In almost all past inversions of large-earthquake ground motions for rupture behavior, the goal of the inversion is to find the “best fitting” rupture model that predicts ground motions which optimize some function of the difference between predicted and observed ground motions. This type of inversion was pioneered in the linear-inverse sense by Olson and Apsel (1982), who minimized the square of the difference between observed and simulated motions (“least squares”) while simultaneously minimizing the rupture-model norm (by setting the null-space component of the rupture model to zero), and has been extended in many ways, one of which is the use of nonlinear inversion schemes such as simulated annealing algorithms that optimize some other misfit function. For example, the simulated annealing algorithm of Piatanesi and others (2007) finds the rupture model that minimizes a “cost” function which combines a least-squares and a waveform-correlation measure of misfit.
All such inversions that look for a unique “best” model have at least three problems. (1) They have removed the null-space component of the rupture model—that is, an infinite family of rupture models that all fit the data equally well have been narrowed down to a single model. Some property of interest in the rupture model might have been discarded in this winnowing process. (2) Smoothing constraints are commonly used to yield a unique “best” model, in which case spatially rough rupture models will have been discarded, even if they provide a good fit to the data. (3) No estimate of confidence in the resulting rupture models can be given because the effects of unknown errors in the Green’s functions (“theory errors”) have not been assessed. In inversion for rupture behavior, these theory errors are generally larger than the data errors caused by ground noise and instrumental limitations, and so overfitting of the data is probably ubiquitous for such inversions.
Recently, attention has turned to the inclusion of theory errors in the inversion process. Yagi and Fukahata (2011) made an important contribution by presenting a method to estimate the uncertainties in predicted large-earthquake ground motions due to uncertainties in the Green’s functions. Here we derive their result and compare it with the results of other recent studies that look at theory errors in a Bayesian inversion context particularly those by Bodin and others (2012), Duputel and others (2012), Dettmer and others (2014), and Minson and others (2014).
Notably, in all these studies, the estimates of theory error were obtained from theoretical considerations alone; none of the investigators actually measured Green’s function errors. Large earthquakes typically have aftershocks, which, if their rupture surfaces are physically small enough, can be considered point evaluations of the real Green’s functions of the Earth. Here we simulate smallaftershock ground motions with (erroneous) theoretical Green’s functions. Taking differences between aftershock ground motions and simulated motions to be the “theory error,” we derive a statistical model of the sources of discrepancies between the theoretical and real Green’s functions. We use this model with an extended frequency-domain version of the time-domain theory of Yagi and Fukahata (2011) to determine the expected variance 2 τ caused by Green’s function error in ground motions from a larger (nonpoint) earthquake that we seek to model.
We also differ from the above-mentioned Bayesian inversions in our handling of the nonuniqueness problem of seismic inversion. We follow the philosophy of Segall and Du (1993), who, instead of looking for a best-fitting model, looked for slip models that answered specific questions about the earthquakes they studied. In their Bayesian inversions, they inductively derived a posterior probability-density function (PDF) for every model parameter. We instead seek to find two extremal rupture models whose ground motions fit the data within the error bounds given by 2 τ , as quantified by using a chi-squared test described below. So, we can ask questions such as, “What are the rupture models with the highest and lowest average rupture speed consistent with the theory errors?” Having found those models, we can then say with confidence that the true rupture speed is somewhere between those values. Although the Bayesian approach gives a complete solution to the inverse problem, it is computationally demanding: Minson and others (2014) needed 1010 forward kinematic simulations to derive their posterior probability distribution. In our approach, only about107 simulations are needed. Moreover, in practical application, only a small set of rupture models may be needed to answer the relevant questions—for example, determining the maximum likelihood solution (achievable through standard inversion techniques) and the two rupture models bounding some property of interest.
The specific property that we wish to investigate is the correlation between various rupturemodel parameters, such as peak slip velocity and rupture velocity, in models of real earthquakes. In some simulations of ground motions for hypothetical large earthquakes, such as those by Aagaard and others (2010) and the Southern California Earthquake Center Broadband Simulation Platform (Graves and Pitarka, 2015), rupture speed is assumed to correlate locally with peak slip, although there is evidence that rupture speed should correlate better with peak slip speed, owing to its dependence on local stress drop. We may be able to determine ways to modify Piatanesi and others’s (2007) inversion’s “cost” function to find rupture models with either high or low degrees of correlation between pairs of rupture parameters. We propose a cost function designed to find these two extremal models.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171151","usgsCitation":"Spudich, P., Cirella, A., Scognamiglio, L., and Tinti, E., 2017, Analysis of the variability in ground-motion synthesis and inversion: U.S. Geological Survey Open-File Report 2017–1151, 39 p., https://doi.org/10.3133/ofr20171151.","productDescription":"iv, 39 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-087954","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":349837,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1151/ofr20171151_.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1151"},{"id":349836,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1151/coverthb.jpg"}],"contact":"Director,
Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road
Mail Stop 977
Menlo Park, CA 94025
We present a prototype operational loss model based on UCERF3-ETAS, which is the third Uniform California Earthquake Rupture Forecast with an Epidemic Type Aftershock Sequence (ETAS) component. As such, UCERF3-ETAS represents the first earthquake forecast to relax fault segmentation assumptions and to include multi-fault ruptures, elastic-rebound, and spatiotemporal clustering, all of which seem important for generating realistic and useful aftershock statistics. UCERF3-ETAS is nevertheless an approximation of the system, however, so usefulness will vary and potential value needs to be ascertained in the context of each application. We examine this question with respect to statewide loss estimates, exemplifying how risk can be elevated by orders of magnitude due to triggered events following various scenario earthquakes. Two important considerations are the probability gains, relative to loss likelihoods in the absence of main shocks, and the rapid decay of gains with time. Significant uncertainties and model limitations remain, so we hope this paper will inspire similar analyses with respect to other risk metrics to help ascertain whether operationalization of UCERF3-ETAS would be worth the considerable resources required.
","language":"English","publisher":"EERI","doi":"10.1193/011817EQS017M","usgsCitation":"Field, E., Porter, K., and Milner, K., 2017, A prototype operational earthquake loss model for California based on UCERF3-ETAS – A first look at valuation: Earthquake Spectra, v. 33, no. 4, p. 1279-1299, https://doi.org/10.1193/011817EQS017M.","productDescription":"21 p.","startPage":"1279","endPage":"1299","ipdsId":"IP-087973","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":349888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-01","publicationStatus":"PW","scienceBaseUri":"5a60faeae4b06e28e9c22988","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":724680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Porter, Keith","contributorId":191074,"corporation":false,"usgs":false,"family":"Porter","given":"Keith","affiliations":[],"preferred":false,"id":724681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Milner, Kevn","contributorId":201228,"corporation":false,"usgs":false,"family":"Milner","given":"Kevn","email":"","affiliations":[],"preferred":false,"id":724682,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196757,"text":"70196757 - 2017 - Experimental stocking of sport fish in the regulated Tallapoosa River to determine critical periods for recruitment","interactions":[],"lastModifiedDate":"2018-04-30T12:50:43","indexId":"70196757","displayToPublicDate":"2017-12-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"128-2017","title":"Experimental stocking of sport fish in the regulated Tallapoosa River to determine critical periods for recruitment","docAbstract":"The stocking of fish in riverine systems to re-establish stocks for conservation and management appears limited to a few species and often occurs in reaches impacted by impoundments. Stocking of sport fish species such as centrarchids and ictalurids is often restricted to lentic environments, although stocking in lotic environments is feasible with variable success. R. L. Harris Dam on the Tallapoosa River, Alabama is the newest and uppermost dam facility on the river (operating since 1983); flows from the dam have been managed adaptively for multiple stakeholder objectives since 2005. One of the stakeholders’ primary objectives is to provide quality sport fisheries in the Tallapoosa River in the managed area below the dam. Historically, ictalurids and cyprinids dominated the river above Lake Martin. However, investigations after Harris Dam closed have detected a shift in community structure to domination by centrarchids. Flow management (termed the Green Plan) has been occurring since March 2005; however, sport fish populations as measured by recruitment of age-1 sport fishes below the dam has not responded adequately to flow management. The objectives of this research were to: (1) determine if stocking Channel Catfish Ictalurus punctatus and Redbreast Sunfish Lepomis auritus influences year-class strength; (2) estimate vital rates (i.e. growth, mortality, and recruitment) for Channel Catfish populations for use in an age-based population model; and (3) identify age-specific survivorship and fecundity rates contributing to Channel Catfish population stability. No marked Redbreast Sunfish were recaptured due to poor marking efficacy and therefore no further analysis was conducted with this species. Stocked Channel Catfish, similarly, were not recaptured, leaving reasons for non-recapture unknown. Matrix models exploring vital rates illustrated survival to age-1 for Channel Catfish to be less than 0.03% and that survival through ages 2 – 4 had equal contribution to overall population growth, indicating recruitment limitation may impact population size and stability. Results from this study indicate stock enhancement of sport fish populations below Harris Dam may not be an effective management technique at this time.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Lloyd, M.C., Lai, Q., Sammons, S., and Irwin, E.R., 2017, Experimental stocking of sport fish in the regulated Tallapoosa River to determine critical periods for recruitment: Cooperator Science Series 128-2017, 24 p.","productDescription":"24 p.","ipdsId":"IP-086160","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":353855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":353845,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/cdm/ref/collection/document/id/2218"}],"country":"United States","state":"Alabama","otherGeospatial":"Tallapoosa River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.7208251953125,\n 32.93953889877841\n ],\n [\n -85.48324584960936,\n 32.93953889877841\n ],\n [\n -85.48324584960936,\n 33.6283419913718\n ],\n [\n -85.7208251953125,\n 33.6283419913718\n ],\n [\n -85.7208251953125,\n 32.93953889877841\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee79ce4b0da30c1bfc2f0","contributors":{"authors":[{"text":"Lloyd, M. Clint","contributorId":204520,"corporation":false,"usgs":false,"family":"Lloyd","given":"M.","email":"","middleInitial":"Clint","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":734239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lai, Quan","contributorId":204521,"corporation":false,"usgs":false,"family":"Lai","given":"Quan","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":734240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sammons, Steve","contributorId":204522,"corporation":false,"usgs":false,"family":"Sammons","given":"Steve","email":"","affiliations":[{"id":36951,"text":"Auburnj University","active":true,"usgs":false}],"preferred":false,"id":734241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irwin, Elise R. 0000-0002-6866-4976 eirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-6866-4976","contributorId":2588,"corporation":false,"usgs":true,"family":"Irwin","given":"Elise","email":"eirwin@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":734238,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195106,"text":"70195106 - 2017 - Considerations in comparing the U.S. Geological Survey one‐year induced‐seismicity hazard models with “Did You Feel It?” and instrumental data","interactions":[],"lastModifiedDate":"2018-02-08T12:43:25","indexId":"70195106","displayToPublicDate":"2017-12-06T00:00:00","publicationYear":"2017","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":"Considerations in comparing the U.S. Geological Survey one‐year induced‐seismicity hazard models with “Did You Feel It?” and instrumental data","docAbstract":"The recent steep increase in seismicity rates in Oklahoma, southern Kansas, and other parts of the central United States led the U.S. Geological Survey (USGS) to develop, for the first time, a probabilistic seismic hazard forecast for one year (2016) that incorporates induced seismicity. In this study, we explore a process to ground‐truth the hazard model by comparing it with two databases of observations: modified Mercalli intensity (MMI) data from the “Did You Feel It?” (DYFI) system and peak ground acceleration (PGA) values from instrumental data. Because the 2016 hazard model was heavily based on earthquake catalogs from 2014 to 2015, this initial comparison utilized observations from these years. Annualized exceedance rates were calculated with the DYFI and instrumental data for direct comparison with the model. These comparisons required assessment of the options for converting hazard model results and instrumental data from PGA to MMI for comparison with the DYFI data. In addition, to account for known differences that affect the comparisons, the instrumental PGA and DYFI data were declustered, and the hazard model was adjusted for local site conditions. With these adjustments, examples at sites with the most data show reasonable agreement in the exceedance rates. However, the comparisons were complicated by the spatial and temporal completeness of the instrumental and DYFI observations. Furthermore, most of the DYFI responses are in the MMI II–IV range, whereas the hazard model is oriented toward forecasts at higher ground‐motion intensities, usually above about MMI IV. Nevertheless, the study demonstrates some of the issues that arise in making these comparisons, thereby informing future efforts to ground‐truth and improve hazard modeling for induced‐seismicity applications.
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Hawaii","interactions":[],"lastModifiedDate":"2020-10-06T20:29:25.699679","indexId":"70194645","displayToPublicDate":"2017-12-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Modeling fine-scale coral larval dispersal and interisland connectivity to help designate mutually-supporting coral reef marine protected areas: Insights from Maui Nui, Hawaii","docAbstract":"Connectivity among individual marine protected areas (MPAs) is one of the most important considerations in the design of integrated MPA networks. To provide such information for managers in Hawaii, USA, a numerical circulation model was developed to determine the role of ocean currents in transporting coral larvae from natal reefs throughout the high volcanic islands of the Maui Nui island complex in the southeastern Hawaiian Archipelago. Spatially- and temporally-varying wind, wave, and circulation model outputs were used to drive a km-scale, 3-dimensional, physics-based circulation model for Maui Nui. The model was calibrated and validated using satellite-tracked ocean surface current drifters deployed during coral-spawning conditions, then used to simulate the movement of the larvae of the dominant reef-building coral, Porites compressa, from 17 reefs during eight spawning events in 2010–2013. These simulations make it possible to investigate not only the general dispersal patterns from individual coral reefs, but also how anomalous conditions during individual spawning events can result in large deviations from those general patterns. These data also help identify those reefs that are dominated by self-seeding and those where self-seeding is limited to determine their relative susceptibility to stressors and potential roadblocks to recovery. Overall, the numerical model results indicate that many of the coral reefs in Maui Nui seed reefs on adjacent islands, demonstrating the interconnected nature of the coral reefs in Maui Nui and providing a key component of the scientific underpinning essential for the design of a mutually supportive network of MPAs to enhance conservation of coral reefs.
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L.","contributorId":194055,"corporation":false,"usgs":false,"family":"Elias","given":"Edwin","email":"","middleInitial":"P. L.","affiliations":[],"preferred":false,"id":724733,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194538,"text":"70194538 - 2017 - Evidence for the interior evolution of Ceres from geologic analysis of fractures","interactions":[],"lastModifiedDate":"2017-12-05T13:03:39","indexId":"70194538","displayToPublicDate":"2017-12-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for the interior evolution of Ceres from geologic analysis of fractures","docAbstract":"Ceres is the largest asteroid belt object, and the Dawn spacecraft observed Ceres since 2015. Dawn observed two morphologically distinct linear features on Ceres's surface: secondary crater chains and pit chains. Pit chains provide unique insights into Ceres's interior evolution. We interpret pit chains called the Samhain Catenae as the surface expression of subsurface fractures. Using the pit chains' spacings, we estimate that the localized thickness of Ceres's fractured, outer layer is approximately ≥58 km, at least ~14 km greater than the global average. We hypothesize that extensional stresses, induced by a region of upwelling material arising from convection/diapirism, formed the Samhain Catenae. We derive characteristics for this upwelling material, which can be used as constraints in future interior modeling studies. For example, its predicted location coincides with Hanami Planum, a high-elevation region with a negative residual gravity anomaly, which may be surficial evidence for this proposed region of upwelling material.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GL075086","usgsCitation":"Scully, J.E., Buczkowski, D., Schmedemann, N., Raymond, C.A., Castillo-Rogez, J., King, S., Bland, M.T., Ermakov, A., O’Brien, D., Marchi, S., Longobardo, A., Russell, C., Fu, R., and Neveu, M., 2017, Evidence for the interior evolution of Ceres from geologic analysis of fractures: Geophysical Research Letters, v. 44, p. 9564-9572, https://doi.org/10.1002/2017GL075086.","productDescription":"9 p.","startPage":"9564","endPage":"9572","ipdsId":"IP-090919","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":469245,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gl075086","text":"Publisher Index Page"},{"id":349690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-14","publicationStatus":"PW","scienceBaseUri":"5a60faf5e4b06e28e9c22a04","contributors":{"authors":[{"text":"Scully, Jennifer E. C.","contributorId":192188,"corporation":false,"usgs":false,"family":"Scully","given":"Jennifer","email":"","middleInitial":"E. C.","affiliations":[],"preferred":false,"id":724364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buczkowski, Debra","contributorId":177352,"corporation":false,"usgs":false,"family":"Buczkowski","given":"Debra","affiliations":[],"preferred":false,"id":724365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmedemann, Nico","contributorId":196623,"corporation":false,"usgs":false,"family":"Schmedemann","given":"Nico","email":"","affiliations":[{"id":34669,"text":"Department of Earth Sciences, Freie Universität Berlin, Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":724366,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Raymond, Carol A.","contributorId":200798,"corporation":false,"usgs":false,"family":"Raymond","given":"Carol","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":724369,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Castillo-Rogez, Julie C.","contributorId":172691,"corporation":false,"usgs":false,"family":"Castillo-Rogez","given":"Julie C.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":724367,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"King, Scott","contributorId":172690,"corporation":false,"usgs":false,"family":"King","given":"Scott","email":"","affiliations":[{"id":27082,"text":"Virginia Inst. of Tech","active":true,"usgs":false}],"preferred":false,"id":724368,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":724363,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ermakov, Anton","contributorId":189478,"corporation":false,"usgs":false,"family":"Ermakov","given":"Anton","email":"","affiliations":[],"preferred":false,"id":724370,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"O’Brien, D.P.","contributorId":173389,"corporation":false,"usgs":false,"family":"O’Brien","given":"D.P.","email":"","affiliations":[{"id":27220,"text":"Planetary Science Inst.","active":true,"usgs":false}],"preferred":false,"id":724371,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Marchi, S.","contributorId":201114,"corporation":false,"usgs":false,"family":"Marchi","given":"S.","affiliations":[],"preferred":false,"id":724372,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Longobardo, A.","contributorId":172144,"corporation":false,"usgs":false,"family":"Longobardo","given":"A.","email":"","affiliations":[{"id":26990,"text":"INAF-IAPS Istituto di Astrofisica e Planetologia Spaziali, Rome","active":true,"usgs":false}],"preferred":false,"id":724373,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Russell, C.T.","contributorId":32275,"corporation":false,"usgs":false,"family":"Russell","given":"C.T.","email":"","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":724374,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Fu, R.R.","contributorId":173388,"corporation":false,"usgs":false,"family":"Fu","given":"R.R.","email":"","affiliations":[{"id":27078,"text":"Columbia University, New York","active":true,"usgs":false}],"preferred":false,"id":724375,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Neveu, M.","contributorId":201118,"corporation":false,"usgs":false,"family":"Neveu","given":"M.","email":"","affiliations":[],"preferred":false,"id":724376,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70207060,"text":"70207060 - 2017 - Assessing the global distribution of river fisheries harvest: A systematic map protocol","interactions":[],"lastModifiedDate":"2020-12-08T17:49:51.927554","indexId":"70207060","displayToPublicDate":"2017-12-04T15:55:06","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5897,"text":"Environmental Evidence","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the global distribution of river fisheries harvest: A systematic map protocol","docAbstract":"Although surface freshwater comprises < 0.01% of the total water volume of earth, freshwater inland capture fisheries and aquaculture represent 40% of the global reported finfish harvest. While the social, economic, and ecological importance of inland fish and fisheries is difficult to overstate, they are often undervalued and underappreciated. Accurate information about these highly dispersed fisheries is inherently difficult to acquire, often unreported, and not collected in a standardized format globally. A standardized river fishery database is needed for managing aquatic systems as well as for defining relevant development policies. Here, we describe our methodology to search, identify, and describe available river fisheries information to create a harmonized global database of river fisheries harvest. This database will provide the first global database of spatially and temporally explicit river fisheries data. The database can be used to identify locations, hotspots of data collection, and gaps in existing knowledge and will be especially important to inform studies and management at larger spatial scales (i.e., watershed, regional, or global scales). This database will also be critical for developing fish biomass models for rivers, which can provide managers with information critical for decision-making, such as improved valuation methods for river fish and fisheries.
This systematic map protocol describes the methodology to search, identify, and describe available information on river fish and fisheries across the globe. We define river fisheries as “both capture and aquaculture of river finfish species for food, income, or recreation”. River fish species are those finfish that live part, or all of their lives in rivers. The searches will be conducted for the period from 1950 to present using bibliographic databases and grey literature sources. To identify relevant evidence, pre-defined inclusion and exclusion criteria will be used to screen articles at title, abstract, and full text. A searchable database containing extracted meta-data from relevant included studies will be developed and presented as a geodatabase. The final systematic map will consist of a descriptive narrative report of the distribution and content of river fish literature including a geodatabase of available information.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s13750-017-0107-x","usgsCitation":"Romulo, C., Basher, Z., Lynch, A., Kao, Y., and Taylor, W., 2017, Assessing the global distribution of river fisheries harvest: A systematic map protocol: Environmental Evidence, v. 6, 29, 10 p., https://doi.org/10.1186/s13750-017-0107-x.","productDescription":"29, 10 p.","ipdsId":"IP-085655","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":461325,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13750-017-0107-x","text":"Publisher Index Page"},{"id":369924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","noUsgsAuthors":false,"publicationDate":"2017-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Romulo, Chelsie 0000-0003-1612-1969","orcid":"https://orcid.org/0000-0003-1612-1969","contributorId":221032,"corporation":false,"usgs":false,"family":"Romulo","given":"Chelsie","email":"","affiliations":[],"preferred":false,"id":776684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Basher, Zeenatul 0000-0002-6439-8324 zbasher@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-8324","contributorId":48118,"corporation":false,"usgs":true,"family":"Basher","given":"Zeenatul","email":"zbasher@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":776685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lynch, Abigail 0000-0001-8449-8392 ajlynch@usgs.gov","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":169460,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","email":"ajlynch@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":776686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kao, Yu-Chun 0000-0001-5552-909X ykao@usgs.gov","orcid":"https://orcid.org/0000-0001-5552-909X","contributorId":192240,"corporation":false,"usgs":true,"family":"Kao","given":"Yu-Chun","email":"ykao@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":776687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, William W.","contributorId":49735,"corporation":false,"usgs":false,"family":"Taylor","given":"William W.","affiliations":[],"preferred":false,"id":776688,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228730,"text":"70228730 - 2017 - Paleoceanographic perspectives on Arctic Ocean change","interactions":[],"lastModifiedDate":"2022-02-17T17:45:40.76836","indexId":"70228730","displayToPublicDate":"2017-12-04T11:42:07","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7564,"text":"Arctic Report Card","active":true,"publicationSubtype":{"id":1}},"title":"Paleoceanographic perspectives on Arctic Ocean change","docAbstract":"The Arctic Ocean is presently experiencing changes in ocean temperature and sea ice extent that are unprecedented in the observational time period (satellite observations: 1979-Present). To provide context for the current changes, scientists turn to paleo records of past climate to document and study natural variability in the Arctic system. Paleoceanographic records that extend limited Arctic instrumental measurements are central to improving our understanding of sea ice dynamics and ocean warming and for enhancing the predictive capability of models. By coupling paleoceanographic records with modern observations, scientists can also contextualize the rate and magnitude of modern change with the deep past.
","language":"English","publisher":"NOAA","usgsCitation":"Osborne, E., Cronin, T.M., and Farmer, J., 2017, Paleoceanographic perspectives on Arctic Ocean change: Arctic Report Card, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-090214","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":396121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396081,"type":{"id":15,"text":"Index Page"},"url":"https://www.arctic.noaa.gov/Report-Card/Report-Card-2017/ArtMID/7798/ArticleID/690/Paleoceanographic-Perspectives-on-Arctic-Ocean-Change"}],"otherGeospatial":"Arctic Ocean","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Osborne, Emily","contributorId":279621,"corporation":false,"usgs":false,"family":"Osborne","given":"Emily","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":835225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":835226,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farmer, Jesse","contributorId":279623,"corporation":false,"usgs":false,"family":"Farmer","given":"Jesse","affiliations":[{"id":6644,"text":"Princeton University","active":true,"usgs":false}],"preferred":false,"id":835227,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199154,"text":"70199154 - 2017 - Evaluating methods to assess the body condition of female polar bears","interactions":[],"lastModifiedDate":"2018-09-07T15:40:32","indexId":"70199154","displayToPublicDate":"2017-12-01T15:39:17","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3671,"text":"Ursus","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating methods to assess the body condition of female polar bears","docAbstract":"An animal's body condition provides insight into its health, foraging success, and overall fitness. Measures of body composition including proportional fat content are useful indicators of condition. Isotopic dilution is a reliable non-destructive method for estimating the body composition of live mammals, but can require prolonged handling times. Alternatively, bioelectrical impedance analysis (BIA) has promise as a quick method for estimating the body composition of live mammals, but measurements can potentially be affected by field conditions. Body condition indices (BCI) and energy density models can also be used to assess body condition based on morphological measurements, but may not reliably reflect an animal's energy stores. Here we evaluate BIA, BCI, and an energy density model in measuring the energy stores of female polar bears (Ursus maritimus). We examine the relationship between total body fat (TBF) derived from isotopic dilution to these alternative methods for 9 female polar bears from 14 captures on the sea ice of the southern Beaufort Sea in April 2014–2016. An energy density model, BCI, and BIA-derived measures of TBF were poor predictors of TBF derived from isotopic dilution. We suggest energy density, BCI, and BIA may not be predictive of an animal's body fat at fine scales (e.g., among individuals within the same sex, reproductive status, and season). In particular, BIA should provide similar measures of body composition as isotopic dilution, but it failed to reliably measure TBF of individual bears. These limitations in the precision of body condition measures should be considered when planning future studies.
","language":"English","publisher":"International Association for Bear Research and Management","doi":"10.2192/URSU-D-16-00029.1","usgsCitation":"Pagano, A.M., Rode, K.D., and Atkinson, S.N., 2017, Evaluating methods to assess the body condition of female polar bears: Ursus, v. 28, no. 2, p. 171-181, https://doi.org/10.2192/URSU-D-16-00029.1.","productDescription":"11 p.","startPage":"171","endPage":"181","ipdsId":"IP-080202","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":438129,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZP447H","text":"USGS data release","linkHelpText":"Bioelectrical Impedance, Deuterium Dilution, Body Mass, and Morphological Measures of Southern Beaufort Sea Female Polar Bears, Spring 2014-2016"},{"id":357126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a365e4b0702d0e843042","contributors":{"authors":[{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":744396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":744398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atkinson, Stephen N.","contributorId":12365,"corporation":false,"usgs":false,"family":"Atkinson","given":"Stephen","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":744399,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203222,"text":"70203222 - 2017 - Simulated juvenile salmon growth and phenology respond to altered thermal regimes and stream network shape","interactions":[],"lastModifiedDate":"2019-04-29T15:40:06","indexId":"70203222","displayToPublicDate":"2017-12-01T15:31:47","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Simulated juvenile salmon growth and phenology respond to altered thermal regimes and stream network shape","docAbstract":"It is generally accepted that climate change will stress coldwater species such as Pacific salmon. However, it is unclear what aspect of altered thermal regimes (e.g., warmer winters, springs, summers, or increased variability) will have the greatest effect, and what role the spatial properties of river networks play. Thermally diverse habitats may afford protection from climate change by providing opportunities for aquatic organisms to find and use habitats with optimal conditions for growth. We hypothesized that climate‐altered thermal regimes will change growth and timing of life history events such as emergence or migration but that changes will be moderated in topologically complex stream networks where opportunities to thermoregulate are more readily available to mobile animals. Because climate change effects on populations are spatially variable and contingent upon physiological optima, assessments of risk must take a spatially explicit approach. We developed a spatially structured individual‐based model for Chinook Salmon (Oncorhynchus tshawytscha) in which movement decisions and growth were governed by water temperature and conspecific density. We evaluated growth and phenology (timing of egg emergence and smolting) under a variety of thermal regimes (each having a different minimum, rate of warming, maximum, and variability) and in three network shapes of increasing spatial complexity. Across networks, fish generally grew faster and were capable of smolting earlier in warmer scenarios where water temperatures experienced by fish were closer to optimal; however, growth decreased for some fish. We found that salmon size and smolt date responded more strongly to warmer springs and summers than to warmer winters or increased variability. Fish in the least complex network grew faster and were ready to smolt earlier than fish in the more spatially complex network shapes in the contemporary thermal regime; patterns were similar but less clear in warmer thermal regimes. Our results demonstrate that network topology may influence how fish respond to thermal landscapes, and this information will be useful for incorporating a spatiotemporal context into conservation decisions that promote long‐term viability of salmon in a changing climate.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2052","usgsCitation":"Fullerton, A.H., Burke, B.J., Lawler, J.J., Torgersen, C.E., Ebersole, J.L., and Leibowitz, S.G., 2017, Simulated juvenile salmon growth and phenology respond to altered thermal regimes and stream network shape: Ecosphere, v. 8, no. 12, Article e02052: 23 p., https://doi.org/10.1002/ecs2.2052.","productDescription":"Article e02052: 23 p.","ipdsId":"IP-080351","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469248,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2052","text":"Publisher Index Page"},{"id":363346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"12","noUsgsAuthors":false,"publicationDate":"2017-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Fullerton, Aimee H.","contributorId":146936,"corporation":false,"usgs":false,"family":"Fullerton","given":"Aimee","email":"","middleInitial":"H.","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":761757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burke, Brian J.","contributorId":196656,"corporation":false,"usgs":false,"family":"Burke","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":761758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawler, Joshua J.","contributorId":73327,"corporation":false,"usgs":false,"family":"Lawler","given":"Joshua","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":761759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":761760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ebersole, Joseph L.","contributorId":146938,"corporation":false,"usgs":false,"family":"Ebersole","given":"Joseph","email":"","middleInitial":"L.","affiliations":[{"id":12657,"text":"EPA NEIC","active":true,"usgs":false}],"preferred":false,"id":761761,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leibowitz, Scott G.","contributorId":156432,"corporation":false,"usgs":false,"family":"Leibowitz","given":"Scott","email":"","middleInitial":"G.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":761762,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202035,"text":"70202035 - 2017 - 3D Pressure‐limited approach to model and estimate CO2 injection and storage capacity: saline Mount Simon Formation","interactions":[],"lastModifiedDate":"2019-02-07T13:49:56","indexId":"70202035","displayToPublicDate":"2017-12-01T13:47:19","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5800,"text":"Greenhouse Gases: Science and Technology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"3D Pressure‐limited approach to model and estimate CO2 injection and storage capacity: saline Mount Simon Formation","title":"3D Pressure‐limited approach to model and estimate CO2 injection and storage capacity: saline Mount Simon Formation","docAbstract":"To estimate the carbon dioxide (CO2) injection and storage capacity of saline formations, we used Tough2‐ECO2N simulation software to develop a pressure‐limited (dynamic) simulation approach based on applying three‐dimensional (3D) numerical simulation only on the effective injection area (Aeff) surrounding each injection well. A statistical analysis was performed to account for existing reservoir heterogeneity and property variations. The accuracy of the model simulation results (such as CO2 plume extension and induced injection well bottomhole pressure values) were tested and verified against the data obtained from the Decatur CO2 injection study of the Mount Simon Formation. Next, we designed a full‐field CO2 injection pattern by populating the core sections of this formation with a series of the simulated effective injection areas such that each simulated Aeff acts as a closed domain. The results of this analysis were used to estimate the optimum number and location of the required CO2 injection wells, along with the dynamic annual CO2 injection rate and overall pressure‐limited storage capacity of this formation. This approach enabled us to model separate CO2 injection activities independently at different sections of the same saline formation and to model and simulate faults and natural barriers by considering them as boundary conditions for each simulated Aeff without constructing full‐field models. Using this approach, a series of modeled Aeff with relevant properties may be redesigned to model any other saline formation with a similar structure.
","language":"English","publisher":"Wiley","doi":"10.1002/ghg.1701","usgsCitation":"Jahediesfanjani, H., Warwick, P., and Anderson, S.T., 2017, 3D Pressure‐limited approach to model and estimate CO2 injection and storage capacity: saline Mount Simon Formation: Greenhouse Gases: Science and Technology, v. 7, no. 6, p. 1080-1096, https://doi.org/10.1002/ghg.1701.","productDescription":"17 p.","startPage":"1080","endPage":"1096","ipdsId":"IP-084315","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":469251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ghg.1701","text":"Publisher Index Page"},{"id":361078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mount Simon Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91,\n 37\n ],\n [\n -84,\n 37\n ],\n [\n -84,\n 41\n ],\n [\n -91,\n 41\n ],\n [\n -91,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"6","noUsgsAuthors":false,"publicationDate":"2017-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Jahediesfanjani, Hossein 0000-0001-6281-5166 hjahediesfanjani@usgs.gov","orcid":"https://orcid.org/0000-0001-6281-5166","contributorId":193397,"corporation":false,"usgs":false,"family":"Jahediesfanjani","given":"Hossein","email":"hjahediesfanjani@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":756795,"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":756796,"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":756797,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198471,"text":"70198471 - 2017 - Tectonic evolution of the Central Andean Plateau and implications for the growth of plateaus","interactions":[],"lastModifiedDate":"2018-08-06T12:47:21","indexId":"70198471","displayToPublicDate":"2017-12-01T12:47:07","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":806,"text":"Annual Review of Earth and Planetary Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Tectonic evolution of the Central Andean Plateau and implications for the growth of plateaus","docAbstract":"Current end-member models for the geodynamic evolution of orogenic plateaus predict (a) slow and steady rise during crustal shortening and ablative subduction (i.e., continuous removal) of the lower lithosphere or (b) rapid surface uplift following shortening, which is associated with punctuated removal of dense lower lithosphere and/or lower crustal flow. This review integrates results from recent studies of the modern lithospheric structure, geologic evolution, and surface uplift history of the Central Andean Plateau to evaluate the geodynamic processes involved in forming it. Comparison of the timing, magnitude, and distribution of shortening and surface uplift, in combination with other geologic evidence, highlights the pulsed nature of plateau growth. We discuss specific regions and time periods that show evidence for end-member geodynamic processes, including middle–late Miocene surface uplift of the southern Eastern Cordillera and Altiplano associated with shortening and ablative subduction, latest Oligocene–early Miocene and late Miocene–early Pliocene punctuated removal of dense lower lithosphere in the Eastern Cordillera and Altiplano, and late Miocene–early Pliocene crustal flow in the central and northern Altiplano.
","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-earth-063016-020612","usgsCitation":"Garzione, C.N., McQuarrie, N., Perez, N.D., Ehlers, T.A., Beck, S.L., Kar, N., Eichelberger, N., Chapman, A.D., Ward, K.M., Ducea, M.N., Lease, R.O., Poulsen, C.J., Wagner, L.S., Saylor, J.E., Zandt, G., and Horton, B.K., 2017, Tectonic evolution of the Central Andean Plateau and implications for the growth of plateaus: Annual Review of Earth and Planetary Sciences, v. 45, p. 529-559, https://doi.org/10.1146/annurev-earth-063016-020612.","productDescription":"31 p.","startPage":"529","endPage":"559","ipdsId":"IP-080064","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":469252,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1146/annurev-earth-063016-020612","text":"Publisher Index 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S.","contributorId":206726,"corporation":false,"usgs":false,"family":"Wagner","given":"Lara","email":"","middleInitial":"S.","affiliations":[{"id":30217,"text":"Carnegie Institution for Science","active":true,"usgs":false}],"preferred":false,"id":741557,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Saylor, Joel E.","contributorId":206727,"corporation":false,"usgs":false,"family":"Saylor","given":"Joel","email":"","middleInitial":"E.","affiliations":[{"id":36391,"text":"University of Houston","active":true,"usgs":false}],"preferred":false,"id":741558,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Zandt, George","contributorId":206728,"corporation":false,"usgs":false,"family":"Zandt","given":"George","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":741559,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Horton, Brian 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Sea-level and Storm Impacts on Estuarine Environments and Shorelines (SSIEES) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a single-beam bathymetry survey within the estuarine, open-bay, and tidal creek environments of Grand Bay, Alabama-Mississippi, from May to June 2015. The goal of the SSIEES project is to assess the physical controls of sediment and material exchange between wetlands and estuarine environments along the northern Gulf of Mexico, specifically Grand Bay, Alabama-Mississippi; Vermilion Bay, Louisiana; and, along the east coast, within Chincoteague Bay, Virginia-Maryland. The data described in this report provide baseline bathymetric information for future research investigating wetland-marsh evolution, sediment transport, erosion, recent and long-term geomorphic change, and can also support the modeling of changes in response to restoration and storm impacts. The survey area encompasses more than 40 square kilometers of Grand Bay’s waters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1070","usgsCitation":"DeWitt, N.T., Stalk, C.A., Smith, C.G., Locker, S.D., Fredericks, J.J., McCloskey, T.A., and Wheaton, C.J., 2017, Single-beam bathymetry data collected in 2015 from Grand Bay, Alabama-Mississippi: U.S. Geological Survey Data Series 1070, https://doi.org/10.3133/ds1070.","productDescription":"HTML Document; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081056","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":349002,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1070","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1070"},{"id":349004,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7NP22M2","text":"USGS data release","description":"USGS data release","linkHelpText":"Single-Beam Bathymetry Data Collected in 2015 from Grand Bay, Mississippi/Alabama"},{"id":349001,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1070/coverthb.jpg"}],"country":"United States","state":"Alabama, Mississippi","otherGeospatial":"Grand Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.41487884521484,\n 30.328434677542585\n ],\n [\n -88.30467224121092,\n 30.328434677542585\n ],\n [\n -88.30467224121092,\n 30.419960083267238\n ],\n [\n -88.41487884521484,\n 30.419960083267238\n ],\n [\n -88.41487884521484,\n 30.328434677542585\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
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Climatic flux together with anthropogenic changes in land use and land cover pose major threats to wildlife, but our understanding of their combined impacts is limited. In arid southwestern North America, ferruginous pygmy-owls (Glaucidium brasilianum) are of major conservation concern due to marked declines in abundance linked to changes in land use and land cover during the past century. We reassessed abundance trends of pygmy-owls in northern Mexico across 17 years (2000-2016), which included data gathered over four additional years since inferences were last reported. We also assessed spatiotemporal trends in territory occupancy (n = 151 territories) across a much larger area that spanned 14 watershed regions in northern Mexico and adjacent Arizona over 16 years (2001-2016). Finally, we evaluated the influence of temperature, precipitation, land-use and land-cover change, spatial variation in local habitat quality, and interactions among these factors on occupancy dynamics. Large increases in abundance in 2015 and 2016 eliminated evidence of population declines that was described recently (e.g., Flesch 2014a) based on two modeling approaches. Moreover, there was little evidence of systematic temporal declines in territory occupancy across the broader bi-national study area, or for population units in Mexico and the adjacent U.S. Instead, occupancy dynamics varied at smaller spatial scales among watershed regions. We found that subpopulations in six regions declined or marginally declined across time, including two in the U.S. that declined to extinction; subpopulations in six other regions were stable; and those in two regions increased or marginally increased. Although variation in territory occupancy was associated with changes in temperature, precipitation, anthropogenic disturbance, and local differences in habitat quality, evidence for interactions among these factors was much greater than that for additive relationships. Territory occupancy declined with rising minimum air temperatures during winter at a much greater rate in disturbed landscapes compared to those with little to no anthropogenic disturbance. Moreover, occupancy increased with annual precipitation at increasingly positive rates as local territory quality increased. Such results suggest a complex set of processes simultaneously drove changes in territory occupancy, likely by influencing food abundance and the quantity, connectivity, and quality of habitat. Management focused on 1) protecting high-quality habitat, 2) enhancing and creating habitat (e.g., nest-cavity augmentation, riparian restoration), 3) reducing deleterious changes in land use and land cover, and 4) increasing landscape connectivity through both passive (e.g., landscape planning and restoration) and active (e.g., facilitated dispersal, translocations) techniques will enhance recovery prospects for pygmyowls.
","language":"English","publisher":"University of Arizona","collaboration":"U.S. Fish and Wildlife Service","usgsCitation":"Flesch, A., Nagler, P.L., Jarchow, C., and Alexander, R.B., 2017, Population trends, extinction risk, and conservation guidelines for ferruginous pygmy-owls in the Sonoran Desert, 38 p.","productDescription":"38 p.","ipdsId":"IP-088307","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":498555,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Sonoran Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.92108833595975,\n 32.77933725310251\n ],\n [\n -112.92108833595975,\n 30.54552222291086\n ],\n [\n -109.9911552778319,\n 30.54552222291086\n ],\n [\n -109.9911552778319,\n 32.77933725310251\n ],\n [\n -112.92108833595975,\n 32.77933725310251\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Flesch, Aaron","contributorId":213954,"corporation":false,"usgs":false,"family":"Flesch","given":"Aaron","affiliations":[{"id":38937,"text":"School of Natural Resources and the Environment, University of Arizona, The Desert Laboratory - 1675 Anklam Rd., Tucson, AZ 85745 flesch@email.arizona.edu","active":true,"usgs":false}],"preferred":false,"id":758803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":758802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jarchow, Christopher 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":196069,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":758804,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alexander, Richard B. 0000-0001-9166-0626 ralex@usgs.gov","orcid":"https://orcid.org/0000-0001-9166-0626","contributorId":541,"corporation":false,"usgs":true,"family":"Alexander","given":"Richard","email":"ralex@usgs.gov","middleInitial":"B.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":953605,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200008,"text":"70200008 - 2017 - Predictability and selection of hydrologic metrics in riverine ecohydrology","interactions":[],"lastModifiedDate":"2018-10-11T10:54:02","indexId":"70200008","displayToPublicDate":"2017-12-01T10:53:55","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Predictability and selection of hydrologic metrics in riverine ecohydrology","docAbstract":"The natural flow regime is critical to the health of riverine ecosystems. Many hydrologic metrics (HMs) have been developed to describe natural flow regimes, quantify flow alteration, and provide the hydrologic foundation for the development of environmental flow standards. Many applications require the use of models to predict expected natural values of HMs from basin characteristics at sites with no observed records of unimpaired flows. However, the error associated with HM estimation has not been evaluated. The primary goal of our study was to provide guidance for river scientists and managers in the selection, use, and interpretation of HMs for stream classification and hydroecological investigations of river ecosystems. We evaluated the predictability of a broad suite of HMs for the conterminous USA based on random forest statistical models. We also examined how the predictability of metrics varied among unique components of the flow regime. Roughly 40% of 612 HMs we examined could be predicted reliably from basin characteristics. The predictable metrics were disproportionately represented in 5 flow components: asymmetry, seasonality, magnitude, variability, and average monthly flows. Most metrics that represent extreme hydrological events (i.e., high and low flows) could not be reliably predicted. Roughly ⅔ of the evaluated HMs were incalculable or highly biased at intermittent/ephemeral streams because of the need for logarithmic transformations or scaling by other HMs, such as mean flows or percentile flow thresholds. Scaling metrics by drainage area tended to improve predictability. We recommend that the predictability of HMs be given greater consideration in studies and applications in which they are used to characterize and assess alteration of streamflow regimes.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/694912","usgsCitation":"Eng, K., Grantham, T., Carlisle, D.M., and Wolock, D.M., 2017, Predictability and selection of hydrologic metrics in riverine ecohydrology: Freshwater Science, v. 36, no. 4, p. 915-926, https://doi.org/10.1086/694912.","productDescription":"12 p.","startPage":"915","endPage":"926","ipdsId":"IP-086242","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":358272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc0309ae4b0fc368eb53a04","contributors":{"authors":[{"text":"Eng, Ken 0000-0001-6838-5849 keng@usgs.gov","orcid":"https://orcid.org/0000-0001-6838-5849","contributorId":3580,"corporation":false,"usgs":true,"family":"Eng","given":"Ken","email":"keng@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":747728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grantham, Theodore E.","contributorId":198855,"corporation":false,"usgs":false,"family":"Grantham","given":"Theodore E.","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":747729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":747730,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":747731,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202828,"text":"70202828 - 2017 - Effect of stocking and biotic and abiotic factors on Muskellunge recruitment in northern Wisconsin lakes","interactions":[],"lastModifiedDate":"2019-04-01T15:51:15","indexId":"70202828","displayToPublicDate":"2017-12-01T10:29:21","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Effect of stocking and biotic and abiotic factors on Muskellunge recruitment in northern Wisconsin lakes","docAbstract":"The Muskellunge Esox masquinongy is an important recreational fish species in North America. Some populations of Muskellunge are in decline, despite a reduction in harvest by anglers due largely to a growing catch-and-release ethic. Our objectives were to determine if Muskellunge recruitment was influenced by stocking, biotic factors, and abiotic factors in northern Wisconsin lakes. To address our first objective, we compared parameters of Ricker stock-recruit models from stocked and non-stocked lakes to determine whether stocking enhanced Muskellunge abundance. Density dependence of recruitment rates did not differ significantly between stocked and non-stocked lakes, but the recruitment rate was significantly higher in stocked lakes than in non-stocked lakes. This finding confirmed that Muskellunge stocking significantly increased recruitment in Wisconsin lakes, so stocking can continue to be used to supplement Muskellunge populations with low natural recruitment. To address our second objective, we tested biotic and abiotic variables in stock-recruit models as possible explanatory variables for Muskellunge recruitment in Wisconsin lakes. Adult stock density, stocked Muskellunge density, average spring temperature, spring temperature variation, and age-0 Walleye Sander vitreus abundance explained significant Muskellunge recruitment variation. Our findings indicate that Muskellunge recruitment is regulated by a mix of stocking, as well as abiotic and biotic environmental factors in northern Wisconsin lakes.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Muskellunge Management: Fifty Years of Cooperation Among Anglers, Scientists, and Fisheries Biologists","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Hugh C. Becker Memorial Muskellunge Symposium","conferenceDate":"March 13-15, 2016","conferenceLocation":"Minnetonka, Minnesota","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","usgsCitation":"Caspers, T.S., Hansen, M.J., and Hewett, S.W., 2017, Effect of stocking and biotic and abiotic factors on Muskellunge recruitment in northern Wisconsin lakes, in Muskellunge Management: Fifty Years of Cooperation Among Anglers, Scientists, and Fisheries Biologists, Minnetonka, Minnesota, March 13-15, 2016.","ipdsId":"IP-075596","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":362582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":362497,"type":{"id":15,"text":"Index Page"},"url":"https://fisheries.org/bookstore/all-titles/afs-symposia/54085c/"}],"country":"United 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W.","contributorId":214546,"corporation":false,"usgs":false,"family":"Hewett","given":"Steven","email":"","middleInitial":"W.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":760170,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263475,"text":"70263475 - 2017 - Geophysical characterization of seismic station sites in the United States – The importance of a flexible, multi-method approach","interactions":[],"lastModifiedDate":"2025-02-12T15:54:05.395998","indexId":"70263475","displayToPublicDate":"2017-12-01T09:49:56","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Geophysical characterization of seismic station sites in the United States – The importance of a flexible, multi-method approach","docAbstract":"Noninvasive geophysical site characterization methods were used in two recent projects to obtain shear-wave velocity (VS) profiles to a minimum depth of 30 m and the time-averaged VS of the upper 30 meters (VS30) at seismic station sites. These projects include the 2009 American Recovery and Reinvestment Act (ARRA) funded U.S. Geological Survey site characterization project for 191 sites in California and the Central-eastern United States (CEUS), and the 2012 Electric Power Research Institute (EPRI) funded project for 33 additional CEUS sites. These sites are located in rural to urban settings with topographic conditions ranging from relatively flat sedimentary basins to mountaintop ridges. About 60 percent of the ARRA sites and 80 percent of the EPRI sites are located on rock or have thin sediment cover over rock, including Quaternary volcanic rock, Tertiary sediments and sedimentary rock, and Mesozoic (or older) crystalline or sedimentary rock. The remaining sites consist of thick sequences of Quaternary sediments overlying older sediments and rock.
ARRA sites were characterized using non-invasive active and passive surface-wave methods, including the horizontal-tovertical spectral ratio (HVSR) method and one or more of the following: spectral analysis of surface waves (SASW), multichannel analysis of surface waves (MASW; Rayleigh and Love waves) and, occasionally, array microtremor (linear and 2-D arrays) methods. P-wave seismic refraction data were also acquired at rock and shallow-rock sites. S-wave seismic refraction and/or Love-wave MASW methods were applied at sites where characterization proved difficult with Rayleighwave methods. Based on our experience from the ARRA project, we acquired Rayleigh- and Love-wave based MASW and P- and S-wave refraction data for the EPRI project at CEUS sites.
The HVSR method was found to be useful for identifying shallow-rock sites and for evaluating the relative variability of the depth-to-rock interface beneath the seismic station and the testing array(s). The fundamental mode modeling assumption was generally valid at most of these sites; nevertheless, multi-mode or effective-mode modeling routines were occasionally required, particularly in the case of shallow high-velocity layers. Deep sediment sites were characterized using active and, when appropriate, passive surface-wave based methods. Rock and shallow sediment sites were generally more challenging to characterize than deep sediment sites. About 10 percent of rock sites could not be characterized using surface wave methods, thus these sites were characterized using body-wave refraction methods. Love wave methods were found to be more effective than Rayleigh wave methods at some rock and shallow-rock sites (e.g., sites with shallow rock and sites with a thin low-velocity, highly attenuating surface layer). Lateral velocity variability was found to be very common at rock and shallow-rock sites, often causing significant scatter in the surface-wave dispersion data. Seismic refraction models have demonstrated that it may not be unusual for VS30 to vary by 20 percent, or more, over small distances (several tens of meters) at such sites. Based on these experiences, it is important to consider the application of combinations of methods when using noninvasive geophysical approaches to characterize seismic site conditions.
","conferenceTitle":"16th World Conference on Earthquake Engineering, 16WCEE 2017","conferenceDate":"January 9-13, 2017","conferenceLocation":"Santiago, Chile","language":"English","publisher":"International Association for Earthquake Engineering","usgsCitation":"Martin, A., Yong, A., Stephenson, W.J., Boatwright, J., and Diehl, J., 2017, Geophysical characterization of seismic station sites in the United States – The importance of a flexible, multi-method approach, 16th World Conference on Earthquake Engineering, 16WCEE 2017, Santiago, Chile, January 9-13, 2017, 19 p.","productDescription":"19 p.","ipdsId":"IP-080676","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":481977,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.wcee.nicee.org/wcee/sixteenth_conf_Santiago/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.07855248193185,\n 32.53666625001908\n ],\n [\n -114.30928863190336,\n 32.63838082249163\n ],\n [\n -114.18940679698169,\n 34.53764946137473\n ],\n [\n -119.39424118924363,\n 38.572056705043025\n ],\n [\n -123.29737686526406,\n 37.63629841187134\n ],\n [\n -120.31399583477251,\n 34.0619554841515\n ],\n [\n -117.07855248193185,\n 32.53666625001908\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -98.56029556803429,\n 36.997446902950074\n ],\n [\n -99.86195232972082,\n 34.14086982696833\n ],\n [\n -91.74686942614534,\n 33.02956856409422\n ],\n [\n -84.68084295679529,\n 31.754844006785248\n ],\n [\n -81.4025521969889,\n 32.03675981430574\n ],\n [\n -76.00210444134004,\n 35.756079891470606\n ],\n [\n -71.27311244517016,\n 44.469348399372535\n ],\n [\n -74.529776508883,\n 45.025831483992505\n ],\n [\n -77.26839093048407,\n 43.03532376235151\n ],\n [\n -81.20361675467349,\n 41.569243273876594\n ],\n [\n -86.76267624679905,\n 41.9776316577331\n ],\n [\n -91.49798799968512,\n 40.22868842092885\n ],\n [\n -98.56029556803429,\n 36.997446902950074\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Martin, Antony","contributorId":243672,"corporation":false,"usgs":false,"family":"Martin","given":"Antony","affiliations":[],"preferred":false,"id":927099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":695,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boatwright, J.","contributorId":87297,"corporation":false,"usgs":true,"family":"Boatwright","given":"J.","email":"","affiliations":[],"preferred":false,"id":927172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diehl, John","contributorId":350842,"corporation":false,"usgs":false,"family":"Diehl","given":"John","affiliations":[{"id":83844,"text":"GEOVision, Incorporated","active":true,"usgs":false}],"preferred":false,"id":927102,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236150,"text":"70236150 - 2017 - Evidence that recent warming is reducing upper Colorado River flows","interactions":[],"lastModifiedDate":"2022-08-30T13:30:45.991635","indexId":"70236150","displayToPublicDate":"2017-12-01T08:29:28","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Evidence that recent warming is reducing upper Colorado River flows","docAbstract":"The upper Colorado River basin (UCRB) is one of the primary sources of water for the western United States, and increasing temperatures likely will elevate the risk of reduced water supply in the basin. Although variability in water-year precipitation explains more of the variability in water-year UCRB streamflow than water-year UCRB temperature, since the late 1980s, increases in temperature in the UCRB have caused a substantial reduction in UCRB runoff efficiency (the ratio of streamflow to precipitation). These reductions in flow because of increasing temperatures are the largest documented temperature-related reductions since record keeping began. Increases in UCRB temperature over the past three decades have resulted in a mean UCRB water-year streamflow departure of −1306 million m3 (or −7% of mean water-year streamflow). Additionally, warm-season (April through September) temperature has had a larger effect on variability in water-year UCRB streamflow than the cool-season (October through March) temperature. The greater contribution of warm-season temperature, relative to cool-season temperature, to variability of UCRB flow suggests that evaporation or snowmelt, rather than changes from snow to rain during the cool season, has driven recent reductions in UCRB flow. It is expected that as warming continues, the negative effects of temperature on water-year UCRB streamflow will become more evident and problematic.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/EI-D-17-0007.1","usgsCitation":"McCabe, G.J., Wolock, D.M., Pederson, G.T., Woodhouse, C.A., and McAfee, S., 2017, Evidence that recent warming is reducing upper Colorado River flows: Earth Interactions, v. 21, no. 10, p. 1-14, https://doi.org/10.1175/EI-D-17-0007.1.","productDescription":"14 p.","startPage":"1","endPage":"14","ipdsId":"IP-082888","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":469255,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/ei-d-17-0007.1","text":"Publisher Index Page"},{"id":405898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"upper Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.90673828125,\n 36.52288052805137\n ],\n [\n -111.796875,\n 36.48755716938576\n ],\n [\n -108.65478515625,\n 35.40696093270201\n ],\n [\n -108.28125,\n 35.53222622770337\n ],\n [\n -107.09472656249999,\n 36.56260003738545\n ],\n [\n -106.41357421875,\n 38.13455657705411\n ],\n [\n -105.5126953125,\n 39.57182223734374\n ],\n [\n -105.62255859375,\n 40.22921818870117\n ],\n [\n -106.74316406249999,\n 41.47566020027821\n ],\n [\n -108.017578125,\n 43.03677585761058\n ],\n [\n -109.62158203125,\n 43.50075243569041\n ],\n [\n -110.478515625,\n 43.54854811091286\n ],\n [\n -110.80810546875,\n 43.29320031385282\n ],\n [\n -110.93994140625,\n 41.672911819602085\n ],\n [\n -111.15966796875,\n 41.42625319507269\n ],\n [\n -111.46728515624999,\n 40.613952441166596\n ],\n [\n -112.0166015625,\n 39.58875727696545\n ],\n [\n -112.30224609374999,\n 38.09998264736481\n ],\n [\n -112.32421875,\n 37.125286284966805\n ],\n [\n -111.90673828125,\n 36.52288052805137\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"10","noUsgsAuthors":false,"publicationDate":"2017-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - 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2017 - Correcting spacecraft jitter in HiRISE images","interactions":[],"lastModifiedDate":"2018-03-13T17:21:17","indexId":"70195364","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"seriesTitle":{"id":5650,"text":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","onlineIssn":"2194-9034","printIssn":"1682-1750","active":true,"publicationSubtype":{"id":19}},"title":"Correcting spacecraft jitter in HiRISE images","docAbstract":"Mechanical oscillations or vibrations on spacecraft, also called pointing jitter, cause geometric distortions and/or smear in high resolution digital images acquired from orbit. Geometric distortion is especially a problem with pushbroom type sensors, such as the High Resolution Imaging Science Experiment (HiRISE) instrument on board the Mars Reconnaissance Orbiter (MRO). Geometric distortions occur at a range of frequencies that may not be obvious in the image products, but can cause problems with stereo image correlation in the production of digital elevation models, and in measuring surface changes over time in orthorectified images. The HiRISE focal plane comprises a staggered array of fourteen charge-coupled devices (CCDs) with pixel IFOV of 1 microradian. The high spatial resolution of HiRISE makes it both sensitive to, and an excellent recorder of jitter. We present an algorithm using Fourier analysis to resolve the jitter function for a HiRISE image that is then used to update instrument pointing information to remove geometric distortions from the image. Implementation of the jitter analysis and image correction is performed on selected HiRISE images. Resulting corrected images and updated pointing information are made available to the public. Results show marked reduction of geometric distortions. This work has applications to similar cameras operating now, and to the design of future instruments (such as the Europa Imaging System).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings: 2017 international symposium on planetary remote sensing and mapping (Volume XLII-3/W1)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2017 International Symposium on Planetary Remote Sensing and Mapping","conferenceDate":"August 13-16, 2017","conferenceLocation":"Hong Kong","language":"English","publisher":"International Society for Photogrammetry and Remote Sensing","doi":"10.5194/isprs-archives-XLII-3-W1-141-2017","usgsCitation":"Sutton, S.S., Boyd, A., Kirk, R.L., Cook, D., Backer, J., Fennema, A., Heyd, R., McEwen, A., and Mirchandani, S., 2017, Correcting spacecraft jitter in HiRISE images, in Proceedings: 2017 international symposium on planetary remote sensing and mapping (Volume XLII-3/W1), v. 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The Dotson Zone comprises a series of felsic dikes that extend from the southeast margin of the composite pluton and may represent an important resource of critical HREEs. Petrographically, the primary igneous mineral assemblage is altered by late-igneous and hydrothermal fluids resulting in redistribution and enrichment of REEs. An area of flexure in the southeastern end of the Dotson Zone was the primary locus of enrichment as shown by the pervasive alteration and consistently high REE+Y values. We favor a model in which the dikes were emplaced concurrently with the marginal intrusions, and then altered during emplacement of the inner, main intrusion in a relatively rapid series of overlapping intrusive and late magmatic fluid-high temperature hydrothermal events as the complex cooled. A much later sodic intrusive event focused on the BMIC may have resulted in additional silica-Na-Zr-rich alteration in proximity to the pluton.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 14th SGA Biennial Meeting","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"14th SGA Biennial Meeting","conferenceDate":"August 20-23, 2017","conferenceLocation":"Québec City, Canada","language":"English","publisher":"The Society for Geology Applied to Mineral Deposits","usgsCitation":"Taylor, C.D., Lowers, H.A., Adams, D., and Robinson, R.J., 2017, Geochemistry and mineralogy of the Dotson Zone HREE deposit in the Bokan Mountain peralkaline igneous complex, southeastern Alaska, USA, in Proceedings of the 14th SGA Biennial Meeting, Québec City, Canada, August 20-23, 2017, p. 1329-1332.","productDescription":"4 p.","startPage":"1329","endPage":"1332","ipdsId":"IP-084921","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":352128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee7abe4b0da30c1bfc349","contributors":{"authors":[{"text":"Taylor, Cliff D. 0000-0001-6376-6298 ctaylor@usgs.gov","orcid":"https://orcid.org/0000-0001-6376-6298","contributorId":1283,"corporation":false,"usgs":true,"family":"Taylor","given":"Cliff","email":"ctaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":718793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowers, Heather A. 0000-0001-5360-9264 hlowers@usgs.gov","orcid":"https://orcid.org/0000-0001-5360-9264","contributorId":191307,"corporation":false,"usgs":true,"family":"Lowers","given":"Heather","email":"hlowers@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":718794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, David 0000-0003-2679-2344 dadams@usgs.gov","orcid":"https://orcid.org/0000-0003-2679-2344","contributorId":199358,"corporation":false,"usgs":true,"family":"Adams","given":"David","email":"dadams@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":169,"text":"Central Mineral Resources Team","active":false,"usgs":true}],"preferred":false,"id":718795,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robinson, R. 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The geodetic network in central Washington has been used to interpret large-scale N-S shortening and westward-increasing strain; however, geodetic data are unable to resolve shortening rates across individual structures in this low-strain-rate environment. Resolving fault geometries, slip rates, and timing of faulting in the Yakima fold province is critically important to seismic hazard assessment for nearby infrastructure and population centers.
The Saddle Mountains anticline is one of the most prominent Yakima folds. It is unique within the Yakima fold province in that the syntectonic strata of the Ringold Formation are preserved and provide a record of deformation and drainage reorganization. Here, we present new stratigraphic columns, U-Pb zircon tephra ages, U-series caliche ages, and geophysical modeling that constrain two line-balanced and retrodeformed cross sections. These new constraints indicate that the Saddle Mountains anticline has accommodated 1.0−1.3 km of N-S shortening since 10 Ma, that shortening increases westward along the anticline, and that the average slip rate has increased 6-fold since 6.8 Ma. Provenance analysis suggests that the source terrane for the Ringold Formation was similar to that of the modern Snake River Plain. Using new slip rates and structural constraints, we calculate the strain accumulation time, interpretable as a recurrence interval, for earthquakes on the Saddle Mountains fault and find that large-magnitude earthquakes could rupture along the Saddle Mountains fault every 2−11 k.y.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31783.1","usgsCitation":"Staisch, L.M., Kelsey, H., Sherrod, B.L., Moller, A., Paces, J.B., Blakely, R.J., and Styron, R., 2017, Miocene−Pleistocene deformation of the Saddle Mountains: Implications for seismic hazard in central Washington, USA: GSA Bulletin, v. 130, no. 3-4, p. 411-437, https://doi.org/10.1130/B31783.1.","productDescription":"27 p.","startPage":"411","endPage":"437","ipdsId":"IP-084555","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":349635,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120,\n 46.5\n ],\n [\n -119,\n 46.5\n ],\n [\n -119,\n 47\n ],\n [\n -120,\n 47\n ],\n [\n -120,\n 46.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"130","issue":"3-4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-10","publicationStatus":"PW","scienceBaseUri":"5a60faf7e4b06e28e9c22a29","contributors":{"authors":[{"text":"Staisch, Lydia M. 0000-0002-1414-5994 lstaisch@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-5994","contributorId":167068,"corporation":false,"usgs":true,"family":"Staisch","given":"Lydia","email":"lstaisch@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":724269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelsey, Harvey","contributorId":106978,"corporation":false,"usgs":true,"family":"Kelsey","given":"Harvey","affiliations":[],"preferred":false,"id":724270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":724271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moller, Andreas","contributorId":201081,"corporation":false,"usgs":false,"family":"Moller","given":"Andreas","email":"","affiliations":[],"preferred":false,"id":724272,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paces, James B. 0000-0002-9809-8493 jbpaces@usgs.gov","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":2514,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"jbpaces@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":724273,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724274,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Styron, Richard","contributorId":201082,"corporation":false,"usgs":false,"family":"Styron","given":"Richard","email":"","affiliations":[],"preferred":false,"id":724275,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195105,"text":"70195105 - 2017 - Probabilistic tsunami hazard analysis: Multiple sources and global applications","interactions":[],"lastModifiedDate":"2018-02-07T17:58:48","indexId":"70195105","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3283,"text":"Reviews of Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Probabilistic tsunami hazard analysis: Multiple sources and global applications","docAbstract":"Applying probabilistic methods to infrequent but devastating natural events is intrinsically challenging. For tsunami analyses, a suite of geophysical assessments should be in principle evaluated because of the different causes generating tsunamis (earthquakes, landslides, volcanic activity, meteorological events, and asteroid impacts) with varying mean recurrence rates. Probabilistic Tsunami Hazard Analyses (PTHAs) are conducted in different areas of the world at global, regional, and local scales with the aim of understanding tsunami hazard to inform tsunami risk reduction activities. PTHAs enhance knowledge of the potential tsunamigenic threat by estimating the probability of exceeding specific levels of tsunami intensity metrics (e.g., run-up or maximum inundation heights) within a certain period of time (exposure time) at given locations (target sites); these estimates can be summarized in hazard maps or hazard curves. This discussion presents a broad overview of PTHA, including (i) sources and mechanisms of tsunami generation, emphasizing the variety and complexity of the tsunami sources and their generation mechanisms, (ii) developments in modeling the propagation and impact of tsunami waves, and (iii) statistical procedures for tsunami hazard estimates that include the associated epistemic and aleatoric uncertainties. Key elements in understanding the potential tsunami hazard are discussed, in light of the rapid development of PTHA methods during the last decade and the globally distributed applications, including the importance of considering multiple sources, their relative intensities, probabilities of occurrence, and uncertainties in an integrated and consistent probabilistic framework.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017RG000579","usgsCitation":"Grezio, A., Babeyko, A., Baptista, M., Behrens, J., Costa, A., Davies, G., Geist, E.L., Glimsdal, S., Gonzalez, F.I., Griffin, J., Harbitz, C.B., LeVeque, R.J., Lorito, S., Løvholt, F., Omira, R., Mueller, C., Paris, R., Parsons, T.E., Polet, J., Power, W., Selva, J., Sorensen, M.B., and Thio, H., 2017, Probabilistic tsunami hazard analysis: Multiple sources and global applications: Reviews of Geophysics, v. 55, no. 4, p. 1158-1198, https://doi.org/10.1002/2017RG000579.","productDescription":"41 p.","startPage":"1158","endPage":"1198","ipdsId":"IP-088600","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":461335,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017rg000579","text":"Publisher Index 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Bergen","active":true,"usgs":false}],"preferred":false,"id":726972,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Thio, Hong Kie","contributorId":52070,"corporation":false,"usgs":false,"family":"Thio","given":"Hong Kie","affiliations":[{"id":13386,"text":"AECOM","active":true,"usgs":false}],"preferred":false,"id":726973,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70196469,"text":"70196469 - 2017 - LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes","interactions":[],"lastModifiedDate":"2018-04-10T10:56:16","indexId":"70196469","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5091,"text":"GigaScience","active":true,"publicationSubtype":{"id":10}},"title":"LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes","docAbstract":"Understanding the factors that affect water quality and the ecological services provided by freshwater ecosystems is an urgent global environmental issue. Predicting how water quality will respond to global changes not only requires water quality data, but also information about the ecological context of individual water bodies across broad spatial extents. Because lake water quality is usually sampled in limited geographic regions, often for limited time periods, assessing the environmental controls of water quality requires compilation of many data sets across broad regions and across time into an integrated database. LAGOS-NE accomplishes this goal for lakes in the northeastern-most 17 US states.
LAGOS-NE contains data for 51 101 lakes and reservoirs larger than 4 ha in 17 lake-rich US states. The database includes 3 data modules for: lake location and physical characteristics for all lakes; ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes; and in situ measurements of lake water quality for a subset of the lakes from the past 3 decades for approximately 2600–12 000 lakes depending on the variable. The database contains approximately 150 000 measures of total phosphorus, 200 000 measures of chlorophyll, and 900 000 measures of Secchi depth. The water quality data were compiled from 87 lake water quality data sets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This database is one of the largest and most comprehensive databases of its type because it includes both in situ measurements and ecological context data. Because ecological context can be used to study a variety of other questions about lakes, streams, and wetlands, this database can also be used as the foundation for other studies of freshwaters at broad spatial and ecological scales.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gigascience/gix101","usgsCitation":"Soranno, P.A., Bacon, L.C., Beauchene, M., Bednar, K.E., Bissell, E.G., Boudreau, C.K., Boyer, M.G., Bremigan, M.T., Carpenter, S.R., Carr, J.W., Cheruvelil, K.S., Christel, S.T., Claucherty, M., Collins, S.M., Conroy, J.D., Downing, J.A., Dukett, J., Fergus, C.E., Filstrup, C.T., Funk, C., Gonzalez, M.J., Green, L.T., Gries, C., Halfman, J.D., Hamilton, S.K., Hanson, P.C., Henry, E.N., Herron, E.M., Hockings, C., Jackson, J.R., Jacobson-Hedin, K., Janus, L.L., Jones, W.W., Jones, J., Keson, C.M., King, K.B., Kishbaugh, S.A., Lapierre, J., Lathrop, B., Latimore, J.A., Lee, Y., Lottig, N.R., Lynch, J.A., Matthews, L.J., McDowell, W.H., Moore, K.E., Neff, B., Nelson, S.J., Oliver, S., Pace, M.L., Pierson, D.C., Poisson, A.C., Pollard, A.I., Post, D.M., Reyes, P.O., Rosenberry, D., Roy, K.M., Rudstam, L.G., Sarnelle, O., Schuldt, N.J., Scott, C.E., Skaff, N.K., Smith, N.J., Spinelli, N.R., Stachelek, J.J., Stanley, E.H., Stoddard, J.L., Stopyak, S.B., Stow, C.A., Tallant, J.M., Tan, P., Thorpe, A.P., Vanni, M.J., Wagner, T., Watkins, G., Weathers, K.C., Webster, K.E., White, J., Wilmes, M.K., and Yuan, S., 2017, LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes: GigaScience, v. 6, no. 12, p. 1-22, https://doi.org/10.1093/gigascience/gix101.","productDescription":"22 p.","startPage":"1","endPage":"22","ipdsId":"IP-088165","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":469264,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gigascience/gix101","text":"Publisher Index Page"},{"id":353287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Iowa, Illinois, Indiana, Massachusetts, Maine, Michigan, Missouri, Minnesota, New Hampshire, New Jersey, New York, Ohio, Pennsylvania, Rhode Island, Vermont, 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Thermal stratification and the subsequent formation of benthic hypoxia may result in nymph mortality. Our goal was to identify potential associations between recent increases in temperature and eutrophication, which exacerbate hypoxic events in lakes, and mayfly populations in Lake Erie. Nymphs were collected during April–May 1999–2014. We used wind and temperature data to calculate four measures of thermal stratification, which drives hypoxic events, during summers of 1998–2013. Bottom trawl data collected during August 1998–2013 were used to estimate annual biomass of fishes known to be predators of mayfly nymphs. We used Akaike's Information Criterion to identify the best one- and two-predictor regression models of annual population densities (N/m2) of age-1 and age-2 nymphs, in which candidate predictors included the four measures of stratification, predator fish biomass, competition, and population densities of age-2 (for age-1) and age-1 (for age-2) nymphs from the previous year. Densities of both age classes of nymphs declined over the time series. Population densities of age-1 and age-2 nymphs from the previous year best predicted annual population densities of nymphs of both age classes. However, hypoxic conditions (indicated by stratification) and predation both had negative effects on annual population density of mayflies. Compared with predation, hypoxia had an inconsistent effect on annual nymph density. The increases in temperature and eutrophication in Lake Erie, which exacerbate hypoxic events, may have drastic effects on the mayfly populations.
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For waterbirds, attachment of transmitters with subcutaneous anchors has been an effective and well-established technique, having been used on >40 species. This method was recently modified to include a second subcutaneous anchor, presumably increasing transmitter retention beyond that of single-anchor attachments. This putative benefit may be offset, however, by increased health risks related to additional incisions and subcutaneous protrusions. To test this potential trade-off, we attached radiotransmitters to molting and wintering surf (Melanitta perspicillata) and white-winged scoters (M. fusca) during 2008 and 2009 in Washington State and southeast Alaska, USA, using single- (121 scoters) and double-anchor (128 scoters) attachment techniques. We estimated daily probabilities of survival and radio retention for each group, this being apparent retention for wintering scoters because we could not differentiate shed transmitters from flighted emigration. For scoters during the flightless remigial molt, we found that addition of a second anchor increased cumulative retention probability (±SE) over a 49-day period from 0.69 ± 0.11 for single-anchor to 0.88 ± 0.07 for double-anchor attachments, while having no effect on survival. However, during winter, scoters with double-anchor attachments experienced no improvement in apparent retention, while having significantly lower survival during their first 14 days following transmitter attachment; of 15 mortalities during this period, 11 had 2 subcutaneous anchors. From day 15 onward, winter survival rates were nearly identical for single- versus double-anchor attachments, indicating that adverse effects of subcutaneous anchors were mainly limited to the 14-day postattachment period. Overall, given that the survival cost of adding a second subcutaneous anchor was substantial for wintering scoters—decreasing 14-day survival by 12% for adults and 23% for juveniles—we recommend that researchers opt for single-anchor attachments under most circumstances, especially during winter when birds may be energetically challenged.
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