"2019-10-19T13:51:31","publicationYear":"2019","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":"Where was the 31 October 1895, Charleston, Missouri Earthquake?","docAbstract":"

We revisit the magnitude and location of the 31 October 1895 Charleston, Missouri earthquake, which is widely regarded to be the last MW6 or greater earthquake in the central United States. Although a recent study (Bakun et al., 2003) concluded that this earthquake was located in southern Illinois, over 100 km north of the traditionally inferred location near Charleston, Missouri, our analysis of exhaustively compiled macroseismic data supports the traditionally inferred location, with a preferred magnitude of MW ≈ 5.8, and preferred range of 5.4 to 6.1. Our preferred magnitude is derived from comparisons with intensity distributions from the 1925 MW = 6.2 Charlevoix, the 1944 MW = 5.8 Massena, and the 1968 MW = 5.3 southern Illinois earthquakes, which we also revisited in this study. Based on the distribution of liquefaction, reports of damage, and early aftershocks, we also explore possible rupture scenarios for the 1895 earthquake. Our preferred scenario involves unilateral rupture to the northeast on a (reactivated) northeast-striking fault (or faults) coinciding with structures associated with the western limb of the Reelfoot Rift, with an epicenter south-southeast of Charleston, Missouri. Our results support the conclusion that, within the Reelfoot Rift, elevated seismic hazard is not restricted to the New Madrid Seismic Zone (NMSZ) as conventionally defined but continues into the Charleston region in southeastern Missouri where faults associated with the western edge of the Reelfoot Rift appear favorably oriented for failure in the current stress regime.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120180328","usgsCitation":"Martin, S.S., and Hough, S.E., 2019, Where was the 31 October 1895, Charleston, Missouri Earthquake?: Bulletin of the Seismological Society of America, v. 109, no. 4, p. 1479-1497, https://doi.org/10.1785/0120180328.","productDescription":"19 p.","startPage":"1479","endPage":"1497","ipdsId":"IP-107007","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":379526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Charleston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.637451171875,\n 36.45884507478879\n ],\n [\n -89.07714843749999,\n 36.45884507478879\n ],\n [\n -89.07714843749999,\n 37.142803443716836\n ],\n [\n -89.637451171875,\n 37.142803443716836\n ],\n [\n -89.637451171875,\n 36.45884507478879\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"109","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-05-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Martin, Stacey S.","contributorId":187758,"corporation":false,"usgs":false,"family":"Martin","given":"Stacey","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":802093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":802094,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70215411,"text":"70215411 - 2019 - Dextral, normal, and sinistral faulting across the eastern California shear zone-Mina deflection transition, California-Nevada","interactions":[],"lastModifiedDate":"2020-10-20T13:30:40.254733","indexId":"70215411","displayToPublicDate":"2019-10-19T13:35:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Dextral, normal, and sinistral faulting across the eastern California shear zone-Mina deflection transition, California-Nevada","docAbstract":"

Strike-slip faults commonly include extensional and contractional bends and stepovers, whereas rotational stepovers are less common. The Volcanic Tableland, Black Mountain, and River Spring areas (California and Nevada, USA) (hereafter referred to as the VBR region) straddle the transition from the dominantly NW-striking dextral faults that define the northwestern part of the eastern California shear zone into a rotational stepover characterized by dominantly NE-striking sinistral faults that define the southwestern Mina deflection. New detailed geologic mapping, structural studies, and 40Ar/39Ar geochronology across the VBR region allow us to calculate Pliocene to Pleistocene fault slip rates and test predictions for the kinematics of fault slip transfer into this rotational stepover. In the VBR, Mesozoic basement is nonconformably overlain by a Miocene sequence of rhyolite, dacite, and andesite volcanic rocks that yield 40Ar/39Ar ages between 22.878 ± 0.051 Ma and 11.399 ± 0.041 Ma. Miocene rocks are unconformably overlain by an extensive sequence of Pliocene basalt and andesite lava flows and cinder cones that yield 40Ar/39Ar ages between 3.606 ± 0.060 Ma and 2.996 ± 0.027 Ma. The Pliocene sequence is, in turn, unconformably overlain by Quaternary tuffs and sedimentary rocks. This sequence of rocks is cut by NS- to NW-striking normal faults across the Volcanic Tableland that transition northward into NS-striking normal faults across the Black Mountain area and that, in turn, transition northward into NW-striking dextral and NE-striking sinistral faults in the River Spring area. A range of geologic markers were used to measure offset across the faults in the VBR, and combined with the age of the markers, yield minimum ∼EW-extension rates of ∼0.5 mm/yr across the Volcanic Tableland and Black Mountain regions, and minimum NW-dextral slip and NE-sinistral slip rates of ∼0.7 and ∼0.3 mm/yr, respectively, across the River Spring region. In the River Spring area, our preferred minimum dextral slip and sinistral slip rates are 0.8–0.9 mm/yr and 0.7–0.9 mm/yr, respectively. We propose three kinematic fault slip models, two irrotational and one rotational, whereby the VBR region transfers a portion of dextral Owens Valley fault slip northwestward into the Mina deflection. In irrotational model 1, Owens Valley fault slip is partitioned into two components, one northeastward onto the White Mountain fault zone and one northwestward into the Volcanic Tableland. Slip from the two zones is then transferred northward into the southwestern Mina deflection. In irrotational model 2, Owens Valley fault slip is partitioned into three components, with the third component partitioned west-northwest onto the Sierra Nevada frontal fault zone. In the rotational model, predicted sinistral slip rates across the southwestern Mina deflection are at least 115% greater than our observed minimum slip rates, implying our minimum observed rates underestimate true sinistral slip rates. A comparison of summed geologic fault slip rates, parallel to motion of the Sierra Nevada block relative to the central Great Basin, from the Sierra Nevada northeastward across the VBR region and into western Nevada are the same as geodetic rates, if our assumptions about the geologic slip rate across the dextral White Mountain fault zone is correct.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01636.1","usgsCitation":"DeLano, K., Lee, J., Roper, R., and Calvert, A.T., 2019, Dextral, normal, and sinistral faulting across the eastern California shear zone-Mina deflection transition, California-Nevada: Geosphere, v. 15, no. 4, p. 1206-1239, https://doi.org/10.1130/GES01636.1.","productDescription":"34 p.","startPage":"1206","endPage":"1239","ipdsId":"IP-097991","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":459455,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01636.1","text":"Publisher Index Page"},{"id":379525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Eastern California shear 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\"}}]}","volume":"15","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-06-24","publicationStatus":"PW","contributors":{"authors":[{"text":"DeLano, Kevin","contributorId":243338,"corporation":false,"usgs":false,"family":"DeLano","given":"Kevin","email":"","affiliations":[{"id":48692,"text":"CWU student, now at California State Water Resources","active":true,"usgs":false}],"preferred":false,"id":802089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Jeffrey","contributorId":193437,"corporation":false,"usgs":false,"family":"Lee","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":802090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roper, Rachelle","contributorId":243339,"corporation":false,"usgs":false,"family":"Roper","given":"Rachelle","email":"","affiliations":[{"id":48693,"text":"Central Washington University student","active":true,"usgs":false}],"preferred":false,"id":802091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":802092,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215420,"text":"70215420 - 2019 - A new set of basaltic tephras from southeastern Alaska represent key stratigraphic markers for the late Pleistocene","interactions":[],"lastModifiedDate":"2020-10-19T18:27:55.952556","indexId":"70215420","displayToPublicDate":"2019-10-19T13:23:14","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"A new set of basaltic tephras from southeastern Alaska represent key stratigraphic markers for the late Pleistocene","docAbstract":"An 8-cm-thick black basaltic tephra with nine discrete normally graded beds is present in cores from a lake on Baker Island in southeastern Alaska. The estimated age of the tephra is 13,492 ± 237 cal yr BP. Although similar in age to the MEd tephra from the adjacent Mt. Edgecumbe Volcanic Field, this tephra is geochemically distinct. Black basaltic tephras recovered from two additional sites in southeastern Alaska, Heceta Island and the Gulf of Esquibel, are also geochemically distinct from the MEd tephra. The age of the tephra from Heceta Island is 14,609 ± 343 cal yr BP. Whereas the tephras recovered from Baker Island/Heceta Island/Gulf of Esquibel are geochemically distinct from each other, similarities in the ages of these tephras and the MEd tephra suggest a shared eruptive trigger, possibly crustal unloading caused by retreat of the Cordilleran Ice Sheet. The submerged Addington Volcanic Field on the continental shelf, which may have been subaerially exposed during the late Pleistocene, is a possible source for the southeastern Alaska tephras","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2018.154","usgsCitation":"Wilcox, P.S., Addison, J.A., Fowell, S.J., Baichtal, J., Severin, K., and Mann, D.H., 2019, A new set of basaltic tephras from southeastern Alaska represent key stratigraphic markers for the late Pleistocene: Quaternary Research, v. 92, no. 1, p. 246-256, https://doi.org/10.1017/qua.2018.154.","productDescription":"11 p.","startPage":"246","endPage":"256","ipdsId":"IP-102481","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":379524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Southeastern Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -136.40625,\n 54.87660665410869\n ],\n [\n -130.4736328125,\n 54.87660665410869\n ],\n [\n -130.4736328125,\n 57.75107598132104\n ],\n [\n -136.40625,\n 57.75107598132104\n ],\n [\n -136.40625,\n 54.87660665410869\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"92","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilcox, Paul S.","contributorId":243353,"corporation":false,"usgs":false,"family":"Wilcox","given":"Paul","email":"","middleInitial":"S.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":802125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Addison, Jason A. 0000-0003-2416-9743 jaddison@usgs.gov","orcid":"https://orcid.org/0000-0003-2416-9743","contributorId":4192,"corporation":false,"usgs":true,"family":"Addison","given":"Jason","email":"jaddison@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":802126,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fowell, Sarah J.","contributorId":243354,"corporation":false,"usgs":false,"family":"Fowell","given":"Sarah","email":"","middleInitial":"J.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":802127,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baichtal, James F.","contributorId":243355,"corporation":false,"usgs":false,"family":"Baichtal","given":"James F.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":802128,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Severin, Ken","contributorId":243356,"corporation":false,"usgs":false,"family":"Severin","given":"Ken","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":802129,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mann, Daniel H.","contributorId":193130,"corporation":false,"usgs":false,"family":"Mann","given":"Daniel","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":802130,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70215410,"text":"70215410 - 2019 - Geese mediate vegetation state changes with parallel effects on N cycling that leave nutritional legacies for offspring","interactions":[],"lastModifiedDate":"2020-10-20T13:48:08.938633","indexId":"70215410","displayToPublicDate":"2019-10-19T13:03:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Geese mediate vegetation state changes with parallel effects on N cycling that leave nutritional legacies for offspring","docAbstract":"

Along the coastal fringe of the Yukon–Kuskokwim River Delta in southwestern Alaska, geese maintain grazing lawns dominated by a rhizomatous sedge that, when ungrazed, transitions to a taller, less palatable growth form that is taxonomically described as a different species. Nutrients recycled in goose feces, in conjunction with grazing, are critical to the rapid, nutritious growth of grazing lawns, and selective foraging on lawns has positive life‐history consequences for goslings. To examine whether bidirectional vegetation shifts were accompanied by parallel changes in N cycling, we studied how 15N‐urea and 13C15N‐glycine were processed through soils and plants of native and recently reverted vegetation states. Biomass and plant 15N uptake from plots reverted to the tall growth form using exclosures and from those shifted to grazing lawns by experimental clipping and then goose grazing were identical to their native counterparts. Total recovery of 15N within the tall vegetation types was significantly greater than within grazing lawns, although when expressed on a per‐gram biomass basis, percentage of 15N recovery was significantly higher in grazing lawns compared with the tall vegetation state. Patterns of 13C enrichment in CO2 soil efflux showed rapid use of 13C‐glycine as a respiratory substrate within the first hour following injection, with both the timing and magnitude of efflux occurring at similar time points for all four vegetation types. However, higher soil respiration rates and a shorter half‐life for 13C‐glycine in soils from tall meadows resulted in a greater proportional loss of 13CO2 compared with grazing lawns. Despite daily‐to‐weekly tidal inundation, all of 15N from labeled substrates could be accounted for within 1 m of the injection grid from soils of both states after 30 d, with significant levels of 15N in soils and vegetation after one year. Geese have remarkably high fidelity to brood‐rearing areas, returning as adults to the same grazing lawns where they were raised as goslings. Our data suggest that the role fecal‐derived nutrients play in the positive feedback loop between geese and their food resources can provide a long‐term legacy that spans generations.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2850","usgsCitation":"Ruess, R.W., McFarland, J., Person, B.T., and Sedinger, J.S., 2019, Geese mediate vegetation state changes with parallel effects on N cycling that leave nutritional legacies for offspring: Ecosphere, v. 10, no. 8, e02850, 16 p., https://doi.org/10.1002/ecs2.2850.","productDescription":"e02850, 16 p.","ipdsId":"IP-107059","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":459459,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2850","text":"Publisher Index Page"},{"id":379523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon–Kuskokwim River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -166.31927490234372,\n 60.7672084234438\n ],\n [\n -163.85284423828125,\n 60.7672084234438\n ],\n [\n -163.85284423828125,\n 61.55280114177263\n ],\n [\n -166.31927490234372,\n 61.55280114177263\n ],\n [\n -166.31927490234372,\n 60.7672084234438\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"8","noUsgsAuthors":false,"publicationDate":"2019-08-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruess, Roger W.","contributorId":45483,"corporation":false,"usgs":false,"family":"Ruess","given":"Roger","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":802085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McFarland, Jack 0000-0001-9672-8597","orcid":"https://orcid.org/0000-0001-9672-8597","contributorId":214819,"corporation":false,"usgs":true,"family":"McFarland","given":"Jack","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":802086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Person, Brian T.","contributorId":107457,"corporation":false,"usgs":false,"family":"Person","given":"Brian","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":802088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sedinger, James S.","contributorId":213694,"corporation":false,"usgs":false,"family":"Sedinger","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":802087,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215409,"text":"70215409 - 2019 - Relevance of wind stress and wave-dependent ocean surface roughness on the generation of winter meteotsunamis in Northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2020-10-19T18:01:53.210147","indexId":"70215409","displayToPublicDate":"2019-10-19T12:45:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5979,"text":"Ocean Modeling","active":true,"publicationSubtype":{"id":10}},"title":"Relevance of wind stress and wave-dependent ocean surface roughness on the generation of winter meteotsunamis in Northern Gulf of Mexico","docAbstract":"Meteotsunamis associated with passing squall lines are often observed ahead of cold fronts during winter seasons in Northern Gulf of Mexico. These types of meteotsunamis occur simultaneously with wind speed variations (~5-20 m/s) and sea-level atmospheric pressure oscillations (~1-6 hPa) with periods between 2 hours to several minutes. In order to enhance understanding of meteotsunami generation and propagation mechanisms, a Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system is applied to one of the most intense winter meteotsunamis measured in Northern Gulf of Mexico in the last decade (2009-2018). The model verification with sea level and atmospheric observations show that the fully-coupled model is able to reproduce the timing and intensity of the 10-m wind and sea level atmospheric pressure fluctuations. The mean bias between observed and measured wind speeds and atmospheric pressure are 1.73 m/s and 0.63 hPa respectively. The maximum meteotsunami elevation and its timing are successfully captured by modeled (with a 7% underestimation of the maximum elevation). The relative effect of atmospheric pressure and wind stress divergence on meteotsunami generation is assessed with different numerical simulations. Results indicate that both wind stress and atmospheric pressure oscillations contributed to the generation of the meteotsunami. Wind stress was the dominant force in shallow waters (<15 m in this application), while the effects of atmospheric pressure disturbances dominated over areas with Froude number close to one (~40 m in this application). During the passage of the squall line, the sea surface became rougher in a sea state characterized by young and steep local ocean waves. Compared to a purely wind-speed-dependent roughness scheme, the application of a wave-dependent roughness parameterization improved in 37% modeled meteotsunami maximum elevation.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocemod.2019.101408","usgsCitation":"Shi, L., Olabarrieta, M., Valle-Levinson, A., and Warner, J., 2019, Relevance of wind stress and wave-dependent ocean surface roughness on the generation of winter meteotsunamis in Northern Gulf of Mexico: Ocean Modeling, v. 140, 101408, 15 p., https://doi.org/10.1016/j.ocemod.2019.101408.","productDescription":"101408, 15 p.","ipdsId":"IP-099874","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459460,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ocemod.2019.101408","text":"Publisher Index Page"},{"id":379522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.8671875,\n 27.352252938063845\n ],\n [\n -82.353515625,\n 27.352252938063845\n ],\n [\n -82.353515625,\n 30.92107637538488\n ],\n [\n -93.8671875,\n 30.92107637538488\n ],\n [\n -93.8671875,\n 27.352252938063845\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"140","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shi, Lijing","contributorId":192873,"corporation":false,"usgs":false,"family":"Shi","given":"Lijing","email":"","affiliations":[],"preferred":false,"id":802081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":211373,"corporation":false,"usgs":false,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":802082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valle-Levinson, Arnoldo","contributorId":243337,"corporation":false,"usgs":false,"family":"Valle-Levinson","given":"Arnoldo","email":"","affiliations":[{"id":48691,"text":"Civil and Coastal Engineering Department, ESSIE, University of Florida 365 Weil Hall, Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":802083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":802084,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215419,"text":"70215419 - 2019 - Ar-Ar age constraints on the timing of Havre Trough opening and magmatism","interactions":[],"lastModifiedDate":"2020-10-20T13:52:51.36972","indexId":"70215419","displayToPublicDate":"2019-10-19T12:26:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2869,"text":"New Zealand Journal of Geology and Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Ar-Ar age constraints on the timing of Havre Trough opening and magmatism","docAbstract":"

The age and style of opening of the Havre Trough back-arc system is uncertain due to a lack of geochronologic constraints for the region. 40Ar/39Ar dating of 19 volcanic rocks from across the southern Havre Trough and Kermadec Arc was conducted in three laboratories to provide age constraints on the system. The results are integrated and interpreted as suggesting that this subduction system is young (<2 Ma) and coeval with opening of the continental Taupo Volcanic Zone of New Zealand. Arc magmatism was broadly concurrent across the breadth of the Havre Trough.

","language":"English","publisher":"Royal Society of New Zealand","doi":"10.1080/00288306.2019.1602059","usgsCitation":"Wysoczanski, R., Leonard, G.S., Gill, J.F., Wright, I., Calvert, A.T., McIntosh, W., Jicha, B., Gamble, J.A., Timm, C., Handler, M., Drewes-Todd, E.K., and Zohrab, A., 2019, Ar-Ar age constraints on the timing of Havre Trough opening and magmatism: New Zealand Journal of Geology and Geophysics, v. 62, no. 3, p. 371-377, https://doi.org/10.1080/00288306.2019.1602059.","productDescription":"7 p.","startPage":"371","endPage":"377","ipdsId":"IP-106648","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":459463,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":379521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Kermadec Arc–Havre Trough","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 174.990234375,\n -37.99616267972812\n ],\n [\n 178.857421875,\n -37.99616267972812\n ],\n [\n 178.857421875,\n -34.59704151614416\n ],\n [\n 174.990234375,\n -34.59704151614416\n ],\n [\n 174.990234375,\n -37.99616267972812\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Wysoczanski, Richard","contributorId":243346,"corporation":false,"usgs":false,"family":"Wysoczanski","given":"Richard","email":"","affiliations":[{"id":27642,"text":"National Institute of Water and Atmospheric Research, New Zealand","active":true,"usgs":false}],"preferred":false,"id":802113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leonard, Graham S.","contributorId":127469,"corporation":false,"usgs":false,"family":"Leonard","given":"Graham","email":"","middleInitial":"S.","affiliations":[{"id":5111,"text":"GNS Science, New Zealand","active":true,"usgs":false}],"preferred":false,"id":802114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gill, James F.","contributorId":196664,"corporation":false,"usgs":false,"family":"Gill","given":"James","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":802115,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, Ian 0000-0002-6660-0493","orcid":"https://orcid.org/0000-0002-6660-0493","contributorId":243347,"corporation":false,"usgs":false,"family":"Wright","given":"Ian","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":802116,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":802117,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McIntosh, William","contributorId":179358,"corporation":false,"usgs":false,"family":"McIntosh","given":"William","affiliations":[],"preferred":false,"id":802118,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jicha, Brian","contributorId":213920,"corporation":false,"usgs":false,"family":"Jicha","given":"Brian","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":802119,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gamble, John A","contributorId":243348,"corporation":false,"usgs":false,"family":"Gamble","given":"John","email":"","middleInitial":"A","affiliations":[{"id":27874,"text":"Victoria University","active":true,"usgs":false}],"preferred":false,"id":802120,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Timm, Christian","contributorId":243349,"corporation":false,"usgs":false,"family":"Timm","given":"Christian","email":"","affiliations":[{"id":48696,"text":"GEOMAR","active":true,"usgs":false}],"preferred":false,"id":802121,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Handler, Monica","contributorId":243350,"corporation":false,"usgs":false,"family":"Handler","given":"Monica","email":"","affiliations":[{"id":27874,"text":"Victoria University","active":true,"usgs":false}],"preferred":false,"id":802122,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Drewes-Todd, Elizabeth Kathleen 0000-0003-0692-3714","orcid":"https://orcid.org/0000-0003-0692-3714","contributorId":243351,"corporation":false,"usgs":true,"family":"Drewes-Todd","given":"Elizabeth","email":"","middleInitial":"Kathleen","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":802123,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zohrab, Alex","contributorId":243352,"corporation":false,"usgs":false,"family":"Zohrab","given":"Alex","email":"","affiliations":[{"id":27874,"text":"Victoria University","active":true,"usgs":false}],"preferred":false,"id":802124,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70215423,"text":"70215423 - 2019 - Temporal relationship between the Lassen Volcanic Center and mafic regional volcanism","interactions":[],"lastModifiedDate":"2020-10-19T17:07:58.396075","indexId":"70215423","displayToPublicDate":"2019-10-19T12:00:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Temporal relationship between the Lassen Volcanic Center and mafic regional volcanism","docAbstract":"Monogenetic volcanoes, distributed over large areas, contribute to the growth of monogenetic volcanic fields (MVFs) over thousands to millions of years of activity. It is now accepted that MVFs are also temporally clustered. To reduce uncertainties inherent to this episodic character, it is critical to combine multi-disciplinary studies to improve our knowledge of the temporal evolution of MVFs. The Lassen region, in the southern Cascades, is investigated to compare timing of eruptions at distributed mafic, intermediate, and silicic monogenetic volcanoes considering a new set of 40Ar/39Ar and K-Ar ages, complementing published radiometric ages for the area. Activity over the past 3.5 Ma has been episodic, alternating periods of intense and reduced activity as observed at other MVFs. More specifically, periods of intense regional mafic activity have occurred simultaneously to eruptive sequences at the silicic Lassen Volcanic Center (LVC). The back-arc Caribou Volcanic Field (CVF, ~800 – 15 ka) and forearc volcanoes, active simultaneously with the LVC, are characterized by eruptive sequences that persisted for 20 – 40 kyr, with the most recent eruptions occurring during the last glacial episode. Crater Mountain, a relatively young (282 - 395 ka) shield volcano spatially close to the CVF, confirms the presence of localized higher fluxes of mantle-derived melts that persisted for hundreds of thousand years in the back-arc region. Over the past 3.5 Ma, many small magma batches erupted simultaneously in short-lived episodes within clusters distributed across the Lassen region, including the LVC.","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-019-1296-7","usgsCitation":"Germa, A., Perry, C., Quidelleur, X., Calvert, A.T., Clynne, M.A., Connor, C., Connor, L., Malservisi, R., and Charbonnier, S., 2019, Temporal relationship between the Lassen Volcanic Center and mafic regional volcanism: Bulletin of Volcanology, v. 81, 38, 17 p., https://doi.org/10.1007/s00445-019-1296-7.","productDescription":"38, 17 p.","ipdsId":"IP-104676","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":379520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Lassen Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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elevation data and imagery","docAbstract":"Salt marshes are valuable ecosystems that are vulnerable to lateral erosion, submergence, and internal disintegration due to sea-level rise, storms, and sediment deficits. Because many salt marshes are losing area in response to these factors, it is important to monitor their lateral extent at high resolution over multiple timescales. In this study we describe two methods to calculate the location of the salt marsh shoreline. The Marsh Edge from Elevation Data (MEED) method uses remotely sensed elevation data to calculate an objective proxy for the shoreline of a salt marsh. This proxy is the abrupt change in elevation that usually characterizes the seaward edge of a salt marsh, designated the “marsh scarp.” It is detected as the maximum slope along a cross-shore transect between Mean High Water and Mean Tide Level. The method was tested using lidar topobathymetric and photogrammetric elevation data from Massachusetts, USA. The other method to calculate the salt marsh shoreline is the Marsh Edge by Image Processing (MEIP) method which finds the unvegetated/vegetated line. This method applies image classification techniques to multispectral imagery and elevation datasets for edge detection. The method was tested using aerial imagery and coastal elevation data from the Plum Island Estuary in Massachusetts, USA. Both methods calculate a line that closely follows the edge of vegetation seen in imagery. The root-mean-square deviation between the two methods within the test area is 0.6 meter. The two methods were compared to each other using high resolution Unmanned Aircraft Systems (UAS) data and to a heads-up digitized shoreline. The root-mean-square deviation was 0.6 meters between the two methods and less than 0.43 meters from the digitized shoreline. MEIP method was also applied to a lower resolution dataset to investigate the effect of horizontal resolution on the results. Both methods provide an accurate, efficient, and objective way to track salt marsh shorelines with spatially intensive data over large spatial scales, which is necessary to evaluate geomorphic change and wetland vulnerability","language":"English","publisher":"MDPI AG","doi":"10.3390/rs11151795","usgsCitation":"Farris, A.S., Defne, Z., and Ganju, N., 2019, Identifying salt marsh shorelines from remotely sensed elevation data and imagery: Remote Sensing, v. 11, no. 15, 1795, 17 p., https://doi.org/10.3390/rs11151795.","productDescription":"1795, 17 p.","ipdsId":"IP-109869","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459466,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11151795","text":"Publisher Index Page"},{"id":379518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","city":"Buzzards Bay, Orleans, Quincy","otherGeospatial":"Broad Meadows Marsh, Brant Island Cove, Pleasant Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.092529296875,\n 42.21224516288584\n ],\n [\n -70.81787109374999,\n 42.21224516288584\n ],\n [\n -70.81787109374999,\n 42.391008609205045\n ],\n [\n -71.092529296875,\n 42.391008609205045\n ],\n [\n -71.092529296875,\n 42.21224516288584\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -69.98703002929688,\n 41.66367910784373\n ],\n [\n -69.89639282226562,\n 41.66367910784373\n ],\n [\n -69.89639282226562,\n 41.84501267270689\n ],\n [\n -69.98703002929688,\n 41.84501267270689\n ],\n [\n -69.98703002929688,\n 41.66367910784373\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.95245361328125,\n 41.59285100004952\n ],\n [\n -70.78765869140625,\n 41.59285100004952\n ],\n [\n -70.78765869140625,\n 41.68111756290652\n ],\n [\n -70.95245361328125,\n 41.68111756290652\n ],\n [\n -70.95245361328125,\n 41.59285100004952\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"15","noUsgsAuthors":false,"publicationDate":"2019-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Farris, Amy S. 0000-0002-4668-7261 afarris@usgs.gov","orcid":"https://orcid.org/0000-0002-4668-7261","contributorId":196866,"corporation":false,"usgs":true,"family":"Farris","given":"Amy","email":"afarris@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":802065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":802066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":802067,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}