The satellite‐derived Normalized Difference Vegetation Index (NDVI) is commonly used by researchers and managers to represent ungulate forage conditions in landscapes across the globe, despite limited information about how it compares to empirical measurements of forage quality and quantity. The application of NDVI as a forage metric is particularly appealing for studying migratory caribou (Rangifer tarandus) in remote Arctic ecosystems, where field assessments are logistically and financially prohibitive, and climate‐mediated changes in vegetation have been hypothesized to influence population declines. To determine the utility of NDVI for adequately representing caribou forage conditions, we compared NDVI derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery to empirical measures of caribou forage biomass, nitrogen, digestible nitrogen, and digestible energy within the summer range of the Central Arctic Caribou Herd on the North Slope of Alaska. Specifically, we determined the strength of forage–NDVI relationships at the start of the growing season and across the summer, assessed the efficacy of NDVI variables for modeling spatiotemporal variation in field measurements of different forage components, and used long‐term MODIS data to estimate temporal changes in forage between 2000 and 2016. We found that NDVI values were weakly correlated with caribou forage quality at the start of the growing season and throughout the summer. Although linear models of forage–NDVI relationships performed poorly, NDVI variables (NDVI and the number of days from when NDVI reached its maximum value) were useful for modeling spatiotemporal variation in empirical measurements of forage components across the growing season, but only when we incorporated nonlinear forage–NDVI relationships and other habitat covariates. Phenological advances in the date of peak NDVI were associated with significant changes in forage conditions, particularly nitrogen, which exhibited earlier seasonal declines. Using long‐term MODIS data, predicted values of forage nitrogen declined between 2000 and 2016, driven by exceedingly low values in 2014 and 2015. Given our results, we caution the application of NDVI as a general (linear) proxy of caribou forage conditions across the growing season, and encourage practitioners to use NDVI variables to model spatiotemporal variation in specific forage conditions from empirical field data, accounting for nonlinear forage–NDVI relationships.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2461","usgsCitation":"Johnson, H.E., Gustine, D., Golden, T.S., Adams, L.G., Parrett, L.S., Lenart, E.A., and Barboza, P.S., 2018, NDVI exhibits mixed success in predicting spatiotemporal variation in caribou summer forage quality and quantity: Ecosphere, v. 9, no. 10, p. 1-19, https://doi.org/10.1002/ecs2.2461.","productDescription":"e02461; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-096032","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468314,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2461","text":"Publisher Index Page"},{"id":358477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.062255859375,\n 68.50811862333941\n ],\n [\n -147.908935546875,\n 68.50811862333941\n ],\n [\n -147.908935546875,\n 70.53954317685509\n ],\n [\n -150.062255859375,\n 70.53954317685509\n ],\n [\n -150.062255859375,\n 68.50811862333941\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-03","publicationStatus":"PW","scienceBaseUri":"5bed4273e4b0b3fc5cf91c8a","contributors":{"authors":[{"text":"Johnson, Heather E. 0000-0001-5392-7676 hejohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5392-7676","contributorId":205919,"corporation":false,"usgs":true,"family":"Johnson","given":"Heather","email":"hejohnson@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":748651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gustine, David D.","contributorId":209728,"corporation":false,"usgs":false,"family":"Gustine","given":"David D.","affiliations":[{"id":37975,"text":"Grand Teton National Park","active":true,"usgs":false}],"preferred":false,"id":748652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Golden, Trevor S. 0000-0003-4138-9289","orcid":"https://orcid.org/0000-0003-4138-9289","contributorId":209729,"corporation":false,"usgs":true,"family":"Golden","given":"Trevor","email":"","middleInitial":"S.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":748653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Layne G. 0000-0001-6212-2856 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2856","contributorId":209730,"corporation":false,"usgs":true,"family":"Adams","given":"Layne","email":"ladams@usgs.gov","middleInitial":"G.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":748654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parrett, Lincoln S.","contributorId":209731,"corporation":false,"usgs":false,"family":"Parrett","given":"Lincoln","email":"","middleInitial":"S.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":748655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lenart, Elizabeth A.","contributorId":209732,"corporation":false,"usgs":false,"family":"Lenart","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":748656,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barboza, Perry S.","contributorId":36454,"corporation":false,"usgs":false,"family":"Barboza","given":"Perry","email":"","middleInitial":"S.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":748657,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70200420,"text":"70200420 - 2018 - Evaluation of biodiversity data portals based on requirement analysis","interactions":[],"lastModifiedDate":"2018-10-17T10:56:55","indexId":"70200420","displayToPublicDate":"2018-10-17T10:56:52","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1457,"text":"Ecological Informatics","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of biodiversity data portals based on requirement analysis","docAbstract":"In recent years, concern about the misuse of natural resources has been increasing. It is essential to know in detail the biodiversity of an ecosystem to understand and analyze the impact of human activities on nature, as well as to promote the economic growth of a country. To achieve these goals, public and private institutions are aggregating and sharing biological data around the world by means of biodiversity data portals. The main purpose of those portals is to provide a set of tools that help users and institutions catalog, analyze, and publish raw data about different species in a manner that is open and freely available to any interested party. Normally the process of choosing the best software solution is not straightforward. This paper proposes a methodology to evaluate a collection of data portals to establish a clear and consistent selection process that analyzes a collection of requirements and research purposes. The proposed approach is based on three strategies: the use of software engineering techniques to identify the desired group of features to be available in the data portal; the application of the Kano Satisfaction Model to score each requirement according to a preset weight of importance; and the use of tree-maps to visualize the requirements based on their implementation priority, to establish a portal deployment road-map. The proposed methodology is broadly applicable to portal analyses for many communities of practice.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2018.09.008","usgsCitation":"Pizzigatti Correa, P.L., de Moraes Batista, A.F., Lins da Silva, D., Soares Rodrigues, R., Frame, M., Morandini, M., Stanzani, S., and Correa, F., 2018, Evaluation of biodiversity data portals based on requirement analysis: Ecological Informatics, v. 48, p. 215-225, https://doi.org/10.1016/j.ecoinf.2018.09.008.","productDescription":"11 p.","startPage":"215","endPage":"225","ipdsId":"IP-090505","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":487865,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://dx.doi.org/10.1016/j.ecoinf.2018.09.008","text":"External Repository"},{"id":358475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a91ce4b034bf6a7e4fdf","contributors":{"authors":[{"text":"Pizzigatti Correa, Pedro Luiz","contributorId":209775,"corporation":false,"usgs":false,"family":"Pizzigatti Correa","given":"Pedro","email":"","middleInitial":"Luiz","affiliations":[],"preferred":false,"id":748797,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Moraes Batista, Andre Filipe","contributorId":209776,"corporation":false,"usgs":false,"family":"de Moraes Batista","given":"Andre","email":"","middleInitial":"Filipe","affiliations":[],"preferred":false,"id":748798,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lins da Silva, Daniel","contributorId":209777,"corporation":false,"usgs":false,"family":"Lins da Silva","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":748799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Soares Rodrigues, Ronaldo","contributorId":209778,"corporation":false,"usgs":false,"family":"Soares Rodrigues","given":"Ronaldo","email":"","affiliations":[],"preferred":false,"id":748800,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frame, Mike 0000-0001-9995-2172 mike_frame@usgs.gov","orcid":"https://orcid.org/0000-0001-9995-2172","contributorId":4541,"corporation":false,"usgs":true,"family":"Frame","given":"Mike","email":"mike_frame@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":748753,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morandini, Marcelo","contributorId":209779,"corporation":false,"usgs":false,"family":"Morandini","given":"Marcelo","email":"","affiliations":[],"preferred":false,"id":748801,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stanzani, Silvio","contributorId":209780,"corporation":false,"usgs":false,"family":"Stanzani","given":"Silvio","email":"","affiliations":[],"preferred":false,"id":748802,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Correa, Fernando","contributorId":209781,"corporation":false,"usgs":false,"family":"Correa","given":"Fernando","email":"","affiliations":[],"preferred":false,"id":748803,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70263619,"text":"70263619 - 2018 - Sources of long-range anthropogenic noise in southern California and implications for tectonic tremor detection","interactions":[],"lastModifiedDate":"2025-02-19T16:24:20.775288","indexId":"70263619","displayToPublicDate":"2018-10-16T10:19:47","publicationYear":"2018","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":"Sources of long-range anthropogenic noise in southern California and implications for tectonic tremor detection","docAbstract":"We study anthropogenic noise sources seen on seismic recordings along the central section of the San Jacinto fault near Anza, southern California. The strongest signals are caused by freight trains passing through the Coachella Valley north of Anza. Train‐induced transients are observed at distances of up to 50 km from the railway, with durations of up to 20 min, and spectra that are peaked between 3 and 5 Hz. Additionally, truck traffic through the Coachella Valley generates a sustained hum with a similar spectral signature as the train transients but with lower amplitude. We also find that wind turbine activity in northern Baja California introduces a seasonal modulation of 1– to 5‐Hz energy across the Anza network. We show that the observed train‐generated transients can be used to constrain shallow attenuation structure at Anza. Using the results from this study as well as available borehole data, we further evaluate the performance of approaches that have been used to detect nonvolcanic tremor at Anza. We conclude that signals previously identified as spontaneous tremor (Hutchison and Ghosh, 2017) were probably generated by other nontectonic sources such as trains.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120180130","usgsCitation":"Inbal, A., Cristea-Platon, T., Ampuero, J., Hillers, G., Agnew, D., and Hough, S.E., 2018, Sources of long-range anthropogenic noise in southern California and implications for tectonic tremor detection: Bulletin of the Seismological Society of America, v. 108, no. 6, p. 3511-3527, https://doi.org/10.1785/0120180130.","productDescription":"17 p.","startPage":"3511","endPage":"3527","ipdsId":"IP-101208","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":500031,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10138/307688","text":"External Repository"},{"id":482224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.875,\n 34\n ],\n [\n -116.875,\n 33.25\n ],\n [\n -116.2,\n 33.25\n ],\n [\n -116.2,\n 34\n ],\n [\n -116.875,\n 34\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"108","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Inbal, Asaf","contributorId":350975,"corporation":false,"usgs":false,"family":"Inbal","given":"Asaf","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":927588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cristea-Platon, Tudor","contributorId":350976,"corporation":false,"usgs":false,"family":"Cristea-Platon","given":"Tudor","affiliations":[{"id":47799,"text":"MIT","active":true,"usgs":false}],"preferred":false,"id":927589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ampuero, Jean-Paul","contributorId":141194,"corporation":false,"usgs":false,"family":"Ampuero","given":"Jean-Paul","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":927590,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hillers, Gregor","contributorId":236647,"corporation":false,"usgs":false,"family":"Hillers","given":"Gregor","email":"","affiliations":[{"id":47489,"text":"Institute of Seismology, University of Helsinki, Helsinki, Finland","active":true,"usgs":false}],"preferred":false,"id":927591,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Agnew, Duncan 0000-0002-2360-7783","orcid":"https://orcid.org/0000-0002-2360-7783","contributorId":178605,"corporation":false,"usgs":false,"family":"Agnew","given":"Duncan","email":"","affiliations":[],"preferred":false,"id":927592,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":927593,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263697,"text":"70263697 - 2018 - Ground motions from the 7 and 19 September 2017 Tehuantepec and Puebla‐Morelos, Mexico, earthquakes","interactions":[],"lastModifiedDate":"2025-02-20T16:19:00.670279","indexId":"70263697","displayToPublicDate":"2018-10-16T10:11:57","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Ground motions from the 7 and 19 September 2017 Tehuantepec and Puebla‐Morelos, Mexico, earthquakes","docAbstract":"The 2017 M 8.2 Tehuantepec and M 7.1 Puebla‐Morelos earthquakes were deep inslab normal‐faulting events that caused significant damage to several central‐to‐southern regions of Mexico. Inslab earthquakes are an important component of seismicity and seismic hazard in Mexico. Ground‐motion prediction equations (GMPEs) are an integral part of seismic hazard assessment as well as risk and rapid‐response products. This work examines the observed ground motions from these two events in comparison to the predicted median ground motions from four GMPEs. The residuals between the observed and modeled ground motions allow us to study regional differences in shaking, the effects of each earthquake, and basin effects in Mexico City, Puebla, and Oaxaca. We find that the ground motions from these two earthquakes are generally well modeled by the GMPEs. However, the Tehuantepec event shows larger than expected ground motions at greater distances and longer periods, which suggests a waveguide effect from the subduction zone geometry. Finally, Mexico City and the cities of Puebla and Oaxaca exhibit very large ground motions, indicative of well‐known site and basin effects that are much stronger than the basin terms included in some of the GMPEs. Simple and rapid ground‐motion parameter estimates that include site effects are key for hazard and real‐time risk assessments in regions such as Mexico, where the vast majority of the population lives in areas where the aforementioned effects are relevant. However, GMPEs based on site correction terms dependent on topographic slope proxies underestimate, at least in the three cities tackled in this work, the observed amplification. Therefore, there is a need to improve models of seismic amplification in basins that could be included in GMPEs.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120180108","usgsCitation":"Sahakian, V.J., Melgar Moctezuma, D., Quintanar, L., Ramirez-Guzman, L., Perez-Campos, X., and Baltay Sundstrom, A.S., 2018, Ground motions from the 7 and 19 September 2017 Tehuantepec and Puebla‐Morelos, Mexico, earthquakes: Bulletin of the Seismological Society of America, v. 108, no. 6, p. 3300-3312, https://doi.org/10.1785/0120180108.","productDescription":"13 p.","startPage":"3300","endPage":"3312","ipdsId":"IP-096930","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","otherGeospatial":"Puebla‐Morelos, Tehuantepec","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102,\n 21\n ],\n [\n -102,\n 15\n ],\n [\n -91.5,\n 15\n ],\n [\n -91.5,\n 21\n ],\n [\n -102,\n 21\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"108","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Sahakian, Valerie Jean 0000-0002-3278-4458","orcid":"https://orcid.org/0000-0002-3278-4458","contributorId":296738,"corporation":false,"usgs":true,"family":"Sahakian","given":"Valerie","email":"","middleInitial":"Jean","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Melgar Moctezuma, Diego","contributorId":351083,"corporation":false,"usgs":false,"family":"Melgar Moctezuma","given":"Diego","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":927871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quintanar, Luis","contributorId":208095,"corporation":false,"usgs":false,"family":"Quintanar","given":"Luis","email":"","affiliations":[{"id":37714,"text":"Instituto de Geofísica, Universidad Nacional Autónoma de México","active":true,"usgs":false}],"preferred":false,"id":927872,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ramirez-Guzman, Leonardo","contributorId":151026,"corporation":false,"usgs":false,"family":"Ramirez-Guzman","given":"Leonardo","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":927873,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Perez-Campos, Xyoli","contributorId":351084,"corporation":false,"usgs":false,"family":"Perez-Campos","given":"Xyoli","affiliations":[{"id":16152,"text":"UNAM","active":true,"usgs":false}],"preferred":false,"id":927874,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":927875,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70200376,"text":"70200376 - 2018 - Novel ecological and climatic conditions drive rapid adaptation in invasive Florida Burmese pythons","interactions":[],"lastModifiedDate":"2019-01-28T09:01:02","indexId":"70200376","displayToPublicDate":"2018-10-15T15:46:01","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Novel ecological and climatic conditions drive rapid adaptation in invasive Florida Burmese pythons","docAbstract":"Invasive species provide powerful in situ experimental systems for studying evolution in response to selective pressures in novel habitats. While research has shown that phenotypic evolution can occur rapidly in nature, few examples exist of genome‐wide adaptation on short ‘ecological’ timescales. Burmese pythons (Python molurus bivittatus) have become a successful and impactful invasive species in Florida over the last 30 years despite major freeze events that caused high python mortality. We sampled Florida Burmese pythons before and after a major freeze event in 2010 and found evidence for directional selection in genomic regions enriched for genes associated with thermosensation, behavior, and physiology. Several of these genes are linked to regenerative organ growth, an adaptive response that modulates organ size and function with feeding and fasting in pythons. Independent histological and functional genomic datasets provide additional layers of support for a contemporary shift in invasive Burmese python physiology. In the Florida population, a shift towards maintaining an active digestive system may be driven by the fitness benefits of maintaining higher metabolic rates and body temperature during freeze events. Our results suggest that a synergistic interaction between ecological and climatic selection pressures have driven adaptation in Florida Burmese pythons, demonstrating the often‐overlooked potential of rapid adaptation to influence the success of invasive species.
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S.","contributorId":209719,"corporation":false,"usgs":false,"family":"Young","given":"Acacia","email":"","middleInitial":"S.","affiliations":[{"id":37974,"text":"The University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":748621,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Andrew, Audra L.","contributorId":209720,"corporation":false,"usgs":false,"family":"Andrew","given":"Audra","email":"","middleInitial":"L.","affiliations":[{"id":37974,"text":"The University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":748622,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jezkova, Tereza","contributorId":209721,"corporation":false,"usgs":false,"family":"Jezkova","given":"Tereza","email":"","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":748623,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pasquesi, Giulia","contributorId":209724,"corporation":false,"usgs":false,"family":"Pasquesi","given":"Giulia","email":"","affiliations":[{"id":37974,"text":"The University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":748629,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hales, Nicole R.","contributorId":209725,"corporation":false,"usgs":false,"family":"Hales","given":"Nicole","email":"","middleInitial":"R.","affiliations":[{"id":37974,"text":"The University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":748630,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Walsh, Matthew R.","contributorId":209722,"corporation":false,"usgs":false,"family":"Walsh","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":37974,"text":"The University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":748624,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rochford, Michael R.","contributorId":200644,"corporation":false,"usgs":false,"family":"Rochford","given":"Michael","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":748625,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mazzotti, Frank J.","contributorId":12358,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12604,"text":"Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, 3205 College Avenue, University of Florida, Davie, FL 33314, USA","active":true,"usgs":false}],"preferred":false,"id":748626,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":748627,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hunter, Margaret 0000-0002-4760-9302 mhunter@usgs.gov","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":140627,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","email":"mhunter@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":748616,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Castoe, Todd A.","contributorId":209723,"corporation":false,"usgs":false,"family":"Castoe","given":"Todd","email":"","middleInitial":"A.","affiliations":[{"id":37974,"text":"The University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":748628,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70200366,"text":"70200366 - 2018 - Effects of persistent energy-related brine contamination on amphibian abundance in national wildlife refuge wetlands","interactions":[],"lastModifiedDate":"2018-10-15T15:33:10","indexId":"70200366","displayToPublicDate":"2018-10-15T15:32:56","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Effects of persistent energy-related brine contamination on amphibian abundance in national wildlife refuge wetlands","docAbstract":"To inform sustainable energy development, it is important to understand the ecological effects of historical and current production practices and the persistence of those effects. The Williston Basin is one of North America's largest oil production areas and overlaps the Prairie Pothole Region, an area densely populated with wetlands that provide important wildlife habitat. Although historical disposal practices that released chloride-rich waters (brines) produced during oil extraction into the environment are no longer used, brine spills still occur frequently. We sampled 33 wetlands for three amphibian species in Montana and North Dakota during 2015–2017, primarily on National Wildlife Refuges, and used N-mixture models to determine how abundance varied with evidence of brine contamination. To provide insight into effects of historical versus contemporary contamination, we also estimated the association of well density and age with water quality and amphibian abundance. Abundance of boreal chorus frog (Pseudacris maculata) larvae declined most rapidly in response to increased chloride (range: 0.04–17,500 mg/L), followed by the northern leopard frog (Lithobates [Rana] pipiens) and barred tiger salamander (Ambystoma mavortium). Water quality and population- and community-level abundance of amphibians were more strongly related to nearby wells (≤800 m) installed before 1982 than to wells installed since 1982. These results suggest historical brine management practices were the primary driver of contamination and reduced amphibian abundance in wetlands we sampled, reflecting multi-decadal ecological effects. These persistent effects also underscore the critical need for tools to restore landscapes affected by brine contamination.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.10.007","usgsCitation":"Hossack, B.R., Smalling, K., Anderson, C.W., Preston, T.M., Cozzarelli, I.M., and Honeycutt, R.K., 2018, Effects of persistent energy-related brine contamination on amphibian abundance in national wildlife refuge wetlands: Biological Conservation, v. 228, p. 36-43, https://doi.org/10.1016/j.biocon.2018.10.007.","productDescription":"8 p.","startPage":"36","endPage":"43","ipdsId":"IP-097267","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468320,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2018.10.007","text":"Publisher Index Page"},{"id":358389,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota, South Dakota","volume":"228","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a91ee4b034bf6a7e4ff3","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":748561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":204696,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748562,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":140160,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey","email":"chauncey@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Preston, Todd M. 0000-0002-8812-9233","orcid":"https://orcid.org/0000-0002-8812-9233","contributorId":204676,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","email":"","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":748564,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":748565,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Honeycutt, R. Ken 0000-0002-7157-7195 rhoneycutt@usgs.gov","orcid":"https://orcid.org/0000-0002-7157-7195","contributorId":156282,"corporation":false,"usgs":true,"family":"Honeycutt","given":"R.","email":"rhoneycutt@usgs.gov","middleInitial":"Ken","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":748566,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70200363,"text":"70200363 - 2018 - Cracking the code of biodiversity responses to past climate change","interactions":[],"lastModifiedDate":"2018-10-15T15:11:13","indexId":"70200363","displayToPublicDate":"2018-10-15T15:11:10","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3653,"text":"Trends in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Cracking the code of biodiversity responses to past climate change","docAbstract":"How individual species and entire ecosystems will respond to future climate change are among the most pressing questions facing ecologists. Past biodiversity dynamics recorded in the paleoecological archives show a broad array of responses, yet significant knowledge gaps remain. In particular, the relative roles of evolutionary adaptation, phenotypic plasticity, and dispersal in promoting survival during times of climate change have yet to be clarified. Investigating the paleo-archives offers great opportunities to understand biodiversity responses to future climate change. In this review we discuss the mechanisms by which biodiversity responds to environmental change, and identify gaps of knowledge on the role of range shifts and tolerance. We also outline approaches at the intersection of paleoecology, genomics, experiments, and predictive models that will elucidate the processes by which species have survived past climatic changes and enhance predictions of future changes in biological diversity.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.tree.2018.07.005","usgsCitation":"Nogues-Bravo, D., Rodriguez-Sanchez, F., Orsini, L., de Boer, E., Jansson, R., Morlon, H., Fordham, D.A., and Jackson, S., 2018, Cracking the code of biodiversity responses to past climate change: Trends in Ecology and Evolution, v. 33, no. 10, p. 765-776, https://doi.org/10.1016/j.tree.2018.07.005.","productDescription":"12 p.","startPage":"765","endPage":"776","ipdsId":"IP-094634","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":468321,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-02408166","text":"External Repository"},{"id":358385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a91ee4b034bf6a7e4ffa","contributors":{"authors":[{"text":"Nogues-Bravo, David","contributorId":209649,"corporation":false,"usgs":false,"family":"Nogues-Bravo","given":"David","email":"","affiliations":[{"id":12672,"text":"University of Copenhagen","active":true,"usgs":false}],"preferred":false,"id":748511,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rodriguez-Sanchez, Francisco","contributorId":209650,"corporation":false,"usgs":false,"family":"Rodriguez-Sanchez","given":"Francisco","email":"","affiliations":[{"id":37951,"text":"Estación Biológica de Doñana","active":true,"usgs":false}],"preferred":false,"id":748512,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orsini, Luisa","contributorId":209651,"corporation":false,"usgs":false,"family":"Orsini","given":"Luisa","email":"","affiliations":[{"id":7157,"text":"University of Birmingham","active":true,"usgs":false}],"preferred":false,"id":748513,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"de Boer, Erik","contributorId":209652,"corporation":false,"usgs":false,"family":"de Boer","given":"Erik","email":"","affiliations":[{"id":36885,"text":"Utrecht University","active":true,"usgs":false}],"preferred":false,"id":748514,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jansson, Roland","contributorId":209653,"corporation":false,"usgs":false,"family":"Jansson","given":"Roland","email":"","affiliations":[{"id":37952,"text":"Umeå University","active":true,"usgs":false}],"preferred":false,"id":748515,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morlon, Helene","contributorId":209654,"corporation":false,"usgs":false,"family":"Morlon","given":"Helene","email":"","affiliations":[{"id":37952,"text":"Umeå University","active":true,"usgs":false}],"preferred":false,"id":748516,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fordham, Damien A.","contributorId":209655,"corporation":false,"usgs":false,"family":"Fordham","given":"Damien","email":"","middleInitial":"A.","affiliations":[{"id":37953,"text":"The University of Adelaide","active":true,"usgs":false}],"preferred":false,"id":748517,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jackson, Stephen T. 0000-0002-1487-4652","orcid":"https://orcid.org/0000-0002-1487-4652","contributorId":209648,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen T.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":748510,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70198944,"text":"sir20185114 - 2018 - Flood-inundation maps for the South Platte River at Fort Morgan, Colorado, 2018","interactions":[],"lastModifiedDate":"2018-10-15T16:08:48","indexId":"sir20185114","displayToPublicDate":"2018-10-15T11:15:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5114","title":"Flood-inundation maps for the South Platte River at Fort Morgan, Colorado, 2018","docAbstract":"In 2017, the U.S. Geological Survey (USGS), in cooperation with the Colorado Water Conservation Board (CWCB), studied floods in the historic record to produce a library of flood-inundation maps for the South Platte River at Fort Morgan, Colorado. Digital flood-inundation maps for a 4.5-mile (7.2-kilometers) reach of the South Platte River at Fort Morgan from Morgan County Road 16 to Morgan County Road 20.5, were created. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey streamgage on the South Platte River at Fort Morgan (streamgage number 06759500).
Water-surface profiles were computed for the stream reach by means of a one-dimensional, step-backwater model. The September 15, 2013, and May 20, 2017, floods were used to calibrate the model, and the June 15, 2015, and May 29, 2017, floods were used to independently validate the model. Nine pressure transducers were deployed to record the stage at nine different locations along the reach and to document the floods of May 20 and 29, 2017, at the South Platte River at Fort Morgan streamgage.
The hydraulic model was then used to compute 16 water-surface profiles for flood stages at 1-foot (ft; 0.3-meter [m]) intervals referenced to the streamgage datum and ranging from 12 ft (3.66 m) or below bankfull to 27 ft (8.23 m), which is 1 ft (0.3 m) greater than the highest recorded water level (25.73 ft [7.84 m] on September 15, 2013) at the South Platte River at Fort Morgan streamgage during its period of record; the 2013 flood exceeds the major flood stage of 21.5 ft (6.55 m) by more than 4 ft (1.2 m), as defined by the National Weather Service.
The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.37-ft [0.11-m] vertical accuracy and 3.28-ft [1.00-m] horizontal resolution) to delineate the area flooded for stages ranging from 12 to 27 ft (3.66 to 8.23 m).
These flood-inundation maps, in conjunction with the real-time stage data from the USGS streamgage on the South Platte River at Fort Morgan, are intended to help guide the general public in taking individual safety precautions and provide emergency management personnel with a tool to efficiently manage emergency flood operations and post flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185114","collaboration":"Prepared in cooperation with the Colorado Water Conservation Board","usgsCitation":"Kohn, M.S., and Patton, T.T., 2018, Flood-inundation maps for the South Platte River at Fort Morgan, Colorado, 2018: U.S. Geological Survey Scientific Investigations Report 2018–5114, 14 p., https://doi.org/10.3133/sir20185114.","productDescription":"Report: vi, 14 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-097350","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":358286,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YA4STZ","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial Data and Surface-Water Model Archive for a Flood-Inundation Mapping Study of the South Platte River at Fort Morgan, Colorado, 2018"},{"id":358285,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7XG9PN1","text":"USGS data release","description":"USGS data release","linkHelpText":"Cross-Section Data and Pressure Transducer Location of the South Platte River near Fort Morgan, Colorado, 2017"},{"id":358279,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5114/sir20185114.pdf","text":"Report","size":"11.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5114"},{"id":358287,"rank":5,"type":{"id":18,"text":"Project Site"},"url":"https://water.usgs.gov/osw/flood_inundation/","text":"Flood Inundation Mapper —","linkHelpText":"USGS Flood Inundation Mapping (FIM) Program"},{"id":358278,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5114/coverthb.jpg"}],"country":"United States","state":"Colorado","city":"Fort Morgan","otherGeospatial":"South Platte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.851040005684,\n 40.244026096225\n ],\n [\n -103.760746121407,\n 40.244026096225\n ],\n [\n -103.760746121407,\n 40.2918348221745\n ],\n [\n -103.851040005684,\n 40.2918348221745\n ],\n [\n -103.851040005684,\n 40.244026096225\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
Several of the impact craters on Ceres have sets of fractures on their floors. These fractures appear similar to those found within a class of lunar craters referred to as floor-fractured craters (FFCs). We have cataloged the Ceres FFCs according to the classification scheme designed for the Moon. An analysis of the depth to diameter ratio for Ceres craters shows that, like lunar FFCs, the Ceres FFCs are anomalously shallow. Large (>50 km) Ceres FFCs are most consistent with Class 1 lunar FFCs, while smaller craters on Ceres are more consistent with Class 4 lunar FFCs. This suggests that Ceres FFCs may similarly be undergoing fracturing due to the intrusion of a low-density material below the craters. While on the Moon (and Mars) the intrusive material is hypothesized to be silicate magma, cryomagmatic intrusions are more likely responsible for the formation of the Ceres FFCs. However, new models suggest that at least some of the FFC fractures may have formed due to the solid-state flow of a low-viscosity and low-density material into the crater wall.
The 29 June 1925 Santa Barbara earthquake is among the largest 20th century earthquakes in southern California. The earthquake also predated the installation of strong motion and local monitoring instruments in southern California; some instrumental data are, however, available from long-period instruments at regional and teleseismic distances. The current catalog moment magnitude is MW 6.8. Initial intensity magnitudes (MI) estimated from original Coast and Geodetic Survey intensity assignments were lower (MI 6.3). In this study we assign modified Mercalli intensity values at 239 locations, including 144 specific locations within the city of Santa Barbara for which detailed damage information is available. Comparing the reinterpreted intensities with Did You Feel it? intensities for recent events in California, we estimate MW = 6.5, with a plausible range of 6.3–6.6. We further consider reported instrumental amplitudes to estimate an instrumental moment magnitude of MW = 6.6 ± 0.5. Our preferred final estimate is MW 6.5. Based on available constraints including aftershock locations inferred from data recorded on portable instruments, we propose that the earthquake nucleated east of the city of Santa Barbara, closer to the coast than previously estimated, and ruptured unilaterally ~30 km to the west, possibly along the south-dipping Mesa-Rincon Creek, and the More Ranch fault systems. Contrary to suggestions made in earlier studies (e.g. Willis, 1925a), relatively high intensities ~50 km west of Santa Barbara can then be explained by directivity rather than involvement of the Santa Ynez fault. Finally, we discuss the possibility that the earthquake was triggered by the larger MW = 6.6 Clarkston, Montana earthquake the previous day or induced by oil production in the Summerland oil field.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.tecto.2018.09.012","usgsCitation":"Hough, S.E., and Martin, S.S., 2018, A proposed rupture scenario for the 1925 Mw 6.5 Santa Barbara, California, earthquake: Tectonophysics, v. 747-748, p. 211-224, https://doi.org/10.1016/j.tecto.2018.09.012.","productDescription":"14 p.","startPage":"211","endPage":"224","ipdsId":"IP-096386","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Santa Barabara","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.9,\n 34.65\n ],\n [\n -119.9,\n 34.25\n ],\n [\n -119.45,\n 34.25\n ],\n [\n -119.45,\n 34.65\n ],\n [\n -119.9,\n 34.65\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"747-748","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":927596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Stacey S.","contributorId":140021,"corporation":false,"usgs":false,"family":"Martin","given":"Stacey","email":"","middleInitial":"S.","affiliations":[{"id":5110,"text":"Earth Observatory of Singapore, Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":927597,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70200142,"text":"70200142 - 2018 - Estimating the pressure-limited CO2 injection and storage capacity of the United States saline formations: Effect of the presence of hydrocarbon reservoirs","interactions":[],"lastModifiedDate":"2019-02-07T12:13:09","indexId":"70200142","displayToPublicDate":"2018-10-12T14:00:28","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2049,"text":"International Journal of Greenhouse Gas Control","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Estimating the pressure-limited CO2 injection and storage capacity of the United States saline formations: Effect of the presence of hydrocarbon reservoirs","title":"Estimating the pressure-limited CO2 injection and storage capacity of the United States saline formations: Effect of the presence of hydrocarbon reservoirs","docAbstract":"The U.S. Geological Survey (USGS) national assessment of carbon dioxide (CO2) storage capacity evaluated 192 saline Storage Assessment Units (SAUs) in 33 U.S. onshore sedimentary basins that may be utilized for CO2 storage (see USGS Circular 1386). Similar to many other available models, volumetric analysis was utilized to estimate the initial CO2injection and storage capacity of these SAUs based on aquifer characteristics and buoyant and residual trapping. The factor being almost always overlooked in most CO2 storage capacity models is that many of the evaluated SAUs contain large numbers of both conventional and unconventional discovered and undiscovered oil and gas reservoirs. The hydrocarbon production and pressure distribution of the resident oil and gas reservoirs may be negatively influenced by the propagated CO2 plume and pressure front resulting from a CO2 injection and storage operation in the surrounding SAU.
To have a more realistic and accurate estimation of CO2 injection and storage capacity in saline formations, a model was previously developed that considers the CO2 injectivity of a given formation, underground pressure build-up limitations imposed by the rock fracturing pressure and the presence of hydrocarbon reservoirs within these aquifers. The developed method estimates the pre–brine extraction, pressure-limited CO2 injection and storage capacity of a saline formation by applying 3D numerical simulation only on the effective injection area (Aeff) surrounding each CO2 injection well utilizing TOUGH2-ECO2N simulation software.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijggc.2018.09.011","usgsCitation":"Jahediesfanjani, H., Warwick, P., and Anderson, S.T., 2018, Estimating the pressure-limited CO2 injection and storage capacity of the United States saline formations: Effect of the presence of hydrocarbon reservoirs: International Journal of Greenhouse Gas Control, v. 79, p. 14-24, https://doi.org/10.1016/j.ijggc.2018.09.011.","productDescription":"11 p.","startPage":"14","endPage":"24","ipdsId":"IP-093110","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":468324,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijggc.2018.09.011","text":"Publisher Index Page"},{"id":358344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Sligo and Hosston Formations","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.82177734375,\n 26.941659545381516\n ],\n [\n -86.220703125,\n 26.941659545381516\n ],\n [\n -86.220703125,\n 34.52466147177172\n ],\n [\n -99.82177734375,\n 34.52466147177172\n ],\n [\n -99.82177734375,\n 26.941659545381516\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a920e4b034bf6a7e500b","contributors":{"authors":[{"text":"Jahediesfanjani, Hossein 0000-0001-6281-5166","orcid":"https://orcid.org/0000-0001-6281-5166","contributorId":201000,"corporation":false,"usgs":false,"family":"Jahediesfanjani","given":"Hossein","affiliations":[],"preferred":false,"id":748291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warwick, Peter D. 0000-0002-3152-7783","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":207248,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":748290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":748292,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200134,"text":"ofr20181095 - 2018 - Modeling resource selection of bobcats (Lynx rufus) and vertebrate species distributions in Orange County, southern California","interactions":[],"lastModifiedDate":"2018-10-12T11:14:31","indexId":"ofr20181095","displayToPublicDate":"2018-10-11T11:44:52","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1095","displayTitle":"Modeling resource selection of bobcats (Lynx rufus) and vertebrate species distributions in Orange County, southern California","title":"Modeling resource selection of bobcats (Lynx rufus) and vertebrate species distributions in Orange County, southern California","docAbstract":"For nature reserves in urban settings, wildlife and wildlife habitats may be affected by recreational activities and intensive, adjacent development. Sustaining biodiversity in such reserves is a challenge for land and natural resource managers, but identification of core areas and key resources for wildlife species may help in planning for current and emerging threats. To help identify core areas and resources, we conducted spatial analyses and predictive modeling of vertebrate distributions for a network of nature reserves in densely populated Orange County, California. We primarily focused on bobcats (Lynx rufus), a species with a strong association with natural habitat. Bobcat space use has been correlated with broad, simple land-use categories, but relatively little is known about the influence of greater landscape complexity on habitat suitability for bobcats. To examine habitat selection by bobcats, we developed spatial data layers representing environmental factors that might influence this species, and we used previously collected Global Positioning System tracking data for 30 male and 21 female bobcats to indicate bobcat response to complex landscape factors. We examined these inputs using Resource Selection Function (RSF) modeling and developed spatially explicit models of the probability of bobcat use (selection or avoidance) of landscape characteristics. RSF models highlighted the general importance of reserve habitat for bobcats, but suggested that female bobcats were more dependent that male bobcats on habitat within designated reserves. Male bobcats, which range more widely than female bobcats, were associated with undeveloped areas both within and outside reserves. Small areas were present outside reserves that seemed to provide additional suitable habitat or movement areas for bobcats, potentially through restoration, connectivity, or reduced edge effects.
Although bobcat RSFs suggested areas of high value to this species and potentially other species, taxa can differ greatly in their resource-selection and spatial requirements. Thus, for several species of reptiles, amphibians, and birds, we adapted species distribution models based on occurrence data to examine the response of other vertebrates to the landscape. To identify potential High-Value Areas (HVAs) for single or multiple species, we then developed a step-wise filtering process that can be applied to a series of spatial data layers. We provide examples of alternative decision models for HVAs that capture different elements of biodiversity and a range of management considerations. As landscape and management challenges change, these spatial layers and decision rules can be adjusted based on new information. Our approach thus establishes a general framework for identifying high-value habitat that can be used for current management decisions and refined in the future, depending on management interests and goals and the availability of suitable quality data or adequate surrogate information.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181095","collaboration":"Prepared in cooperation with Natural Communities Coalition","usgsCitation":"Boydston, E.E., and Tracey, J.A., 2018, Modeling resource selection of bobcats (Lynx rufus) and vertebrate species distributions in Orange County, southern California, with a section on Modeling for reptile, amphibian, and bird distributions by Tracey, J.A., Preston, K.L., Rochester, C.J., Boydston, E.E., and Fisher, R.N.: U.S. Geological Survey Open-File Report 2018–1095, 65 p., https://doi.org/10.3133/ofr20181095.","productDescription":"vi, 65 p.","onlineOnly":"Y","ipdsId":"IP-086435","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":358295,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1095/coverthb.jpg"},{"id":358296,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1095/ofr20181095.pdf","text":"Report","size":"13.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1095"}],"country":"United States","state":"California","county":"Orange County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.95,\n 33.5\n ],\n [\n -117.5667,\n 33.5\n ],\n [\n -117.5667,\n 34\n ],\n [\n -117.95,\n 34\n ],\n [\n -117.95,\n 33.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Mineral criticality is a subjective concept that has evolved throughout history. An abundance of literature on this topic has been published over the last decade, encompassing a variety of criteria and methodologies. To our knowledge, this work is the first large-scale effort to organize and analyze recent comprehensive criticality studies in order to determine if a consensus exists within the global community as to which elements are critical. Here, we set aside methodological differences and analyze the results of 32 comprehensive nonfuel mineral criticality studies that evaluate at least 10 elements. Of the 56 elements or elemental groups evaluated, the three most commonly identified as critical in these studies are the rare-earth elements (REE), the platinum-group metals (PGM), and indium. Most of the studies also identify tungsten, germanium, cobalt, niobium, tantalum, gallium, and antimonyas critical. These results are consistent with the 11 most recent studies, published post-2014, which also identify bismuth as critical. Furthermore, the same elements identified in the complete dataset, except antimony, were designated as critical when normalized by geographic region. Magnesium was also deemed critical. Elements may be identified consistently as critical for several reasons; similarities in methodologies, which embody evolving perceptions of risk, or changing national and institutional priorities. This work compiles a large number of recent criticality studies in an effort to define a consensus of currently critical materials, essentially defining the modern criticality paradigm, which is valuable when interpreting an individual perspective in more global context.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.resourpol.2018.06.015","usgsCitation":"Hayes, S.M., and McCullough, E.A., 2018, Critical minerals: A review of elemental trends in comprehensive criticality studies: Resources Policy, v. 59, p. 192-199, https://doi.org/10.1016/j.resourpol.2018.06.015.","productDescription":"8 p.","startPage":"192","endPage":"199","ipdsId":"IP-093413","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":468328,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.resourpol.2018.06.015","text":"Publisher Index Page"},{"id":358273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f72e4b0fc368eb53823","contributors":{"authors":[{"text":"Hayes, Sarah M. 0000-0001-5887-6492","orcid":"https://orcid.org/0000-0001-5887-6492","contributorId":208569,"corporation":false,"usgs":true,"family":"Hayes","given":"Sarah","email":"","middleInitial":"M.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":747732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCullough, Erin A. 0000-0002-9072-7021 emccullough@usgs.gov","orcid":"https://orcid.org/0000-0002-9072-7021","contributorId":196629,"corporation":false,"usgs":true,"family":"McCullough","given":"Erin","email":"emccullough@usgs.gov","middleInitial":"A.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":747733,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70199918,"text":"ds1095 - 2018 - Nearshore single-beam bathymetry data collected in 2015, Dauphin Island, Alabama","interactions":[],"lastModifiedDate":"2018-10-11T12:00:22","indexId":"ds1095","displayToPublicDate":"2018-10-11T10:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1095","title":"Nearshore single-beam bathymetry data collected in 2015, Dauphin Island, Alabama","docAbstract":"Dauphin Island, Alabama, is a barrier island located in the northern Gulf of Mexico that supports local residences, tourism, commercial infrastructure, and historic Fort Gaines. During the past decade, Dauphin Island was affected by several major hurricanes—Hurricanes Ivan (2004), Katrina (2005), and Isaac (2012)—and storms, along with sea-level rise, continue to present a threat to island stability. State and Federal managers are using a scientific approach to identify, formulate, and implement a long-term plan to provide restoration options for Dauphin Island, thereby helping increase its resilience against future storms and sea-level rise. Island morphology, including current bathymetry and shoreline data, is one scientific domain being investigated in an effort to produce a comprehensive restoration plan funded by an interagency grant from the National Fish and Wildlife Foundation Gulf Environmental Benefit Fund.
In August 2015, the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), in cooperation with the U.S. Army Corps of Engineers at the U.S. Army Engineer Research and Development Center, Mobile District, and the State of Alabama, conducted bathymetric surveys of the nearshore waters surrounding Dauphin Island. This report provides a detailed methodology for the data acquisition and post-processing of 1,165-line kilometers (km) of single-beam bathymetry data collected under the USGS–SPCMSC Alabama Barrier Island Restoration Study. These data were acquired and processed under USGS field activity number 2015–326–FA. Data are provided in three datums: (1) the International Terrestrial Reference Frame of 2000, ellipsoid height (from –47.04 meters (m) to –29.36 m); (2) the North American Datum of 1983, CORS96 realization (NAD83 (CORS96)) horizontal, and the North American Vertical Datum 1988 GEOID12A vertical (from –0.24 m to –17.33 m); and (3) NAD83 (CORS96) horizontal, and mean lower low water vertical (from –0.12 m to –17.93 m). The x,y,z point datasets, trackline shapefiles, digital and handwritten Field Activity Collection Systems logs, one 50-m digital elevation model, and formal Federal Geographic Data Committee metadata are obtainable from the Data Downloads page or the associated USGS data release.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1095","usgsCitation":"DeWitt, N.T., Stalk, C.A., Flocks, J.G., Bernier, J.C., Kelso, K.W., Fredericks, J.J., and Tuten, T.M., 2018, Nearshore single-beam bathymetry data collected in 2015, Dauphin Island, Alabama: U.S. Geological Survey Data Series 1095, https://doi.org/10.3133/ds1095.","productDescription":"Report: HTML; Data release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-090788","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":358117,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1095/coverthb.jpg"},{"id":358118,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1095/index.html","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1095"},{"id":358119,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BZ648W","text":"USGS data release","description":"USGS data release","linkHelpText":"Single-beam bathymetry data collected in 2015 nearshore Dauphin Island, Alabama"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.38706970214844,\n 30.194992169502903\n ],\n [\n -88.05061340332031,\n 30.194992169502903\n ],\n [\n -88.05061340332031,\n 30.292274851024256\n ],\n [\n -88.38706970214844,\n 30.292274851024256\n ],\n [\n -88.38706970214844,\n 30.194992169502903\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th St. S.
St. Petersburg, FL 33701
This short course was prepared at the request of Servicio Geológico Colombiano (SGC) as a module for staff training. Prior to the short course, the SGC expressed interest in receiving training in (1) geochemistry and quality of coal; (2) geochemistry of trace elements in coal; (3) mercury and halogens in coal; (4) characterization and cycling of atmospheric mercury; (5) mercury, trace elements, and organic constituents in atmospheric fine particulate matter; (6) mercury in coal and the effect of coal quality on mercury emissions from combustion systems; (7) environmental and health effects related to coal use; and (8) related topics in coal combustion processes. A five-session short course was prepared that addressed all but the engineering aspects of coal use. In the sections that follow, topic overviews are given for the material that was presented. Brief descriptions of each slide are given in appendix 1, and the actual short course material, presented as a series of PowerPoint slides, is included in Portable Document Format (PDF) as appendix 2.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181145","collaboration":"Prepared in collaboration with Servicio Geológico Colombiano, Bogotá, Colombia","usgsCitation":"Kolker, A., 2018, Topics in coal geochemistry—Short course: U.S. Geological Survey Open-File Report 2018–1145, 31 p., https://doi.org/10.3133/ofr20181145.","productDescription":"Report: x, 31 p.; Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-087688","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":358209,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1145/ofr20181145_appendix2.pdf","text":"Appendix 2","size":"11.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1145 Appendix 2","linkHelpText":"Appendix 2. Short Course Slides"},{"id":358207,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1145/coverthb.jpg"},{"id":358208,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1145/ofr20181145.pdf","text":"Report","size":"365 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1145"}],"contact":"Eastern Energy Resources Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
956 National Center
Reston, VA 20192
https://energy.usgs.gov/
Video measurements of runup were collected at low tide along several profiles covering an alongshore distance of 500 m. The morphology displayed a complex shape with a shoreline sandwave in the lower beach face of about 250 m long mirrored in the inner sandbar. Wave conditions were stationary and moderate (offshore height of 2 m and peak period of nearly 13 s) but yet dissipative. Runup energy was dominated by infragravity frequencies. Alongshore variations in runup (by a factor up to 3) observed both in the incident and infragravity bands were much higher than reported previously (e.g., Guedes et al., 2012, https://doi.org/10.1016/j.csr.2012.08.022; Ruggiero et al., 2004, https://doi.org/10.1029/2003JC002160) while the alongshore variations in other environmental parameters (e.g., foreshore beach slope) appear to be much lower. Our data suggest that the beach morphology in the inner surf zone plays a crucial role by inducing rapid and significant modification in the incident wave pattern and the alongshore coherence length scales were consistent with the typical alongshore length scale of the morphology.
","language":"English","publisher":"AGU","doi":"10.1029/2018JC014109","usgsCitation":"Senechal, N., Coco, G., Plant, N.G., Bryan, K., Brown, J., and MacMahan, J., 2018, Field observations of alongshore runup variability under dissipative conditions in presence of a shoreline sandwave: Journal of Geophysical Research C: Oceans, v. 123, no. 9, p. 6800-6817, https://doi.org/10.1029/2018JC014109.","productDescription":"18 p.","startPage":"6800","endPage":"6817","ipdsId":"IP-101035","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468329,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jc014109","text":"Publisher Index Page"},{"id":358240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-22","publicationStatus":"PW","scienceBaseUri":"5bc02f74e4b0fc368eb5382b","contributors":{"authors":[{"text":"Senechal, Nadia","contributorId":208563,"corporation":false,"usgs":false,"family":"Senechal","given":"Nadia","email":"","affiliations":[],"preferred":false,"id":747702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coco, Giovanni","contributorId":84978,"corporation":false,"usgs":true,"family":"Coco","given":"Giovanni","affiliations":[],"preferred":false,"id":747703,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":747704,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bryan, Karin R.","contributorId":147360,"corporation":false,"usgs":false,"family":"Bryan","given":"Karin R.","affiliations":[{"id":12678,"text":"University of Waikato","active":true,"usgs":false}],"preferred":false,"id":747705,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Jennifer 0000-0003-3137-7073 jenniferbrown@usgs.gov","orcid":"https://orcid.org/0000-0003-3137-7073","contributorId":181793,"corporation":false,"usgs":true,"family":"Brown","given":"Jennifer","email":"jenniferbrown@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":747706,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"MacMahan, Jamie","contributorId":194053,"corporation":false,"usgs":false,"family":"MacMahan","given":"Jamie","affiliations":[],"preferred":false,"id":747707,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199956,"text":"70199956 - 2018 - Hydrodynamics of a tidally‐forced coral reef atoll","interactions":[],"lastModifiedDate":"2018-12-05T14:13:42","indexId":"70199956","displayToPublicDate":"2018-10-09T10:33:54","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Hydrodynamics of a tidally‐forced coral reef atoll","docAbstract":"The hydrodynamics of a tidally forced semi‐enclosed coral reef atoll (North Scott) at the edge of the continental shelf of northwestern Australia were investigated by combining field observations and numerical modeling. The observations revealed that the spring tidal range outside the atoll reaches 4 m, and as the water level drops below mean sea level, the reef rim surrounding the shallow (~10–15 m) lagoon becomes exposed. During this time, the lagoon can only exchange with the open ocean through two narrow channels, resulting in highly asymmetric water levels and velocities that were most pronounced during spring tide. On average, the ebb tide duration was ~2 hr longer than the flood, with rapid flood velocities in the channel reaching 2 m/s. We applied an unstructured grid model Delft3D‐Flexible Mesh to simulate the atoll hydrodynamics and were able to replicate the asymmetric water levels and complex velocities in the lagoon. The results revealed that at higher tidal stages, a dominant momentum balance exists between the pressure gradient (established by the propagation of the tide on the shelf) and the local flow acceleration of water throughout the interior of the atoll. At lower tidal stages, which coincided with a reversal of the offshore tidal pressure gradient, the lagoon became isolated from offshore dynamics and all momentum terms were negligible. This resulted in a tidally averaged residual westward flow within the lagoon that drove an asymmetric flushing pattern within the atoll, which we propose would be a common flushing mechanism within other tide‐dominated atolls worldwide.
","language":"English","publisher":"AGU","doi":"10.1029/2018JC013946","usgsCitation":"Green, R.H., Lowe, R.J., and Buckley, M.L., 2018, Hydrodynamics of a tidally‐forced coral reef atoll: Journal of Geophysical Research C: Oceans, v. 123, no. 10, p. 7084-7101, https://doi.org/10.1029/2018JC013946.","productDescription":"18 p.","startPage":"7084","endPage":"7101","ipdsId":"IP-095615","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468331,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jc013946","text":"Publisher Index Page"},{"id":358199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 122,\n -14.05\n ],\n [\n 121.8,\n -14.05\n ],\n [\n 121.8,\n -13.9\n ],\n [\n 122,\n -13.9\n ],\n [\n 122,\n -14.05\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-08","publicationStatus":"PW","scienceBaseUri":"5bc02f77e4b0fc368eb53839","contributors":{"authors":[{"text":"Green, Rebecca H.","contributorId":208503,"corporation":false,"usgs":false,"family":"Green","given":"Rebecca","email":"","middleInitial":"H.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":747469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":747470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":747468,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199954,"text":"70199954 - 2018 - Improving earthquake rupture forecasts using California as a guide","interactions":[],"lastModifiedDate":"2018-11-14T09:01:53","indexId":"70199954","displayToPublicDate":"2018-10-09T10:18:39","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Improving earthquake rupture forecasts using California as a guide","docAbstract":"This article discusses ways in which earthquake rupture forecast models might be improved. Because changes are most easily described in the context of specific models, the third Uniform California Earthquake Rupture Forecast (UCERF3) and its presumed successor, UCERF4, is used as a basis for discussion. Virtually all of the issues and possible improvements discussed are nevertheless general and should therefore be applicable to other regions as well. Two common themes are a need for better epistemic uncertainty representation and the potential utility of physics‐based simulators. Given the large number of possible improvements, coupled with challenges in defining the potential value of each, which will vary among uses, community feedback is invaluable in terms of setting priorities. We should also strive to define more objective valuation metrics.
","language":"English","publisher":"SSA","doi":"10.1785/0220180151","usgsCitation":"Field, E., and Working Group on California Earthquake Probabilities, 2018, Improving earthquake rupture forecasts using California as a guide: Seismological Research Letters, v. 89, no. 6, p. 2337-2346, https://doi.org/10.1785/0220180151.","productDescription":"10 p.","startPage":"2337","endPage":"2346","ipdsId":"IP-101307","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":358197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-03","publicationStatus":"PW","scienceBaseUri":"5bc02f77e4b0fc368eb5383b","contributors":{"authors":[{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":1165,"corporation":false,"usgs":true,"family":"Field","given":"Edward H.","email":"field@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":747466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Working Group on California Earthquake Probabilities","contributorId":128141,"corporation":true,"usgs":false,"organization":"Working Group on California Earthquake Probabilities","id":747523,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70199996,"text":"70199996 - 2018 - Downhole log evidence for the coexistence of structure II gas hydrate and free gas below the bottom simulating reflector in the South China Sea","interactions":[],"lastModifiedDate":"2018-10-10T10:06:27","indexId":"70199996","displayToPublicDate":"2018-10-09T10:03:02","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Downhole log evidence for the coexistence of structure II gas hydrate and free gas below the bottom simulating reflector in the South China Sea","docAbstract":"Stratigraphic layered pore-filling gas hydrates are identified above the bottom simulating reflector (BSR) using the well log and core data acquired at Sites W11 and W17 during the third gas hydrate drilling expedition conducted by China's Geological Survey/Guangzhou Marine Geological Survey (GMGS3) in the South China Sea. A seismic profile near Site W17, reveal the presence of two BSRs (i.e., double BSR), which we show to relate to zones of structure I gas hydrate (I-BSR) and structure II gas hydrate (II-BSR). Well log data from Site W17 between the “I-BSR” (projected depth of 250 mbsf) and “II-BSR” (projected depth of 330 mbsf) showed anomalous responses for gas hydrate-bearing sediments with high resistivity, high S-wave velocity, and alternating high and low P-wave velocities. Pressure core data support the interpretation that structure II gas hydrate occurs at a depth of 263 mbsf at Site W17. The cross-plot between log-derived neutron and density porosities reveals a free gas-bearing layer at a depth of 258–270 mbsf, suggesting gas hydrate coexists with free gas between the “I-BSR” and the “II-BSR.” Synthetic seismograms generated from the P-wave velocity and density logs further support the presence of free gas in this section. Based on the coexistence of hydrate, free gas and water, the simplified three-phase equation (STPE) was modified to simultaneously estimate free gas and hydrate saturations beneath the “I-BSR” from P-wave and S-wave velocity logs, assuming uniform or patchy distributions of free gas. The estimated free gas and hydrate saturations, together with gas compositions from pressure core samples, collectively indicate that structure II gas hydrate and free gas are interbedded and coexist below the “I-BSR” at Site W17. Our study of the coexistence of gas hydrate and free gas between the double BSR at Site W17 provides new insights into gas hydrate systems in nature that contain more complex gas chemistries.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.09.024","usgsCitation":"Qian, J., Wang, X., Collett, T.S., Guo, Y., Kang, D., and Jin, J., 2018, Downhole log evidence for the coexistence of structure II gas hydrate and free gas below the bottom simulating reflector in the South China Sea: Marine and Petroleum Geology, v. 98, p. 662-674, https://doi.org/10.1016/j.marpetgeo.2018.09.024.","productDescription":"13 p.","startPage":"662","endPage":"674","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":358236,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"South China Sea","volume":"98","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f78e4b0fc368eb5383f","contributors":{"authors":[{"text":"Qian, Jin","contributorId":208554,"corporation":false,"usgs":false,"family":"Qian","given":"Jin","email":"","affiliations":[],"preferred":false,"id":747680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Xiujuan","contributorId":87071,"corporation":false,"usgs":true,"family":"Wang","given":"Xiujuan","affiliations":[],"preferred":false,"id":747681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":747682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guo, Yiqun","contributorId":195860,"corporation":false,"usgs":false,"family":"Guo","given":"Yiqun","email":"","affiliations":[],"preferred":false,"id":747683,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kang, Dongju","contributorId":208555,"corporation":false,"usgs":false,"family":"Kang","given":"Dongju","email":"","affiliations":[],"preferred":false,"id":747684,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jin, Jiapeng","contributorId":208556,"corporation":false,"usgs":false,"family":"Jin","given":"Jiapeng","email":"","affiliations":[],"preferred":false,"id":747685,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226708,"text":"70226708 - 2018 - Igneous and detrital zircon U-Pb and Lu-Hf geochronology of the late Meso- to Neoproterozoic northwest Botswana rift: Maximum depositional age and provenance of the Ghanzi Group, Kalahari Copperbelt, Botswana and Namibia","interactions":[],"lastModifiedDate":"2021-12-07T12:17:51.532126","indexId":"70226708","displayToPublicDate":"2018-10-06T06:09:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3112,"text":"Precambrian Research","active":true,"publicationSubtype":{"id":10}},"title":"Igneous and detrital zircon U-Pb and Lu-Hf geochronology of the late Meso- to Neoproterozoic northwest Botswana rift: Maximum depositional age and provenance of the Ghanzi Group, Kalahari Copperbelt, Botswana and Namibia","docAbstract":"New igneous and detrital zircon laser ablation-inductively coupled plasma mass spectrometry (LA-ICPMS) U-Pb geochronology and Lu-Hf isotopic data are presented for the Mesoproterozoic Kgwebe Formation and the unconformably overlying Ghanzi Group in northwestern Botswana. The Makgabana Hills porphyritic rhyolite flow from the Ghanzi area yielded a U-Pb concordia age of 1085.5 ± 4.5 Ma and provides a new maximum depositional age for the unconformably overlying Ghanzi Group. Detrital zircon (n = 448) from the Ghanzi Group yielded a 207Pb/206Pb age distribution with a dominant (70 to 90%) Mesoproterozoic population (∼1450 to ∼1050 Ma), a smaller (5 to 20%) Paleoproterozoic (∼2200 to ∼1700 Ma) population, and a few (n = 4) older (∼3000 Ma to ∼2450 Ma) grains. A maximum depositional age constraint of ∼1060 to ∼1050 Ma was obtained for middle and upper Ghanzi Group based on the weighted-mean 207Pb/206Pb age of the youngest clusters of overlapping zircon ages for each sample.
Initial hafnium ratios (εHfi) and corresponding crustal residence model ages (TCDM) for the Paleoproterozoic zircon populations indicate either fractionation from a chondritic uniform reservoir (CHUR) or mixing between juvenile mantle and older crustal components. Mesoproterozoic zircon with εHfi values between −20 and +15 and TCDM model ages between 3000 and 1200 Ma suggest that the source terrane(s) contained magmatic rocks including both juvenile material and substantially reworked Paleoproterozoic and possibly Archean crust.
Comparison with a compilation of published U-Pb, Lu-Hf, and Sm-Nd data from the Kalahari Craton suggests that the predominant Mesoproterozoic zircon population was derived from the Namaqua Sector, Rehoboth Basement Inlier, Kwando Complex, and Choma-Kalomo Block; some zircon may have had distal sources in adjacent Rodinia landmasses. Both Archean cratonic components and juvenile ∼1200 to ∼1000 Ma magmatic rocks of the Natal Sector and the Maud and Mozambique belts on the eastern margin of the craton are unlikely sources for the detrital zircon based on isotopic composition. Sediment transported from the western margin of the Kalahari Craton entered the northwest Botswana rift and mixed with sediments from the Rehoboth Basement Inlier and Paleo- to Mesoproterozoic terranes that bound the northwest Botswana rift.
Insufficient food during early life could limit the population growth of endangered Pallid Sturgeon Scaphirhynchus albus in the lower Missouri River. Shallow‐water habitat restoration is intended to provide nursery benefits, including food, for young sturgeon, but the effect of shallow‐water habitat on their diet is unknown. Age‐0 Pallid Sturgeon are rare, providing little opportunity for direct evaluation; however, studying the closely related and abundant Shovelnose Sturgeon S. platorynchus may provide valuable information to guide habitat restoration efforts. We compared diet, body condition (lipid content), and change in body weight (24‐h bioenergetics simulation) for postdrift, age‐0 sturgeon among five reaches ranging widely in shallow‐water habitat availability. Lipid content of satiated and emaciated laboratory‐reared individuals were compared with that of wild‐caught fish. In general, shallow‐water habitat availability appeared to have little effect on the variables examined. Regardless of reach, wild‐caught fish primarily consumed chironomids, and empty stomachs were rare. Additionally, differences in prey weight, lipid content, or the modeled change in body weight did not usually correspond to differences in shallow‐water habitat availability. Instead, we found annual differences, as prey weight consumed and the percentage of fish with modeled weight gain was often higher in 2015 than 2014, while the opposite was true for the percentage of fish with lipid content values that were comparable with the emaciated laboratory standard. Overall, our findings complement recent suggestions that shallow‐water habitat restoration efforts, as previously implemented, may not benefit sturgeon populations. Our results coupled with previous research suggest that the lower Missouri River prey base can support a stable Shovelnose Sturgeon population; however, additional research is needed to determine whether this applies to Pallid Sturgeon.
","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10236","usgsCitation":"Civiello, A.P., Gosch, N., Gemeinhardt, T., Miller, M., Bonneau, J., Chojnacki, K., Delonay, A.J., and Long, J.M., 2018, Diet and condition of age‐0 Scaphirhynchus Sturgeon: Implications for shallow‐water habitat restoration: North American Journal of Fisheries Management, v. 38, no. 6, p. 1324-1338, https://doi.org/10.1002/nafm.10236.","productDescription":"15 p.","startPage":"1324","endPage":"1338","ipdsId":"IP-090944","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468332,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10236","text":"Publisher Index Page"},{"id":379943,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.658203125,\n 38.151837403006766\n ],\n [\n -90.3076171875,\n 38.151837403006766\n ],\n [\n -90.3076171875,\n 39.57182223734374\n ],\n [\n -94.658203125,\n 39.57182223734374\n ],\n [\n -94.658203125,\n 38.151837403006766\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Civiello, A. P.","contributorId":171493,"corporation":false,"usgs":false,"family":"Civiello","given":"A.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":803389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gosch, N. J. C.","contributorId":244139,"corporation":false,"usgs":false,"family":"Gosch","given":"N. J. C.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":803390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gemeinhardt, T. R.","contributorId":171492,"corporation":false,"usgs":false,"family":"Gemeinhardt","given":"T. R.","affiliations":[],"preferred":false,"id":803391,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, M. L.","contributorId":244140,"corporation":false,"usgs":false,"family":"Miller","given":"M. L.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":803392,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bonneau, J. L.","contributorId":171494,"corporation":false,"usgs":false,"family":"Bonneau","given":"J. L.","affiliations":[],"preferred":false,"id":803393,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chojnacki, Kimberly 0000-0001-6091-3977 kchojnacki@usgs.gov","orcid":"https://orcid.org/0000-0001-6091-3977","contributorId":221080,"corporation":false,"usgs":true,"family":"Chojnacki","given":"Kimberly","email":"kchojnacki@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":803394,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DeLonay, Aaron J. 0000-0002-3752-2799 adelonay@usgs.gov","orcid":"https://orcid.org/0000-0002-3752-2799","contributorId":2725,"corporation":false,"usgs":true,"family":"DeLonay","given":"Aaron","email":"adelonay@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":803395,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":803396,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70199953,"text":"70199953 - 2018 - Improving confidence by embracing uncertainty: A meta-analysis of U.S. hunting values for benefit transfer","interactions":[],"lastModifiedDate":"2018-10-05T14:42:19","indexId":"70199953","displayToPublicDate":"2018-10-05T14:42:16","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1477,"text":"Ecosystem Services","active":true,"publicationSubtype":{"id":10}},"title":"Improving confidence by embracing uncertainty: A meta-analysis of U.S. hunting values for benefit transfer","docAbstract":"Recreational hunting in the United States has traditional and cultural importance, and generates substantial economic benefits to individual hunters themselves. This paper conducts a meta-analysis of existing nonmarket valuation estimates for hunting in the United States to explore sources and implications of variation and uncertainty in these estimates. A multi-level meta-regression model is estimated to forecast point estimates for different hunting contexts, as well as to construct bounds of uncertainty around these estimates. The results and discussion provide insight to practitioners who need to conduct or understand benefit transfer, as well as those particularly interested in the value of hunting in the U.S.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2018.07.001","usgsCitation":"Huber, C., Meldrum, J., and Richardson, L., 2018, Improving confidence by embracing uncertainty: A meta-analysis of U.S. hunting values for benefit transfer: Ecosystem Services, v. 33, no. B, p. 225-236, https://doi.org/10.1016/j.ecoser.2018.07.001.","productDescription":"12 p.","startPage":"225","endPage":"236","ipdsId":"IP-091230","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":358189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"B","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f78e4b0fc368eb53843","contributors":{"authors":[{"text":"Huber, Christopher 0000-0001-8446-8134 chuber@usgs.gov","orcid":"https://orcid.org/0000-0001-8446-8134","contributorId":127600,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":747463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":747464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, Leslie","contributorId":197525,"corporation":false,"usgs":false,"family":"Richardson","given":"Leslie","affiliations":[],"preferred":false,"id":747465,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199950,"text":"70199950 - 2018 - Machine learning for ecosystem services","interactions":[],"lastModifiedDate":"2018-10-05T14:40:59","indexId":"70199950","displayToPublicDate":"2018-10-05T14:40:55","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1477,"text":"Ecosystem Services","active":true,"publicationSubtype":{"id":10}},"title":"Machine learning for ecosystem services","docAbstract":"Recent developments in machine learning have expanded data-driven modelling (DDM) capabilities, allowing artificial intelligence to infer the behaviour of a system by computing and exploiting correlations between observed variables within it. Machine learning algorithms may enable the use of increasingly available ‘big data’ and assist applying ecosystem service models across scales, analysing and predicting the flows of these services to disaggregated beneficiaries. We use the Weka and ARIES software to produce two examples of DDM: firewood use in South Africa and biodiversity value in Sicily, respectively. Our South African example demonstrates that DDM (64–91% accuracy) can identify the areas where firewood use is within the top quartile with comparable accuracy as conventional modelling techniques (54–77% accuracy). The Sicilian example highlights how DDM can be made more accessible to decision makers, who show both capacity and willingness to engage with uncertainty information. Uncertainty estimates, produced as part of the DDM process, allow decision makers to determine what level of uncertainty is acceptable to them and to use their own expertise for potentially contentious decisions. We conclude that DDM has a clear role to play when modelling ecosystem services, helping produce interdisciplinary models and holistic solutions to complex socio-ecological issues.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2018.04.004","usgsCitation":"Willcock, S., Martinez-Lopez, J., Hooftman, D.A., Bagstad, K.J., Balbi, S., Marzo, A., Prato, C., Sciandrello, S., Signorello, G., Voigt, B., Villa, F., Bullock, J.M., and Athanasiadis, I., 2018, Machine learning for ecosystem services: Ecosystem Services, v. 33, no. Part B, p. 165-174, https://doi.org/10.1016/j.ecoser.2018.04.004.","productDescription":"10 p.","startPage":"165","endPage":"174","ipdsId":"IP-091205","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468333,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoser.2018.04.004","text":"Publisher Index Page"},{"id":358188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"Part B","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f79e4b0fc368eb53845","contributors":{"authors":[{"text":"Willcock, Simon 0000-0001-9534-9114","orcid":"https://orcid.org/0000-0001-9534-9114","contributorId":201576,"corporation":false,"usgs":false,"family":"Willcock","given":"Simon","email":"","affiliations":[{"id":36207,"text":"Bangor University","active":true,"usgs":false}],"preferred":false,"id":747437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martinez-Lopez, Javier 0000-0003-4857-3396","orcid":"https://orcid.org/0000-0003-4857-3396","contributorId":208480,"corporation":false,"usgs":false,"family":"Martinez-Lopez","given":"Javier","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":747438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooftman, Danny A.P.","contributorId":208490,"corporation":false,"usgs":false,"family":"Hooftman","given":"Danny","email":"","middleInitial":"A.P.","affiliations":[{"id":37805,"text":"NERC Centre for Ecology and Hydrology","active":true,"usgs":false}],"preferred":false,"id":747439,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":747436,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Balbi, Stefano 0000-0001-8190-5968","orcid":"https://orcid.org/0000-0001-8190-5968","contributorId":208481,"corporation":false,"usgs":false,"family":"Balbi","given":"Stefano","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":747440,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marzo, Alessia","contributorId":208491,"corporation":false,"usgs":false,"family":"Marzo","given":"Alessia","email":"","affiliations":[{"id":37806,"text":"University of Catania","active":true,"usgs":false}],"preferred":false,"id":747441,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prato, Carlo","contributorId":208492,"corporation":false,"usgs":false,"family":"Prato","given":"Carlo","email":"","affiliations":[{"id":37806,"text":"University of Catania","active":true,"usgs":false}],"preferred":false,"id":747442,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sciandrello, Saverio 0000-0003-1132-5698","orcid":"https://orcid.org/0000-0003-1132-5698","contributorId":208493,"corporation":false,"usgs":false,"family":"Sciandrello","given":"Saverio","email":"","affiliations":[{"id":37806,"text":"University of Catania","active":true,"usgs":false}],"preferred":false,"id":747443,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Signorello, Giovanni 0000-0002-5140-4975","orcid":"https://orcid.org/0000-0002-5140-4975","contributorId":208494,"corporation":false,"usgs":false,"family":"Signorello","given":"Giovanni","email":"","affiliations":[{"id":37807,"text":"University of Cataria","active":true,"usgs":false}],"preferred":false,"id":747444,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Voigt, Brian","contributorId":208483,"corporation":false,"usgs":false,"family":"Voigt","given":"Brian","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":747445,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Villa, Ferdinando 0000-0002-5114-3007","orcid":"https://orcid.org/0000-0002-5114-3007","contributorId":208486,"corporation":false,"usgs":false,"family":"Villa","given":"Ferdinando","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":747446,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bullock, James M.","contributorId":208495,"corporation":false,"usgs":false,"family":"Bullock","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":37805,"text":"NERC Centre for Ecology and Hydrology","active":true,"usgs":false}],"preferred":false,"id":747447,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Athanasiadis, Ioannis 0000-0003-2764-0078","orcid":"https://orcid.org/0000-0003-2764-0078","contributorId":208484,"corporation":false,"usgs":false,"family":"Athanasiadis","given":"Ioannis","email":"","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":747448,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70197900,"text":"sir20185085 - 2018 - Historical eruptions and hazards at Bogoslof volcano, Alaska","interactions":[],"lastModifiedDate":"2018-10-09T11:20:05","indexId":"sir20185085","displayToPublicDate":"2018-10-05T12:05:38","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5085","title":"Historical eruptions and hazards at Bogoslof volcano, Alaska","docAbstract":"Bogoslof volcano is a submarine volcano in the southern
Bering Sea (53.9272°N, 168.0344°W), located 100 kilometers
(km) west of Dutch Harbor/Unalaska, and 40 km north
of Umnak Island. The volcano has a relatively long history of
scientific investigation and several of its historical eruptions
have been documented during brief visits to the area since the
late 1700s. The purpose of this report is to provide a modern
volcanological perspective on past eruptions of Bogoslof and
to readdress some of the eruptive phenomena described in
historical documents and reports. We also present for the first
time a brief analysis of the hazards posed by Bogoslof eruptions.
While this report was being prepared, Bogoslof volcano
was in an ongoing state of eruptive activity that began in
mid-December 2016. Detectable eruptive activity ended in late
August 2017 and the volcano has remained quiet since then.
Because we have not yet visited Bogoslof Island and have
only a few distal tephra samples from two eruptive events,
we will not discuss in detail the 2016–17 eruptive sequence,
but will provide some information for comparative purposes.
When more detailed data has been collected, a more extensive
review of the 2016–17 Bogoslof eruption should be the subject
of future reports.
Alaska Volcano Observatory
U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508
Context
The Rainwater Basin region in south-central Nebraska supports a complex network of spatially-isolated wetlands that harbor diverse floral and faunal communities. Since European settlement, many wetlands have been lost from the network, which has increased distances among remaining wetlands. As a result, populations of wildlife species with limited dispersal capabilities may have become isolated and face greater local extinction risks.
Objectives
We compared the pre-European settlement and current extent of the Rainwater Basin network to assess the effects of wetland losses on network connectivity for a range of maximum dispersal distances.
Methods
We constructed network models for a range of maximum dispersal distances and calculated network metrics to assess changes in network connectivity and the relative importance of individual wetlands in regulating flow.
Results
Since European settlement, the number of wetlands in the Rainwater Basin has decreased by >90%. The average distance to the nearest neighboring wetland has increased by 150% to ~1.2 km, and the dispersal distance necessary to travel throughout the whole network has increased from 3.5 to 10.0 km. Last, relative importance of individual wetlands depended on the maximum dispersal distance. Which wetlands to preserve to maintain connectivity might therefore depend on the dispersal capabilities of the species or taxa of interest.
Conclusions
To preserve a broad range of biodiversity, conservation efforts should focus on preserving dense clusters of wetlands at fine spatial scales to maintain current levels of network connectivity, and restoring connections between clusters to facilitate long-range dispersal of species with limited dispersal capabilities.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-018-0721-1","usgsCitation":"Verheijen, B., Varner, D.M., and Haukos, D.A., 2018, Effects of large-scale wetland loss on network connectivity of the Rainwater Basin, Nebraska: Landscape Ecology, v. 33, p. 1939-1951, https://doi.org/10.1007/s10980-018-0721-1.","productDescription":"13 p.","startPage":"1939","endPage":"1951","ipdsId":"IP-097520","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395455,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Rainwater Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.77783203125,\n 40.04443758460856\n ],\n [\n -95.64697265625,\n 40.04443758460856\n ],\n [\n -95.64697265625,\n 41.376808565702355\n ],\n [\n -99.77783203125,\n 41.376808565702355\n ],\n [\n -99.77783203125,\n 40.04443758460856\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","noUsgsAuthors":false,"publicationDate":"2018-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Verheijen, Bram H. F.","contributorId":274514,"corporation":false,"usgs":false,"family":"Verheijen","given":"Bram H. F.","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":833103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Varner, Dana M.","contributorId":271196,"corporation":false,"usgs":false,"family":"Varner","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":40582,"text":"Rainwater Basin Joint Venture","active":true,"usgs":false}],"preferred":false,"id":833104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833105,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}