Consumption of telemetered fishes by piscivores is problematic for telemetry studies because tag detections from the piscivore could introduce bias into the analysis of telemetry data. We illustrate the use of multivariate mixture models to estimate group membership (smolt or predator) of telemetered juvenile Chinook salmon (Oncorhynchus tshawytscha), juvenile steelhead trout (O. mykiss), striped bass (Morone saxatilis), smallmouth bass (Micropterus dolomieu) and spotted bass (M. punctulatus) in the Sacramento River, CA, USA. First, we estimated two types of track statistics from spatially explicit two-dimensional movement tracks of telemetered fishes: the Lévy exponent (b) and tortuosity (τ). Second, we hypothesized that the distribution of each track statistic would differ between predators and smolts. To estimate the distribution of track statistics for putative predators and smolts, we fitted a bivariate normal mixture model to the mixed distribution of track statistics. Lastly, we classified each track as a smolt or predator using parameter estimates from the mixture model to estimate the probability that each track was that of a predator or smolt.
\nTracks classified as predators exhibited movement that was tortuous and consistent with prey searching tactics, whereas tracks classified as smolts were characterized by directed, linear downstream movement. The estimated mean tortuosity was 0.565 (SD = 0.07) for predators and 0.944 (SD = 0.001) for smolts. The estimated mean Lévy exponent was 1.84 (SD = 1.23) for predators and -0.304 (SD = 1.46) for smolts. We correctly classified 90% of the Micropterus species and 72% of the striped bass as predators. For tagged smolts, 80% of Chinook salmon and 74% of steelhead trout were not classified as predators.
\nMixture models proved valuable as a means to differentiate between salmonid smolts and predators that consumed salmonid smolts. However, successful application of this method requires that telemetered fishes and their predators exhibit measurable differences in movement behavior. Our approach is flexible, allows inclusion of multiple track statistics and improves upon rule-based manual classification methods.
\nGiven the large amount of resources required for long-term control or eradication projects, it is important to assess strategies and associated costs and outcomes before a particular plan is implemented. We developed a population model to assess the cost-effectiveness of mechanical removal strategies for suppressing long-term abundance of nonnative Lake Trout Salvelinus namaycush in Swan Lake, Montana. We examined the efficacy of targeting life stages (i.e., juveniles or adults) using temporally pulsed fishing effort for reducing abundance and program cost. Exploitation rates were high (0.80 for juveniles and 0.68 for adults) compared with other lakes in the western USA with Lake Trout suppression programs. Harvesting juveniles every year caused the population to decline, whereas harvesting only adults caused the population to increase above carrying capacity. Simultaneous harvest of juveniles and adults was required to cause the population to collapse (i.e., 95% reduction relative to unharvested abundance) with 95% confidence. The population could collapse within 15 years for a total program cost of US$1,578,480 using the most aggressive scenario. Substantial variation in cost existed among harvest scenarios for a given reduction in abundance; however, total program cost was minimized when collapse was rapid. Our approach provides a useful case study for evaluating long-term mechanical removal options for fish populations that are not likely to be eradicated.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/02755947.2013.824935","usgsCitation":"Syslo, J.M., Guy, C.S., and Cox, B.S., 2013, Comparison of harvest scenarios for the cost-effective suppression of Lake Trout in Swan Lake, Montana: North American Journal of Fisheries Management, v. 33, no. 6, p. 1079-1090, https://doi.org/10.1080/02755947.2013.824935.","productDescription":"12 p.","startPage":"1079","endPage":"1090","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-046340","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":325037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Swan Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.99276733398438,\n 47.9085180470967\n ],\n [\n -113.99276733398438,\n 48.02162055064295\n ],\n [\n -113.83415222167969,\n 48.02162055064295\n ],\n [\n -113.83415222167969,\n 47.9085180470967\n ],\n [\n -113.99276733398438,\n 47.9085180470967\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-10-10","publicationStatus":"PW","scienceBaseUri":"5784c338e4b0e02680be591a","contributors":{"authors":[{"text":"Syslo, John M.","contributorId":171452,"corporation":false,"usgs":false,"family":"Syslo","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":642126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":518195,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cox, Benjamin S.","contributorId":105158,"corporation":false,"usgs":true,"family":"Cox","given":"Benjamin","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":642127,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70059777,"text":"70059777 - 2013 - Breeding site heterogeneity reduces variability in frog recruitment and population dynamics","interactions":[],"lastModifiedDate":"2014-02-14T09:48:01","indexId":"70059777","displayToPublicDate":"2014-01-24T10:23:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Breeding site heterogeneity reduces variability in frog recruitment and population dynamics","docAbstract":"Environmental stochasticity can have profound effects on the dynamics and viability of wild populations, and habitat heterogeneity provides one mechanism by which populations may be buffered against the negative effects of environmental fluctuations. Heterogeneity in breeding pond hydroperiod across the landscape may allow amphibian populations to persist despite variable interannual precipitation. We examined recruitment dynamics over 10 yr in a high-elevation Columbia spotted frog (Rana luteiventris) population that breeds in ponds with a variety of hydroperiods. We combined these data with matrix population models to quantify the consequences of heterogeneity in pond hydroperiod on net recruitment (i.e. number of metamorphs produced) and population growth rates. We compared our heterogeneous system to hypothetical homogeneous environments with only ephemeral ponds, only semi-permanent ponds, and only permanent ponds. We also examined the effects of breeding pond habitat loss on population growth rates. Most eggs were laid in permanent ponds each year, but survival to metamorphosis was highest in the semi-permanent ponds. Recruitment success varied by both year and pond type. Net recruitment and stochastic population growth rate were highest under a scenario with homogeneous semi-permanent ponds, but variability in recruitment was lowest in the scenario with the observed heterogeneity in hydroperiods. Loss of pond habitat decreased population growth rate, with greater decreases associated with loss of permanent and semi-permanent habitat. The presence of a diversity of pond hydroperiods on the landscape will influence population dynamics, including reducing variability in recruitment in an uncertain climatic future.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biological Conservation","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2013.12.013","usgsCitation":"McCaffery, R., Eby, L.A., Maxell, B.A., and Corn, P., 2013, Breeding site heterogeneity reduces variability in frog recruitment and population dynamics: Biological Conservation, v. 170, p. 169-176, https://doi.org/10.1016/j.biocon.2013.12.013.","productDescription":"8 p.","startPage":"169","endPage":"176","ipdsId":"IP-053191","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":282379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282378,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.biocon.2013.12.013"}],"country":"United States","state":"Montana","otherGeospatial":"Little Rock Creek Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.977216,47.725464 ], [ -114.977216,47.729912 ], [ -114.938275,47.729912 ], [ -114.938275,47.725464 ], [ -114.977216,47.725464 ] ] ] } } ] }","volume":"170","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5351702ae4b05569d805a180","contributors":{"authors":[{"text":"McCaffery, Rebecca M.","contributorId":57364,"corporation":false,"usgs":true,"family":"McCaffery","given":"Rebecca M.","affiliations":[],"preferred":false,"id":487805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eby, Lisa A.","contributorId":42910,"corporation":false,"usgs":true,"family":"Eby","given":"Lisa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":487804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maxell, Bryce A.","contributorId":100113,"corporation":false,"usgs":true,"family":"Maxell","given":"Bryce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":487806,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Corn, Paul Stephen 0000-0002-4106-6335","orcid":"https://orcid.org/0000-0002-4106-6335","contributorId":107379,"corporation":false,"usgs":true,"family":"Corn","given":"Paul Stephen","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":487807,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70058777,"text":"ofr20131279 - 2013 - Native Prairie Adaptive Management: a multi region adaptive approach to invasive plant management on Fish and Wildlife Service owned native prairies","interactions":[],"lastModifiedDate":"2017-10-20T12:08:32","indexId":"ofr20131279","displayToPublicDate":"2014-01-24T08:16:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1279","title":"Native Prairie Adaptive Management: a multi region adaptive approach to invasive plant management on Fish and Wildlife Service owned native prairies","docAbstract":"Much of the native prairie managed by the U.S. Fish and Wildlife Service (FWS) in the Prairie Pothole Region (PPR) of the northern Great Plains is extensively invaded by the introduced cool-season grasses, smooth brome (Bromus inermis) and Kentucky bluegrass (Poa pratensis). Management to suppress these invasive plants has had poor to inconsistent success. The central challenge to managers is selecting appropriate management actions in the face of biological and environmental uncertainties. In partnership with the FWS, the U.S. Geological Survey (USGS) developed an adaptive decision support framework to assist managers in selecting management actions under uncertainty and maximizing learning from management outcomes. This joint partnership is known as the Native Prairie Adaptive Management (NPAM) initiative. The NPAM decision framework is built around practical constraints faced by FWS refuge managers and includes identification of the management objective and strategies, analysis of uncertainty and construction of competing decision models, monitoring, and mechanisms for model feedback and decision selection. Nineteen FWS field stations, spanning four states of the PPR, have participated in the initiative. These FWS cooperators share a common management objective, available management strategies, and biological uncertainties. Though the scope is broad, the initiative interfaces with individual land managers who provide site-specific information and receive updated decision guidance that incorporates understanding gained from the collective experience of all cooperators. We describe the technical components of this approach, how the components integrate and inform each other, how data feedback from individual cooperators serves to reduce uncertainty across the whole region, and how a successful adaptive management project is coordinated and maintained on a large scale.
\nDuring an initial scoping workshop, FWS cooperators developed a consensus management objective: increase the composition of native grasses and forbs on native sod while minimizing cost. Cooperators agreed that decision guidance should be provided annually and should account for local, real-time vegetation conditions observed on the ground. Over the course of development, two prototypes of the decision framework were considered. The final framework recognized four alternative actions that managers could take in any given year: (1) Graze—targeted use of grazing ungulates to achieve defoliation, (2) Burn—application of prescribed fire as the single form of defoliation, (3) Burn/Graze—a combination treatment, and (4) Rest—no action. The study area included northern mixed-grass and tallgrass prairie. Native vegetation in mixed–grass prairie has a strong cool-season component and thus the dominant native species have a phenology similar to that of smooth brome and Kentucky bluegrass, making management of those species challenging. In contrast, tallgrass prairie has a strong warm-season native component, leading to an existence of cool-season windows, periods of time in the fall and spring when cool‐season invasive grass species are actively growing and vulnerable to damage via select management actions, but warm‐season grass species are not active and are thus less susceptible to damage via the same actions. This dichotomy between prairie types necessitated the development of separate but parallel decision support systems for mixed-grass and tallgrass biomes.
\nManagement units are parcels of native prairie that receive a single management treatment at any one time over their entire extent. At any particular time, the vegetation state of each management unit is characterized by the amount of cover of native grasses and forbs and the type of invasive grass that is dominant. In addition, each unit has a defoliation state which reflects the number of years since the last defoliation event and an index to how intensively the unit was managed during the previous 7 years. State-transition models are used to predict the state of a management unit in year t+1 from its state in year t and a prescribed management action that was applied between the two monitoring events. Alternative models are built around key uncertainties that make choice of a management action difficult. Three uncertainties revolve around whether the effect of management actions depends on (1) type of dominant invader, (2) past defoliation history, and (3) level of invasion. Two additional uncertainties are considered when choosing a management action for tallgrass units: (4) the effectiveness of grazing within the cool-season window as a surrogate for burning when smooth brome is the dominant invader, and (5) the differential effect of active management outside the window as compared to rest.
\nBecause data on the probability of transitioning from one state to another under the various models were lacking, expert opinion and elicitation were used to parameterize the models. In addition, cooperators participated in elicitation exercises to extract their beliefs regarding the value of having native prairie compared to the cost of achieving it. Quantifying the subjective expression of utility in this way allowed for mathematical representation of the management objective into an objective function. By maximizing the objective function, cumulative utility is maximized, leading to the identification of a sequence of decisions that will achieve the management objective.
\nThe NPAM system adopted a vegetation monitoring protocol that was rapid, inexpensive, and familiar to many of the cooperators. The monitoring protocol served three purposes: (1) determining current vegetation and defoliation states of each unit, (2) evaluating progress toward the management objective, and (3) assessing predictive performance of the alternative models. The management year runs from September 1 to August 31. Management can be applied anytime during that period and monitoring takes places from late June to mid-August. Cooperators enter vegetation data and management information into a centralized database by August 25 of each year. Given the current state of the system (vegetation and defoliation states) and the current understanding of the system (or the belief state), identifying the current best management decision is a matter of looking up the combination (that is, system state and belief state) in the appropriate (mixed-grass or tallgrass) optimal decision table. Given complete uncertainty at the outset of decision-making, initial assignment of equal belief weights to each model was believed reasonable. The decisions in the optimal decision table that correspond to the current belief state constitute the current optimal decision policy. By August 31 of each year, individual cooperators are provided with a recommended management action for each of their management units for the upcoming management year. Upon receiving the management recommendations for their units, managers consider the recommendation, along with other relevant information, and at some point during the year one of the management alternatives is carried out. This iterative cycle of making and implementing a management decision, predicting the response, monitoring the outcome, comparing predicted and observed outcomes, updating model weights, and recommending a management action for the next cycle is expected to result in an accumulation of weight on a representative model of system dynamics, thereby increasing understanding needed to effectively manage native prairies.
\nThe NPAM system is now entering its second full year of complete operation, and represents one of only a few fully implemented applications of adaptive management within the U.S. Fish and Wildlife Service. NPAM is truly unique in that it originated from the ground up as a result of the leadership and steadfastness of several refuge biologists and managers confronted with a common problem. These biologists recognized that working together across a large landscape presented perhaps the best opportunity for halting and reversing the invasion of native grasslands by non-native cool-season grasses. Importantly, the NPAM system encapsulates the collective thinking and experience of tens if not hundreds of individuals who have battled this vexing problem for much of their careers.
\nThe NPAM initiative is rooted in principles of adaptive management, thereby affording the opportunity for grassland managers to pursue management objectives while acquiring information to reduce uncertainty and improve future management. The project introduced a number of technical innovations that will serve as templates for conservation efforts throughout and beyond the U.S. Fish and Wildlife Service. First, NPAM is an on-the-ground implementation of active adaptive management—possibly the first of its kind in conservation management—in which recommended management actions result from a prospective analysis of future learning (Williams, 1996). Second, by the use of dynamic optimization, NPAM demonstrates how decisions can be made that take into account possible future transitions of the system. Third, NPAM demonstrates how models of partial controllability are an effective means of accommodating unpredictable circumstances that cause a manager to follow a different course than was intended. Finally, the database developed for NPAM is an unparalleled system that enables the rapid integration of data from the field for the generation of ‘just-in-time’ management recommendations. In all, NPAM provides an example of how a science-management partnership can be forged to achieve large-scale conservation objectives.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131279","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Gannon, J., Shaffer, T.L., and Moore, C., 2013, Native Prairie Adaptive Management: a multi region adaptive approach to invasive plant management on Fish and Wildlife Service owned native prairies: U.S. Geological Survey Open-File Report 2013-1279, Report: vii, 184 p.; Downloads Directory, https://doi.org/10.3133/ofr20131279.","productDescription":"Report: vii, 184 p.; Downloads Directory","numberOfPages":"190","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-043840","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":281449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131279.jpg"},{"id":280311,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1279/"},{"id":281447,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1279/pdf/of2013-1279.pdf"},{"id":281448,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1279/Downloads/"}],"country":"United States","state":"Minnesota;Montana;North Dakota;South Dakota","otherGeospatial":"Great Plains;Prairie Pothole Region","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.32,40.75 ], [ -116.32,50.04 ], [ -90.88,50.04 ], [ -90.88,40.75 ], [ -116.32,40.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd68a3e4b0b290851022f6","contributors":{"authors":[{"text":"Gannon, Jill J.","contributorId":12722,"corporation":false,"usgs":true,"family":"Gannon","given":"Jill J.","affiliations":[],"preferred":false,"id":487376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shaffer, Terry L. 0000-0001-6950-8951 tshaffer@usgs.gov","orcid":"https://orcid.org/0000-0001-6950-8951","contributorId":3192,"corporation":false,"usgs":true,"family":"Shaffer","given":"Terry","email":"tshaffer@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":487374,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Clinton T.","contributorId":9767,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton T.","affiliations":[],"preferred":false,"id":487375,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70073692,"text":"70073692 - 2013 - Comment on “Historical perspective on seismic hazard to Hispaniola and the northeast Caribbean region” by U. ten Brink et al.","interactions":[],"lastModifiedDate":"2017-05-18T11:17:31","indexId":"70073692","displayToPublicDate":"2014-01-22T10:52:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Comment on “Historical perspective on seismic hazard to Hispaniola and the northeast Caribbean region” by U. ten Brink et al.","docAbstract":"The analysis of historical earthquakes in the northeastern Caribbean by ten Brink et al. [2011, hereafter TB11] addresses the occurrence of large and destructive historical earthquakes associated with the North American-Caribbean plate boundary. One conclusion presented in TB11 is that the recurrence interval for large earthquakes on the left-lateral, strike-slip Septentrional Fault (SF) (Figure 1a) is approximately 300 years. Their Figure 7 shows rupture of the SF across the entire island of Hispaniola in CE 1200, 1542, and 1842. Our comment challenges this model for SF earthquake recurrence because it is inconsistent with our published paleoseismic data that show no large historical earthquake is associated with surface rupture along the SF east of Santiago (Figure 1a)[Prentice et al., 1993; Mann et al., 1998; Prentice et al., 2003].
","language":"English","publisher":"Wiley","doi":"10.1002/jgrb.50170","usgsCitation":"Prentice, C.S., Mann, P., and Pena, L.R., 2013, Comment on “Historical perspective on seismic hazard to Hispaniola and the northeast Caribbean region” by U. ten Brink et al.: Journal of Geophysical Research B: Solid Earth, v. 118, no. 4, p. 1602-1605, https://doi.org/10.1002/jgrb.50170.","productDescription":"4 p.","startPage":"1602","endPage":"1605","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038092","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":281363,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Dominican Republic, Haiti","otherGeospatial":"Hispaniola","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.5083,17.5817 ], [ -74.5083,20.1244 ], [ -68.2763,20.1244 ], [ -68.2763,17.5817 ], [ -74.5083,17.5817 ] ] ] } } ] }","volume":"118","issue":"4","publicComments":"Comment on: ten Brink, U.S., W.H. Bakun, and C.H. Flores (2011), Historical perspective on seismic hazard to Hispaniola and the NE Caribbean, J. Geophys.Res., 116, B12318, doi:10.1029/2011JB008497.","noUsgsAuthors":false,"publicationDate":"2013-04-25","publicationStatus":"PW","scienceBaseUri":"54dd2b60e4b08de9379b3353","contributors":{"authors":[{"text":"Prentice, Carol S. 0000-0003-3732-3551 cprentice@usgs.gov","orcid":"https://orcid.org/0000-0003-3732-3551","contributorId":2676,"corporation":false,"usgs":true,"family":"Prentice","given":"Carol","email":"cprentice@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":489043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mann, Paul","contributorId":57729,"corporation":false,"usgs":true,"family":"Mann","given":"Paul","email":"","affiliations":[],"preferred":false,"id":489044,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pena, Luis R.","contributorId":72705,"corporation":false,"usgs":true,"family":"Pena","given":"Luis","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":489045,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70055685,"text":"ofr20131262 - 2013 - Technical evaluation of a total maximum daily load model for Upper Klamath and Agency Lakes, Oregon","interactions":[],"lastModifiedDate":"2014-01-21T13:40:33","indexId":"ofr20131262","displayToPublicDate":"2014-01-21T13:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1262","title":"Technical evaluation of a total maximum daily load model for Upper Klamath and Agency Lakes, Oregon","docAbstract":"We reviewed a mass balance model developed in 2001 that guided establishment of the phosphorus total maximum daily load (TMDL) for Upper Klamath and Agency Lakes, Oregon. The purpose of the review was to evaluate the strengths and weaknesses of the model and to determine whether improvements could be made using information derived from studies since the model was first developed. The new data have contributed to the understanding of processes in the lakes, particularly internal loading of phosphorus from sediment, and include measurements of diffusive fluxes of phosphorus from the bottom sediments, groundwater advection, desorption from iron oxides at high pH in a laboratory setting, and estimates of fluxes of phosphorus bound to iron and aluminum oxides. None of these processes in isolation, however, is large enough to account for the episodically high values of whole-lake internal loading calculated from a mass balance, which can range from 10 to 20 milligrams per square meter per day for short periods.
\nThe possible role of benthic invertebrates in lake sediments in the internal loading of phosphorus in the lake has become apparent since the development of the TMDL model. Benthic invertebrates can increase diffusive fluxes several-fold through bioturbation and biodiffusion, and, if the invertebrates are bottom feeders, they can recycle phosphorus to the water column through metabolic excretion. These organisms have high densities (1,822–62,178 individuals per square meter) in Upper Klamath Lake. Conversion of the mean density of tubificid worms (Oligochaeta) and chironomid midges (Diptera), two of the dominant taxa, to an areal flux rate based on laboratory measurements of metabolic excretion of two abundant species suggested that excretion by benthic invertebrates is at least as important as any of the other identified processes for internal loading to the water column.
\nData from sediment cores collected around Upper Klamath Lake since the development of the TMDL model also contributed to this review. Cores were sequentially extracted to determine the distribution of phosphorus associated with several matrices in the sediment (freely exchangeable, metal-oxides, acid-soluble minerals, and residual). The concentrations of phosphorus in these fractions varied around the lake in patterns that reflect transport processes in the lake and the ultimate deposition of organic and inorganic forms of phosphorus from the water column. Both organic and inorganic phosphorus had higher concentrations in the northern part of the lake, in and just west of Goose Bay. At the time that these cores were collected, prior to restoration of the Williamson River Delta, this area was close to the shoreline of the lake and east of the Williamson River mouth. This contrasts with erosional inputs, which, in addition to being high to the east of the pre-restoration Williamson River mouth, were higher in the middle of the lake than at the northern end. Organic forms of phosphorus had particularly high concentrations in the northern bays. When these cores were used to calculate a new estimate of the whole-lake-averaged concentration of total phosphorus in the top 10 centimeters of the lake sediments, the estimate was about one-third of the best estimate available when the TMDL model was developed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131262","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Wood, T.M., Wherry, S., Carter, J.L., Kuwabara, J.S., Simon, N.S., and Rounds, S.A., 2013, Technical evaluation of a total maximum daily load model for Upper Klamath and Agency Lakes, Oregon: U.S. Geological Survey Open-File Report 2013-1262, vi, 75 p., https://doi.org/10.3133/ofr20131262.","productDescription":"vi, 75 p.","numberOfPages":"84","onlineOnly":"Y","ipdsId":"IP-037641","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":281330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131262.GIF"},{"id":281328,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1262/"},{"id":281329,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1262/pdf/ofr2013-1262.pdf"}],"projection":"Universal Transverse Mercator","datum":"North American Datum of 1927","country":"United States","state":"Oregon","otherGeospatial":"Agency Lake;Goose Bay;Upper Klamath Lake;Williamson River;Williamson River Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.197797,42.082902 ], [ -122.197797,42.650173 ], [ -121.577757,42.650173 ], [ -121.577757,42.082902 ], [ -122.197797,42.082902 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7657e4b0b2908510ad44","contributors":{"authors":[{"text":"Wood, Tamara M. 0000-0001-6057-8080 tmwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6057-8080","contributorId":1164,"corporation":false,"usgs":true,"family":"Wood","given":"Tamara","email":"tmwood@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wherry, Susan A.","contributorId":79403,"corporation":false,"usgs":true,"family":"Wherry","given":"Susan A.","affiliations":[],"preferred":false,"id":486208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, James L. 0000-0002-0104-9776 jlcarter@usgs.gov","orcid":"https://orcid.org/0000-0002-0104-9776","contributorId":3278,"corporation":false,"usgs":true,"family":"Carter","given":"James","email":"jlcarter@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":486206,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuwabara, James S. 0000-0003-2502-1601 kuwabara@usgs.gov","orcid":"https://orcid.org/0000-0003-2502-1601","contributorId":3374,"corporation":false,"usgs":true,"family":"Kuwabara","given":"James","email":"kuwabara@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":486207,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Simon, Nancy S. 0000-0003-2706-7611 nssimon@usgs.gov","orcid":"https://orcid.org/0000-0003-2706-7611","contributorId":838,"corporation":false,"usgs":true,"family":"Simon","given":"Nancy","email":"nssimon@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":486203,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486204,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70049064,"text":"ofr20131257 - 2013 - Geologic assessment of undiscovered oil and gas resources: Oligocene Frio and Anahuac Formations, United States Gulf of Mexico coastal plain and State waters","interactions":[],"lastModifiedDate":"2014-01-16T08:34:03","indexId":"ofr20131257","displayToPublicDate":"2014-01-16T08:19:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1257","title":"Geologic assessment of undiscovered oil and gas resources: Oligocene Frio and Anahuac Formations, United States Gulf of Mexico coastal plain and State waters","docAbstract":"The Oligocene Frio and Anahuac Formations were assessed as part of the 2007 U.S. Geological Survey (USGS) assessment of Tertiary strata of the U.S. Gulf of Mexico Basin onshore and State waters. The Frio Formation, which consists of sand-rich fluvio-deltaic systems, has been one of the largest hydrocarbon producers from the Paleogene in the Gulf of Mexico. The Anahuac Formation, an extensive transgressive marine shale overlying the Frio Formation, contains deltaic and slope sandstones in Louisiana and Texas and carbonate rocks in the eastern Gulf of Mexico. In downdip areas of the Frio and Anahuac Formations, traps associated with faulted, rollover anticlines are common. Structural traps commonly occur in combination with stratigraphic traps. Faulted salt domes in the Frio and Anahuac Formations are present in the Houston embayment of Texas and in south Louisiana. In the Frio Formation, stratigraphic traps are found in fluvial, deltaic, barrier-bar, shelf, and strandplain systems.
\nThe USGS Tertiary Assessment Team defined a single, Upper Jurassic-Cretaceous-Tertiary Composite Total Petroleum System (TPS) for the Gulf Coast basin, based on previous studies and geochemical analysis of oils in the Gulf Coast basin. The primary source rocks for oil and gas within Cenozoic petroleum systems, including Frio Formation reservoirs, in the northern, onshore Gulf Coastal region consist of coal and shale rich in organic matter within the Wilcox Group (Paleocene–Eocene), with some contributions from the Sparta Sand of the Claiborne Group (Eocene). The Jurassic Smackover Formation and Cretaceous Eagle Ford Formation also may have contributed substantial petroleum to Cenozoic reservoirs. Modeling studies of thermal maturity by the USGS Tertiary Assessment Team indicate that downdip portions of the basal Wilcox Group reached sufficient thermal maturity to generate hydrocarbons by early Eocene; this early maturation is the result of rapid sediment accumulation in the early Tertiary, combined with the reaction kinetic parameters used in the models. A number of studies indicate that the migration of oil and gas in the Cenozoic Gulf of Mexico basin is primarily vertical, occurring along abundant growth faults associated with sediment deposition or along faults associated with salt domes.
\nThe USGS Tertiary assessment team developed a geologic model based on recurring regional-scale structural and depositional features in Paleogene strata to define assessment units (AUs). Three general areas, as described in the model, are found in each of the Paleogene stratigraphic intervals assessed: “Stable Shelf,” “Expanded Fault,” and “Slope and Basin Floor” zones. On the basis of this model, three AUs for the Frio Formation were defined: (1) the Frio Stable Shelf Oil and Gas AU, containing reservoirs with a mean depth of about 4,800 feet in normally pressured intervals; (2) the Frio Expanded Fault Zone Oil and Gas AU, containing reservoirs with a mean depth of about 9,000 feet in primarily overpressured intervals; and (3) the Frio Slope and Basin Floor Gas AU, which currently has no production but has potential for deep gas resources (>15,000 feet). AUs also were defined for the Hackberry trend, which consists of a slope facies stratigraphically in the middle part of the Frio Formation, and the Anahuac Formation. The Frio Basin Margin AU, an assessment unit extending to the outcrop of the Frio (or basal Miocene), was not quantitatively assessed because of its low potential for production. Two proprietary, commercially available databases containing field and well production information were used in the assessment. Estimates of undiscovered resources for the five AUs were based on a total of 1,734 reservoirs and 586,500 wells producing from the Frio and Anahuac Formations. Estimated total mean values of technically recoverable, undiscovered resources are 172 million barrels of oil (MMBO), 9.4 trillion cubic feet of natural gas (TCFG), and 542 million barrels of natural gas liquids for all of the Frio and Anahuac AUs. Of the five units assessed, the Frio Slope and Basin Floor Gas AU has the greatest potential for undiscovered gas resources, having an estimated mean of 5.6 TCFG. The Hackberry Oil and Gas AU shows the second highest potential for gas of the five units assessed, having an estimated mean of 1.8 TCFG. The largest undiscovered, conventional crude oil resource was estimated for the Frio Slope and Basin Floor Gas AU; the estimated mean for oil in this AU is 110 MMBO.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131257","usgsCitation":"Swanson, S.M., Karlsen, A.W., and Valentine, B.J., 2013, Geologic assessment of undiscovered oil and gas resources: Oligocene Frio and Anahuac Formations, United States Gulf of Mexico coastal plain and State waters: U.S. Geological Survey Open-File Report 2013-1257, Report: viii, 66 p.; Appendix 1: 10 p., https://doi.org/10.3133/ofr20131257.","productDescription":"Report: viii, 66 p.; Appendix 1: 10 p.","numberOfPages":"78","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051257","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":281142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131257.jpg"},{"id":281139,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1257/"},{"id":281140,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1257/pdf/of2013-1257.pdf"},{"id":281141,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1257/pdf/ofr2013-1257_appendix1_input_data.pdf"}],"scale":"2000000","projection":"Albers Equal-Area Conic projection","country":"United States","state":"Louisiana;Texas","otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -101.0,24.84 ], [ -101.0,33.0 ], [ -88.5,33.0 ], [ -88.5,24.84 ], [ -101.0,24.84 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52d8ff61e4b08fdd528145fd","contributors":{"authors":[{"text":"Swanson, Sharon M. 0000-0002-4235-1736 smswanson@usgs.gov","orcid":"https://orcid.org/0000-0002-4235-1736","contributorId":590,"corporation":false,"usgs":true,"family":"Swanson","given":"Sharon","email":"smswanson@usgs.gov","middleInitial":"M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":486096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karlsen, Alexander W.","contributorId":105382,"corporation":false,"usgs":true,"family":"Karlsen","given":"Alexander","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":486098,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valentine, Brett J. 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":3846,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":486097,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70059127,"text":"ofr20131270 - 2013 - Hurricane Isaac: observations and analysis of coastal change","interactions":[],"lastModifiedDate":"2014-01-14T16:17:00","indexId":"ofr20131270","displayToPublicDate":"2014-01-14T16:05:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1270","title":"Hurricane Isaac: observations and analysis of coastal change","docAbstract":"Understanding storm-induced coastal change and forecasting these changes require knowledge of the physical processes associated with a storm and the geomorphology of the impacted coastline. The primary physical process of interest is sediment transport that is driven by waves, currents, and storm surge associated with storms. Storm surge, which is the rise in water level due to the wind, barometric pressure, and other factors, allows both waves and currents to impact parts of the coast not normally exposed to these processes.
\nCoastal geomorphology reflects the coastal changes associated with extreme-storm processes. Relevant geomorphic variables that are observable before and after storms include sand dune elevation, beach width, shoreline position, sediment grain size, and foreshore beach slope. These variables, in addition to hydrodynamic processes, can be used to quantify coastal change and are used to predict coastal vulnerability to storms (Stockdon and others, 2007).
\nThe U.S. Geological Survey (USGS) National Assessment of Coastal Change Hazards (NACCH) project (http://coastal.er.usgs.gov/national-assessment/) provides hazard information to those concerned about the Nation’s coastlines, including residents of coastal areas, government agencies responsible for coastal management, and coastal researchers. Extreme-storm research is a component of the NACCH project (http://coastal.er.usgs.gov/hurricanes/) that includes development of predictive understanding, vulnerability assessments using models, and updated observations in response to specific storm events. In particular, observations were made to determine morphological changes associated with Hurricane Isaac, which made landfall in the United States first at Southwest Pass, at the mouth of the Mississippi River, at 0000 August 29, 2012 UTC (Coordinated Universal Time) and again, 8 hours later, west of Port Fourchon, Louisiana (Berg, 2013). Methods of observation included oblique aerial photography, airborne light detection and ranging (lidar) topographic surveys, and ground-based topographic surveys. This report documents data-collection efforts and presents qualitative and quantitative descriptions of hurricane-induced changes to the shoreline, beaches, dunes, and infrastructure in the region that was heavily impacted by Hurricane Isaac.
\nThe report is divided into the following sections:
\nWater samples were collected from Maumee Bay State Park Lakeside Beach, Oregon, Ohio, during the 2012 recreational season and analyzed for selected cyanobacteria gene sequences by DNA-based quantitative polymerase chain reaction (qPCR) and RNA-based quantitative reverse-transcription polymerase chain reaction (qRT-PCR). Results from the four DNA assays (for quantifying total cyanobacteria, total Microcystis, and Microcystis and Planktothrix strains that possess the microcystin synthetase E (mcyE) gene) and two RNA assays (for quantifying Microcystis and Planktothrix genera that are expressing the microcystin synthetase E (mcyE) gene) were compared to microcystin concentration results determined by an enzyme-linked immunosorbent assay (ELISA).
\nConcentrations of the target in replicate analyses were log10 transformed. The average value of differences in log10 concentrations for the replicates that had at least one detection were found to range from 0.05 to >0.37 copy per 100 milliliters (copy/100 mL) for DNA-based methods and from >0.04 to >0.17 copy/100 mL for RNA-based methods.
\nRNA has a shorter half-life than DNA; consequently, a 24-hour holding-time study was done to determine the effects of holding time on RNA concentrations. Holding-time comparisons for the RNA-based Microcystis toxin mcyE assay showed reductions in the number of copies per 100 milliliters over 24 hours. The log difference between time 2 hours and time 24 hours was >0.37 copy/100 mL, which was higher than the analytical variability (log difference of >0.17 copy/100 mL).
\nSpearman’s correlation analysis indicated that microcystin toxin concentrations were moderately to highly related to DNA-based assay results for total cyanobacteria (rho=0.69), total Microcystis (rho=0.74), and Microcystis strains that possess the mcyE gene (rho=0.81). Microcystin toxin concentrations were strongly related with RNA-based assay results for Microcystis mcyE gene expression (rho=0.95). Correlation analysis could not be done for Planktothrix mcyE gene expression because of too few detections.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135189","collaboration":"Prepared in cooperation with the Ohio Lake Erie Commission","usgsCitation":"Stelzer, E.A., Loftin, K.A., and Struffolino, P., 2013, Relations between DNA- and RNA-based molecular methods for cyanobacteria and microcystin concentration at Maumee Bay State Park Lakeside Beach, Oregon, Ohio, 2012: U.S. Geological Survey Scientific Investigations Report 2013-5189, iv, 9 p., https://doi.org/10.3133/sir20135189.","productDescription":"iv, 9 p.","numberOfPages":"16","ipdsId":"IP-051214","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":280671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135189.jpg"},{"id":280669,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5189/"},{"id":280670,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5189/pdf/sir2013-5189.pdf"}],"projection":"Universal Transverse Mercator projection","country":"United States","state":"Ohio","city":"Oregon","otherGeospatial":"Lake Erie;Maumee Bay State Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.387003,41.678489 ], [ -83.387003,41.689931 ], [ -83.362584,41.689931 ], [ -83.362584,41.678489 ], [ -83.387003,41.678489 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52cd2200e4b0c3f95143ed19","contributors":{"authors":[{"text":"Stelzer, Erin A. 0000-0001-7645-7603 eastelzer@usgs.gov","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":1933,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin","email":"eastelzer@usgs.gov","middleInitial":"A.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486094,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":486093,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Struffolino, Pamela","contributorId":87233,"corporation":false,"usgs":true,"family":"Struffolino","given":"Pamela","affiliations":[],"preferred":false,"id":486095,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70048353,"text":"70048353 - 2013 - NGA-West 2 Equations for predicting PGA, PGV, and 5%-Damped PSA for shallow crustal earthquakes","interactions":[],"lastModifiedDate":"2014-09-23T12:59:38","indexId":"70048353","displayToPublicDate":"2014-01-07T10:44:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"NGA-West 2 Equations for predicting PGA, PGV, and 5%-Damped PSA for shallow crustal earthquakes","docAbstract":"We provide ground-motion prediction equations for computing medians and standard deviations of average horizontal component intensity measures (IMs) for shallow crustal earthquakes in active tectonic regions. The equations were derived from a global database with M 3.0–7.9 events. We derived equations for the primary M- and distance-dependence of the IMs after fixing the VS30-based nonlinear site term from a parallel NGA-West 2 study. We then evaluated additional effects using mixed effects residuals analysis, which revealed no trends with source depth over the M range of interest, indistinct Class 1 and 2 event IMs, and basin depth effects that increase and decrease long-period IMs for depths larger and smaller, respectively, than means from regional VS30-depth relations. Our aleatory variability model captures decreasing between-event variability with M, as well as within-event variability that increases or decreases with M depending on period, increases with distance, and decreases for soft sites.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earthquake Spectra","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Earthquake Engineering Research Institute","publisherLocation":"Berkeley, CA","doi":"10.1193/070113EQS184M","usgsCitation":"Boore, D.M., Stewart, J.P., Seyhan, E., and Atkinson, G.M., 2013, NGA-West 2 Equations for predicting PGA, PGV, and 5%-Damped PSA for shallow crustal earthquakes: Earthquake Spectra, v. 30, no. 3, p. 1057-1085, https://doi.org/10.1193/070113EQS184M.","productDescription":"29 p.","startPage":"1057","endPage":"1085","numberOfPages":"29","ipdsId":"IP-049134","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":280644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280643,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1193/070113EQS184M"}],"volume":"30","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-08-01","publicationStatus":"PW","scienceBaseUri":"52cd21fde4b0c3f95143ecfe","contributors":{"authors":[{"text":"Boore, David M. boore@usgs.gov","contributorId":2509,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":484389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stewart, Jon P.","contributorId":78644,"corporation":false,"usgs":true,"family":"Stewart","given":"Jon","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":484392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seyhan, Emel","contributorId":51193,"corporation":false,"usgs":false,"family":"Seyhan","given":"Emel","email":"","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":484390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atkinson, Gail M.","contributorId":60515,"corporation":false,"usgs":false,"family":"Atkinson","given":"Gail","email":"","middleInitial":"M.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":484391,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70059743,"text":"70059743 - 2013 - Environmental survey in the Tuul and Orkhon River basins of north-central Mongolia, 2010: Metals and other elements in streambed sediment and floodplain soil","interactions":[],"lastModifiedDate":"2020-12-30T17:03:19.475861","indexId":"70059743","displayToPublicDate":"2014-01-07T09:51:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Environmental survey in the Tuul and Orkhon River basins of north-central Mongolia, 2010: Metals and other elements in streambed sediment and floodplain soil","docAbstract":"Streambed sediment and subsurface floodplain soil were sampled for elemental analyses from 15 locations in river basins of north-central Mongolia during August 2010. Our primary objective was to conduct a reconnaissance-level assessment of potential inputs of toxicologically important metals and metalloids to Lake Baikal, Russia, that might originate from mining and urban activities within tributaries of the Selenga River in Mongolia. Samples were collected in triplicate from all sites, then dried, and sieved to <2 mm for analysis by portable X-ray florescence spectroscopy and by inductively coupled plasma mass spectrometry after digestion with concentrated nitric and hydrochloric acids. Arsenic, copper, and mercury were greatly elevated in sediment and floodplain soil collected from tributary streams located near two major mining operations. Lead and zinc were moderately elevated in streambed sediment and in floodplain soil obtained from a small tributary in the capital city of Ulaanbaatar, but those concentrations were considerably less than probable effects benchmarks. Historical and possibly present mining activities have led to considerable metal contamination in certain tributaries of the Orkhon River in north-central Mongolia; however, metals originating from those sources did not appear to be accumulating in sediments at our downstream-most sampling sites located near the border between Mongolia and Russia.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-013-3229-9","usgsCitation":"Brumbaugh, W.G., Tillitt, D.E., May, T.W., Javzan, C., and Komov, V.T., 2013, Environmental survey in the Tuul and Orkhon River basins of north-central Mongolia, 2010: Metals and other elements in streambed sediment and floodplain soil: Environmental Monitoring and Assessment, v. 185, no. 11, p. 8991-9008, https://doi.org/10.1007/s10661-013-3229-9.","productDescription":"18 p.","startPage":"8991","endPage":"9008","ipdsId":"IP-035628","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":280642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mongolia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 103.7439,47.7356 ], [ 103.7439,49.6178 ], [ 108.2263,49.6178 ], [ 108.2263,47.7356 ], [ 103.7439,47.7356 ] ] ] } } ] }","volume":"185","issue":"11","noUsgsAuthors":false,"publicationDate":"2013-05-18","publicationStatus":"PW","scienceBaseUri":"52cd21fce4b0c3f95143ecf2","contributors":{"authors":[{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":487758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tillitt, Donald E. 0000-0002-8278-3955 dtillitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8278-3955","contributorId":1875,"corporation":false,"usgs":true,"family":"Tillitt","given":"Donald","email":"dtillitt@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":487759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"May, Thomas W. tmay@usgs.gov","contributorId":2598,"corporation":false,"usgs":true,"family":"May","given":"Thomas","email":"tmay@usgs.gov","middleInitial":"W.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":487760,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Javzan, Ch.","contributorId":245976,"corporation":false,"usgs":false,"family":"Javzan","given":"Ch.","email":"","affiliations":[],"preferred":false,"id":487762,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Komov, V. T.","contributorId":6757,"corporation":false,"usgs":false,"family":"Komov","given":"V.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":487761,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70048961,"text":"sim3277 - 2013 - Lidar-revised geologic map of the Olalla 7.5' quadrangle, King, Kitsap, and Pierce Counties, Washington","interactions":[],"lastModifiedDate":"2023-05-26T15:59:48.629964","indexId":"sim3277","displayToPublicDate":"2014-01-06T14:35:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3277","title":"Lidar-revised geologic map of the Olalla 7.5' quadrangle, King, Kitsap, and Pierce Counties, Washington","docAbstract":"The Olalla 7.5' quadrangle, which lies almost in the center of the Puget Lowland, displays the broad range of geologic environments typical of the region. The upland plain is fluted by the passage of the great continental ice sheet that last covered the area about 17,000 (14,000 radiocarbon) years ago. The plain is cut by channel deposits, both late glacial and postglacial in age, and it is cleaved even more deeply by one of the major arms of Puget Sound, Colvos Passage, which here separates the west coast of Vashon Island from the Kitsap Peninsula.
\nBeneath the deposits of the last ice sheet is a complex sequence of older Quaternary-age sediments that extends about 400 m below the modern ground surface. These older sediments are best exposed along the shorelines and beach cliffs of Puget Sound, where wave action and landslides maintain relatively fresh exposures. The older sediments typically are compact, having been loaded by ice during one or more episodes of glaciation subsequent to their deposition. Locally these sediments are also cemented by iron and manganese oxides and hydroxides, a consequence of many tens or hundreds of thousands of years of weathering and groundwater movement.
\nOur map is an interpretation of a 6-ft resolution lidar-derived digital elevation model combined with the geology depicted on the \"Geologic map of the Olalla 7.5' quadrangle, King, Kitsap, and Pierce Counties, Washington,\" by Booth and Troost (2005), which was described, interpreted, and located on the 1953 1:24,000-scale topographic map of the Olalla 7.5-minute quadrangle. The original topographic base map, derived from 1951 aerial photographs, has 20-ft contours, nominal horizontal resolution of circa 40 ft (12 m), and nominal mean vertical accuracy of circa 13 ft (4 m). This new DEM has a horizontal resolution of 6 ft (2 m) and mean vertical accuracy circa 1 ft (0.3 m). The greater resolution and accuracy of the lidar DEM facilitated a much-improved interpretation of many aspects of the surficial geology, especially the distribution and relative age of landforms and the materials inferred to comprise them.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3277","usgsCitation":"Tabor, R.W., Haugerud, R.A., Booth, D.B., and Troost, K.G., 2013, Lidar-revised geologic map of the Olalla 7.5' quadrangle, King, Kitsap, and Pierce Counties, Washington: U.S. Geological Survey Scientific Investigations Map 3277, Pamphlet: ii, 14 p.; 1 Plate: 29.14 x 32.64 inches; Readme; Metadata; Database, https://doi.org/10.3133/sim3277.","productDescription":"Pamphlet: ii, 14 p.; 1 Plate: 29.14 x 32.64 inches; Readme; Metadata; Database","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-038416","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":280629,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3277/pdf/sim3277_pamphlet.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":280633,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3277/downloads/sim3277_database.zip"},{"id":398885,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_99480.htm","linkFileType":{"id":5,"text":"html"}},{"id":280634,"rank":7,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3277.jpg"},{"id":280631,"rank":6,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3277/pdf/OlallaREADME.pdf"},{"id":280630,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3277/pdf/sim3277.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":280632,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3277/downloads/olageol-genmd.txt"},{"id":280628,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3277/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","country":"United States","state":"Washington","county":"King County, Kitsap County, Pierce County","otherGeospatial":"Olalla 7.5' quadrangle","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.625,47.375 ], [ -122.625,47.5 ], [ -122.5,47.5 ], [ -122.5,47.375 ], [ -122.625,47.375 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52cbd082e4b03116c9ddba00","contributors":{"authors":[{"text":"Tabor, Rowland W. rtabor@usgs.gov","contributorId":3816,"corporation":false,"usgs":true,"family":"Tabor","given":"Rowland","email":"rtabor@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":485881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haugerud, Ralph A. 0000-0001-7302-4351 rhaugerud@usgs.gov","orcid":"https://orcid.org/0000-0001-7302-4351","contributorId":2691,"corporation":false,"usgs":true,"family":"Haugerud","given":"Ralph","email":"rhaugerud@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":485880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Booth, Derek B.","contributorId":100873,"corporation":false,"usgs":false,"family":"Booth","given":"Derek","email":"","middleInitial":"B.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":485883,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Troost, Kathy Goetz","contributorId":35023,"corporation":false,"usgs":true,"family":"Troost","given":"Kathy","email":"","middleInitial":"Goetz","affiliations":[],"preferred":false,"id":485882,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70048978,"text":"sir20135184 - 2013 - Hydrogeology and water quality in the Snake River alluvial aquifer at Jackson Hole Airport, Jackson, Wyoming, water years 2011 and 2012","interactions":[],"lastModifiedDate":"2014-01-06T13:57:09","indexId":"sir20135184","displayToPublicDate":"2014-01-06T13:41:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5184","title":"Hydrogeology and water quality in the Snake River alluvial aquifer at Jackson Hole Airport, Jackson, Wyoming, water years 2011 and 2012","docAbstract":"The hydrogeology and water quality of the Snake River alluvial aquifer at the Jackson Hole Airport in northwest Wyoming was studied by the U.S. Geological Survey, in cooperation with the Jackson Hole Airport Board, during water years 2011 and 2012 as part of a followup to a previous baseline study during September 2008 through June 2009. Hydrogeologic conditions were characterized using data collected from 19 Jackson Hole Airport wells. Groundwater levels are summarized in this report and the direction of groundwater flow, hydraulic gradients, and estimated groundwater velocity rates in the Snake River alluvial aquifer underlying the study area are presented. Analytical results of groundwater samples collected from 10 wells during water years 2011 and 2012 are presented and summarized.
\nThe water table at Jackson Hole Airport was lowest in early spring and reached its peak in July or August, with an increase of 12.5 to 15.5 feet between April and July 2011. Groundwater flow was predominantly horizontal but generally had the hydraulic potential for downward flow. Groundwater flow within the Snake River alluvial aquifer at the airport was from the northeast to the west-southwest, with horizontal velocities estimated to be about 25 to 68 feet per day. This range of velocities slightly is broader than the range determined in the previous study and likely is due to variability in the local climate. The travel time from the farthest upgradient well to the farthest downgradient well was approximately 52 to 142 days. This estimate only describes the average movement of groundwater, and some solutes may move at a different rate than groundwater through the aquifer.
\nThe quality of the water in the alluvial aquifer generally was considered good. Water from the alluvial aquifer was fresh, hard to very hard, and dominated by calcium carbonate. No constituents were detected at concentrations exceeding U.S. Environmental Protection Agency maximum contaminant levels or health advisories; however, reduction and oxidation (redox) measurements indicate oxygen-poor water in many of the wells. Gasoline-range organics, three volatile organic compounds, and triazoles were detected in some groundwater samples. The quality of groundwater in the alluvial aquifer generally was suitable for domestic and other uses; however, dissolved iron and manganese were detected in samples from many of the monitor wells at concentrations exceeding U.S. Environmental Protection Agency secondary maximum contaminant levels. Iron and manganese likely are both natural components of the geologic materials in the area and may have become mobilized in the aquifer because of redox processes. Additionally, measurements of dissolved-oxygen concentrations and analyses of major ions and nutrients indicate reducing conditions exist at 7 of the 10 wells sampled.
\nMeasurements of dissolved-oxygen concentrations (less than 0.1 to 9 milligrams per liter) indicated some variability in the oxygen content of the aquifer. Dissolved-oxygen concentrations in samples from 3 of the 10 wells indicated oxic conditions in the aquifer, whereas low dissolved-oxygen concentrations (less than 1 milligram per liter) in samples from 7 wells indicated anoxic conditions. Nutrients were present in low concentrations in all samples collected. Nitrate plus nitrite was detected in samples from 6 of the 10 monitored wells, whereas dissolved ammonia was detected in small concentrations in 8 of the 10 monitored wells. Dissolved organic carbon concentrations generally were low. At least one dissolved organic carbon concentration was quantified by the laboratory in samples from all 10 wells; one of the concentrations was an order of magnitude higher than other detected dissolved organic carbon concentrations, and slightly exceeded the estimated range for natural groundwater.
\nSamples were collected for analyses of dissolved gases, and field analyses of ferrous iron, hydrogen sulfide, and low-level dissolved oxygen were completed to better understand the redox conditions of the alluvial aquifer. Dissolved gas analyses confirmed low concentrations of dissolved oxygen in samples from wells where reducing conditions exist and indicated the presence of methane gas in samples from several wells. Redox processes in the alluvial aquifer were identified using a model designed to use a multiple-lines-of-evidence approach to distinguish reduction processes. Results of redox analyses indicate iron reduction was the dominant redox process; however, the model indicated manganese reduction and methanogenesis also were taking place in the aquifer.
\nEach set of samples collected during this study included analysis of at least two, but often many anthropogenic compounds. During the previous 2008–09 study at Jackson Hole Airport, diesel-range organics were measured in small (estimated) concentrations in several samples. Samples collected from all 10 wells sampled during the 2011–12 study were analyzed for diesel-range organics, and there were no detections; however, several other anthropogenic compounds were detected in groundwater samples during water years 2011—12 that were not detected during the previous 2008–09 study. Gasoline-range organics, benzene, ethylbenzene, and total xylene were each detected (but reported as estimated concentrations) in at least one groundwater sample. These compounds were not detected during the previous study or consistently during this study. Several possible reasons these compounds were not detected consistently include (1) these compounds are present in the aquifer at concentrations near the analytical method detection limit and are difficult to detect, (2) these compounds were not from a persistent source during this study, and (3) these compounds were detected because of contamination introduced during sampling or analysis. During water years 2011–2012, groundwater samples were analyzed for triazoles, specifically benzotriazole, 4-methyl-1H-benzotriazole, and 5-methyl-1H-benzotriazole. Triazoles are anthropogenic compounds often used as an additive in deicing and anti-icing fluids as a corrosion inhibitor, and can be detected at lower laboratory reporting levels than glycols, which previously had not been detected. Two of the three triazoles measured, 4-methyl-1H-benzotriazole and 5-methyl-1H-benzotriazole, were detected at low concentrations in groundwater at 7 of the 10 wells sampled. The detection of triazole compounds in groundwater downgradient from airport operations makes it unlikely there is a natural cause for the high rates of reduction present in many airport monitor wells. It is more likely that aircraft deicers, anti-icers, or pavement deicers have seeped into the groundwater system and caused the reducing conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135184","collaboration":"Prepared in cooperation with the Jackson Hole Airport Board","usgsCitation":"Wright, P., 2013, Hydrogeology and water quality in the Snake River alluvial aquifer at Jackson Hole Airport, Jackson, Wyoming, water years 2011 and 2012: U.S. Geological Survey Scientific Investigations Report 2013-5184, vii, 56 p., https://doi.org/10.3133/sir20135184.","productDescription":"vii, 56 p.","numberOfPages":"68","temporalStart":"2010-10-01","temporalEnd":"2012-09-30","ipdsId":"IP-042348","costCenters":[{"id":684,"text":"Wyoming Water Science Center","active":false,"usgs":true}],"links":[{"id":280625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135184.jpg"},{"id":280624,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5184/pdf/sir2013-5184.pdf"},{"id":280623,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5184/"}],"projection":"Lambert Conformal Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Wyoming","city":"Jackson","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.047058,43.400059 ], [ -111.047058,43.899871 ], [ -110.398865,43.899871 ], [ -110.398865,43.400059 ], [ -111.047058,43.400059 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52cbd082e4b03116c9ddb9fc","contributors":{"authors":[{"text":"Wright, Peter R. prwright@usgs.gov","contributorId":1828,"corporation":false,"usgs":true,"family":"Wright","given":"Peter R.","email":"prwright@usgs.gov","affiliations":[],"preferred":true,"id":485917,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70059914,"text":"70059914 - 2013 - The effect of sampling rate and anti-aliasing filters on high-frequency response spectra","interactions":[],"lastModifiedDate":"2014-02-17T10:29:44","indexId":"70059914","displayToPublicDate":"2014-01-06T09:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1101,"text":"Bulletin of Earthquake Engineering","active":true,"publicationSubtype":{"id":10}},"title":"The effect of sampling rate and anti-aliasing filters on high-frequency response spectra","docAbstract":"The most commonly used intensity measure in ground-motion prediction equations is the pseudo-absolute response spectral acceleration (PSA), for response periods from 0.01 to 10 s (or frequencies from 0.1 to 100 Hz). PSAs are often derived from recorded ground motions, and these motions are usually filtered to remove high and low frequencies before the PSAs are computed. In this article we are only concerned with the removal of high frequencies. In modern digital recordings, this filtering corresponds at least to an anti-aliasing filter applied before conversion to digital values. Additional high-cut filtering is sometimes applied both to digital and to analog records to reduce high-frequency noise. Potential errors on the short-period (high-frequency) response spectral values are expected if the true ground motion has significant energy at frequencies above that of the anti-aliasing filter. This is especially important for areas where the instrumental sample rate and the associated anti-aliasing filter corner frequency (above which significant energy in the time series is removed) are low relative to the frequencies contained in the true ground motions. A ground-motion simulation study was conducted to investigate these effects and to develop guidance for defining the usable bandwidth for high-frequency PSA. The primary conclusion is that if the ratio of the maximum Fourier acceleration spectrum (FAS) to the FAS at a frequency fsaa corresponding to the start of the anti-aliasing filter is more than about 10, then PSA for frequencies above fsaa should be little affected by the recording process, because the ground-motion frequencies that control the response spectra will be less than fsaa . A second topic of this article concerns the resampling of the digital acceleration time series to a higher sample rate often used in the computation of short-period PSA. We confirm previous findings that sinc-function interpolation is preferred to the standard practice of using linear time interpolation for the resamplin","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of Earthquake Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10518-013-9574-9","usgsCitation":"Boore, D.M., and Goulet, C., 2013, The effect of sampling rate and anti-aliasing filters on high-frequency response spectra: Bulletin of Earthquake Engineering, v. 12, no. 1, p. 203-216, https://doi.org/10.1007/s10518-013-9574-9.","productDescription":"14 p.","startPage":"203","endPage":"216","ipdsId":"IP-052513","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":280620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280618,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10518-013-9574-9"}],"volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-12-25","publicationStatus":"PW","scienceBaseUri":"52cbd083e4b03116c9ddba08","contributors":{"authors":[{"text":"Boore, David M. boore@usgs.gov","contributorId":2509,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":487851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goulet, Christine","contributorId":97812,"corporation":false,"usgs":true,"family":"Goulet","given":"Christine","affiliations":[],"preferred":false,"id":487852,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70095532,"text":"70095532 - 2013 - Megathrust splay faults at the focus of the Prince William Sound asperity, Alaska","interactions":[],"lastModifiedDate":"2023-11-07T11:47:56.268815","indexId":"70095532","displayToPublicDate":"2014-01-05T12:45:04","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Megathrust splay faults at the focus of the Prince William Sound asperity, Alaska","docAbstract":"High-resolution sparker and crustal-scale air gun seismic reflection data, coupled with repeat bathymetric surveys, document a region of repeated coseismic uplift on the portion of the Alaska subduction zone that ruptured in 1964. This area defines the western limit of Prince William Sound. Differencing of vintage and modern bathymetric surveys shows that the region of greatest uplift related to the 1964 Great Alaska earthquake was focused along a series of subparallel faults beneath Prince William Sound and the adjacent Gulf of Alaska shelf. Bathymetric differencing indicates that 12 m of coseismic uplift occurred along two faults that reached the seafloor as submarine terraces on the Cape Cleare bank southwest of Montague Island. Sparker seismic reflection data provide cumulative Holocene slip estimates as high as 9 mm/yr along a series of splay thrust faults within both the inner wedge and transition zone of the accretionary prism. Crustal seismic data show that these megathrust splay faults root separately into the subduction zone décollement. Splay fault divergence from this megathrust correlates with changes in midcrustal seismic velocity and magnetic susceptibility values, best explained by duplexing of the subducted Yakutat terrane rocks above Pacific plate rocks along the trailing edge of the Yakutat terrane. Although each splay fault is capable of independent motion, we conclude that the identified splay faults rupture in a similar pattern during successive megathrust earthquakes and that the region of greatest seismic coupling has remained consistent throughout the Holocene.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/jgrb.50372","usgsCitation":"Liberty, L.M., Finn, S.P., Haeussler, P.J., Pratt, T.L., and Peterson, A., 2013, Megathrust splay faults at the focus of the Prince William Sound asperity, Alaska: Journal of Geophysical Research, v. 118, no. 10, p. 5428-5441, https://doi.org/10.1002/jgrb.50372.","productDescription":"14 p.","startPage":"5428","endPage":"5441","ipdsId":"IP-052743","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":283836,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154,\n 55.75\n ],\n [\n -144,\n 55.75\n ],\n [\n -144,\n 62\n ],\n [\n -154,\n 62\n ],\n [\n -154,\n 55.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"118","issue":"10","noUsgsAuthors":false,"publicationDate":"2013-10-17","publicationStatus":"PW","scienceBaseUri":"53cd6684e4b0b29085100ceb","contributors":{"authors":[{"text":"Liberty, Lee M.","contributorId":89631,"corporation":false,"usgs":true,"family":"Liberty","given":"Lee","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":491272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finn, Shaun P.","contributorId":75438,"corporation":false,"usgs":true,"family":"Finn","given":"Shaun","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":491271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":491268,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pratt, Thomas L. 0000-0003-3131-3141 tpratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3131-3141","contributorId":3279,"corporation":false,"usgs":true,"family":"Pratt","given":"Thomas","email":"tpratt@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":491269,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peterson, Andrew","contributorId":41732,"corporation":false,"usgs":true,"family":"Peterson","given":"Andrew","affiliations":[],"preferred":false,"id":491270,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70049036,"text":"fs20133095 - 2013 - Mountain pine beetle impacts on vegetation and carbon stocks","interactions":[],"lastModifiedDate":"2014-01-03T12:37:28","indexId":"fs20133095","displayToPublicDate":"2014-01-04T12:31:43","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3095","title":"Mountain pine beetle impacts on vegetation and carbon stocks","docAbstract":"In the Southern Rocky Mountains, an epidemic outbreak of mountain pine beetle (Dendroctonus ponderosae; MPB) has caused levels of tree mortality unprecedented in recorded history. The impacts of this mortality on vegetation composition, forest structure, and carbon stocks have only recently received attention, although the impacts of other disturbances such as fires and land-use/land-cover change are much better known. This study, initiated in 2010, aims to increase our understanding of MPB outbreaks and their impacts. We have integrated field-collected data with vegetation simulation models to assess and quantify how long-term patterns of vegetation and carbon stocks have and may change in response to MPB outbreaks and other disturbances.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133095","usgsCitation":"Hawbaker, T., Briggs, J., Caldwell, M.K., and Stitt, S., 2013, Mountain pine beetle impacts on vegetation and carbon stocks: U.S. Geological Survey Fact Sheet 2013-3095, 2 p., https://doi.org/10.3133/fs20133095.","productDescription":"2 p.","ipdsId":"IP-049649","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":280602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133095.jpg"},{"id":280600,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3095/pdf/fs2013-3095.pdf"},{"id":280601,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3095/"}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.06,36.99 ], [ -109.06,41.0 ], [ -102.04,41.0 ], [ -102.04,36.99 ], [ -109.06,36.99 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c92d93e4b03cb62a1b0784","contributors":{"authors":[{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":486061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Jennifer S.","contributorId":101167,"corporation":false,"usgs":true,"family":"Briggs","given":"Jennifer S.","affiliations":[],"preferred":false,"id":486064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Megan K. mcaldwell@usgs.gov","contributorId":4243,"corporation":false,"usgs":true,"family":"Caldwell","given":"Megan","email":"mcaldwell@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":486063,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stitt, Susan susan_stitt@usgs.gov","contributorId":1410,"corporation":false,"usgs":true,"family":"Stitt","given":"Susan","email":"susan_stitt@usgs.gov","affiliations":[],"preferred":true,"id":486062,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70049005,"text":"sim3278 - 2013 - Flood-inundation maps for a 6.5-mile reach of the Kentucky River at Frankfort, Kentucky","interactions":[],"lastModifiedDate":"2014-01-03T10:44:30","indexId":"sim3278","displayToPublicDate":"2014-01-03T10:27:48","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3278","title":"Flood-inundation maps for a 6.5-mile reach of the Kentucky River at Frankfort, Kentucky","docAbstract":"Digital flood-inundation maps for a 6.5-mile reach of Kentucky River at Frankfort, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Frankfort Office of Emergency Management. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage Kentucky River at Lock 4 at Frankfort, Kentucky (station no. 03287500). Current conditions for the USGS streamgage may be obtained online at the USGS National Water Information System site (http://waterdata.usgs.gov/nwis/inventory?agency_code=USGS&site_no=03287500). In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http:/water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated at USGS streamgages. The forecasted peak-stage information, also available on the Internet, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the Kentucky River reach by using HEC–RAS, a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current (2013) stage-discharge relation for the Kentucky River at Lock 4 at Frankfort, Kentucky, in combination with streamgage and high-water-mark measurements collected for a flood event in May 2010. The calibrated model was then used to calculate 26 water-surface profiles for a sequence of flood stages, at 1-foot intervals, referenced to the streamgage datum and ranging from a stage near bankfull to the elevation that breached the levees protecting the City of Frankfort. To delineate the flooded area at each interval flood stage, the simulated water-surface profiles were combined with a digital elevation model (DEM) of the study area by using geographic information system software. The DEM consisted of bare-earth elevations within the study area and was derived from a Light Detection And Ranging (LiDAR) dataset having a 5.0-foot horizontal resolution and an accuracy of 0.229 foot. The availability of these maps, along with Internet information regarding current stages from USGS streamgages and forecasted stages from the NWS, provides emergency management personnel and local residents with critical information for flood response activities such as evacuations, road closures, and postflood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3278","collaboration":"Prepared in cooperation with City of Frankfort, Kentucky, Office of Emergency Management","usgsCitation":"Lant, J.G., 2013, Flood-inundation maps for a 6.5-mile reach of the Kentucky River at Frankfort, Kentucky: U.S. Geological Survey Scientific Investigations Map 3278, Report: vi, 10 p.; Low Resolution and High Resolution Map Sheets; Downloads Directory, https://doi.org/10.3133/sim3278.","productDescription":"Report: vi, 10 p.; Low Resolution and High Resolution Map Sheets; Downloads Directory","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-045182","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":280591,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3278/"},{"id":280592,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3278/pdf/sim3278.pdf"},{"id":280593,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3278/PDF-mapSheets/"},{"id":280594,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3278/downloads/"},{"id":280595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3278.jpg"}],"projection":"Lambert Conformal Conic","datum":"North American Datum of 1983","country":"United States","state":"Kentucky","city":"Fankfort","otherGeospatial":"Kentucky River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.916,38.15 ], [ -84.916,38.233 ], [ -84.816,38.233 ], [ -84.816,38.15 ], [ -84.916,38.15 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c7dbe1e4b0a753c7d3e375","contributors":{"authors":[{"text":"Lant, Jeremiah G. 0000-0001-6688-4820 jlant@usgs.gov","orcid":"https://orcid.org/0000-0001-6688-4820","contributorId":4912,"corporation":false,"usgs":true,"family":"Lant","given":"Jeremiah","email":"jlant@usgs.gov","middleInitial":"G.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485986,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70055737,"text":"ofr20131255 - 2013 - seawaveQ: an R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables","interactions":[],"lastModifiedDate":"2017-10-12T20:16:54","indexId":"ofr20131255","displayToPublicDate":"2014-01-03T09:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1255","title":"seawaveQ: an R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables","docAbstract":"The seawaveQ R package fits a parametric regression model (seawaveQ) to pesticide concentration data from streamwater samples to assess variability and trends. The model incorporates the strong seasonality and high degree of censoring common in pesticide data and users can incorporate numerous ancillary variables, such as streamflow anomalies. The model is fitted to pesticide data using maximum likelihood methods for censored data and is robust in terms of pesticide, stream location, and degree of censoring of the concentration data. This R package standardizes this methodology for trend analysis, documents the code, and provides help and tutorial information, as well as providing additional utility functions for plotting pesticide and other chemical concentration data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131255","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Ryberg, K.R., and Vecchia, A.V., 2013, seawaveQ: an R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables: U.S. Geological Survey Open-File Report 2013-1255, Report: iv, 13 p.; Downloads Directory, https://doi.org/10.3133/ofr20131255.","productDescription":"Report: iv, 13 p.; Downloads Directory","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-049192","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":280584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131255.jpg"},{"id":280570,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1255/"},{"id":280582,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1255/pdf/ofr13-1255.pdf.pdf"},{"id":280583,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1255/Downloads/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c7dc0ee4b0a753c7d3e47d","contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":41810,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":486258,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70057380,"text":"70057380 - 2013 - Quantifying potential earthquake and tsunami hazard in the Lesser Antilles subduction zone of the Caribbean region","interactions":[],"lastModifiedDate":"2014-02-11T14:36:24","indexId":"70057380","displayToPublicDate":"2014-01-01T14:23:11","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying potential earthquake and tsunami hazard in the Lesser Antilles subduction zone of the Caribbean region","docAbstract":"In this study, we quantify the seismic and tsunami hazard in the Lesser Antilles subduction zone, focusing on the plate interface offshore of Guadeloupe. We compare potential strain accumulated via GPS-derived plate motions to strain release due to earthquakes that have occurred over the past 110 yr, and compute the resulting moment deficit. Our results suggest that enough strain is currently stored in the seismogenic zone of the Lesser Antilles subduction arc in the region of Guadeloupe to cause a large and damaging earthquake of magnitude Mw ∼ 8.2 ± 0.4. We model several scenario earthquakes over this magnitude range, using a variety of earthquake magnitudes and rupture areas, and utilizing the USGS ShakeMap and PAGER software packages. Strong ground shaking during the earthquake will likely cause loss of life and damage estimated to be in the range of several tens to several hundreds of fatalities and hundreds of millions to potentially billions of U.S. dollars of damage. In addition, such an event could produce a significant tsunami. Modelled tsunamis resulting from these scenario earthquakes predict meter-scale wave amplitudes even for events at the lower end of our magnitude range (M 7.8), and heights of over 3 m in several locations with our favoured scenario (M 8.0, partially locked interface from 15–45 km depth). In all scenarios, only short lead-times (on the order of tens of minutes) would be possible in the Caribbean before the arrival of damaging waves.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Journal International","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Oxford University Press","doi":"10.1093/gji/ggt385","usgsCitation":"Hayes, G., McNamara, D.E., Seidman, L., and Roger, J., 2013, Quantifying potential earthquake and tsunami hazard in the Lesser Antilles subduction zone of the Caribbean region: Geophysical Journal International, v. 196, no. 1, p. 510-521, https://doi.org/10.1093/gji/ggt385.","productDescription":"12 p.","startPage":"510","endPage":"521","ipdsId":"IP-052110","costCenters":[{"id":415,"text":"National Earthquake Information Center","active":false,"usgs":true}],"links":[{"id":473366,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggt385","text":"Publisher Index Page"},{"id":282278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282276,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1093/gji/ggt385"}],"country":"Guadeloupe","otherGeospatial":"Lesser Antilles","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90,0 ], [ -90,8.333333333333334E-4 ], [ -50,8.333333333333334E-4 ], [ -50,0 ], [ -90,0 ] ] ] } } ] }","volume":"196","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-11-20","publicationStatus":"PW","scienceBaseUri":"53cd6ec8e4b0b29085105fe6","contributors":{"authors":[{"text":"Hayes, Gavin P. 0000-0003-3323-0112","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":6157,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":486661,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNamara, Daniel E. 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":402,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":486660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seidman, Lily","contributorId":81017,"corporation":false,"usgs":true,"family":"Seidman","given":"Lily","email":"","affiliations":[],"preferred":false,"id":486662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roger, Jean","contributorId":81804,"corporation":false,"usgs":true,"family":"Roger","given":"Jean","email":"","affiliations":[],"preferred":false,"id":486663,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70038467,"text":"70038467 - 2013 - Insights and issues with simulating terrestrial DOC loading of Arctic river networks","interactions":[],"lastModifiedDate":"2015-06-17T13:19:15","indexId":"70038467","displayToPublicDate":"2014-01-01T14:02:49","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Insights and issues with simulating terrestrial DOC loading of Arctic river networks","docAbstract":"Terrestrial carbon dynamics influence the contribution of dissolved organic carbon (DOC) to river networks in addition to hydrology. In this study, we use a biogeochemical process model to simulate the lateral transfer of DOC from land to the Arctic Ocean via riverine transport. We estimate that, over the 20th century, the pan-Arctic watershed has contributed, on average, 32 Tg C/yr of DOC to river networks emptying into the Arctic Ocean with most of the DOC coming from the extensive area of boreal deciduous needle-leaved forests and forested wetlands in Eurasian watersheds. We also estimate that the rate of terrestrial DOC loading has been increasing by 0.037 Tg C/yr2 over the 20th century primarily as a result of climate-induced increases in water yield. These increases have been offset by decreases in terrestrial DOC loading caused by wildfires. Other environmental factors (CO2 fertilization, ozone pollution, atmospheric nitrogen deposition, timber harvest, agriculture) are estimated to have relatively small effects on terrestrial DOC loading to Arctic rivers. The effects of the various environmental factors on terrestrial carbon dynamics have both offset and enhanced concurrent effects on hydrology to influence terrestrial DOC loading and may be changing the relative importance of terrestrial carbon dynamics on this carbon flux. Improvements in simulating terrestrial DOC loading to pan-Arctic rivers in the future will require better information on the production and consumption of DOC within the soil profile, the transfer of DOC from land to headwater streams, the spatial distribution of precipitation and its temporal trends, carbon dynamics of larch-dominated ecosystems in eastern Siberia, and the role of industrial organic effluents on carbon budgets of rivers in western Russia.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/11-1050.1","usgsCitation":"Kicklighter, D.W., Hayes, D.J., McClelland, J.W., Peterson, B.J., McGuire, A., and Melillo, J.M., 2013, Insights and issues with simulating terrestrial DOC loading of Arctic river networks: Ecological Applications, v. 23, no. 8, p. 1817-1836, https://doi.org/10.1890/11-1050.1.","productDescription":"20 p.","startPage":"1817","endPage":"1836","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-032239","costCenters":[{"id":108,"text":"Alaska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":473368,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/6466","text":"External Repository"},{"id":282846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282845,"type":{"id":11,"text":"Document"},"url":"https://www.lter.uaf.edu/pdf/1632_Kicklighter_Hayes_2013.pdf"}],"otherGeospatial":"Arctic","volume":"23","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd62a5e4b0b290850fe513","contributors":{"authors":[{"text":"Kicklighter, David W.","contributorId":48872,"corporation":false,"usgs":false,"family":"Kicklighter","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":464295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Daniel J.","contributorId":100237,"corporation":false,"usgs":true,"family":"Hayes","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":464299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McClelland, James W.","contributorId":94905,"corporation":false,"usgs":true,"family":"McClelland","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":464298,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peterson, Bruce J.","contributorId":62453,"corporation":false,"usgs":true,"family":"Peterson","given":"Bruce","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":464296,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGuire, A. David","contributorId":18494,"corporation":false,"usgs":true,"family":"McGuire","given":"A. David","affiliations":[],"preferred":false,"id":464294,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Melillo, Jerry M.","contributorId":87847,"corporation":false,"usgs":false,"family":"Melillo","given":"Jerry","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":464297,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}