The key to Eastern Meadowlark (Sturnella magna) management is providing large areas of contiguous grassland of moderate height with significant grass cover and moderate forb density. Eastern Meadowlarks have been reported to use habitats with 10–187 centimeters (cm) average vegetation height, 6–88 cm visual obstruction reading, 53–86 percent grass cover, 4–50 percent forb cover, less than or equal to (≤) 4 percent shrub cover, less than 38 percent bare ground, 6–23 percent litter cover, and ≤13 cm litter depth.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842MM","usgsCitation":"Hull, S.D., Shaffer, J.A., and Igl, L.D., 2019, The effects of management practices on grassland birds—Eastern Meadowlark (Sturnella magna), chap. MM of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 26 p., https://doi.org/10.3133/pp1842MM.","productDescription":"iv, 26 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":367879,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/mm/coverthb.jpg"},{"id":367880,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/mm/pp1842mm.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–MM"}],"contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
In 2015, the U.S. Geological Survey, in cooperation with the Iroquois River Conservancy District, deployed continuous water-quality monitors and began collecting representative discrete water-quality samples at the Iroquois River near Foresman, Indiana, streamflow-gaging station (U.S. Geological Survey station 05524500). By relating continuously monitored water-quality data and discrete water-quality samples collected from April 2015 through July 2018, regression models that estimate concentrations of suspended sediment, total nitrogen, and total phosphorus were developed. Developed regression models indicated a strong correlation between turbidity and streamflow with suspended-sediment concentration (adjusted coefficient of determination equals 0.84, predicted residual error sum of squares equals 0.493), nitrate plus nitrite and streamflow with total nitrogen (adjusted coefficient of determination equals 0.99, predicted residual error sum of squares equals 0.0202), and specific conductance and turbidity with total phosphorus (adjusted coefficient of determination equals 0.84, predicted residual error sum of squares equals 0.0935).
Daily loads of suspended sediment, total nitrogen, and total phosphorus were computed as the product of daily mean regression model concentrations and daily mean streamflow. During periods when regression model concentrations could not be computed, rloadest models, the R programming language version of the LOADEST FORTRAN program, were used to compute daily loads of each constituent. For 2016 and 2017, the estimated annual suspended-sediment loads were 25,000 and 32,100 tons; estimated total nitrogen loads were 4,260 and 5,780 tons; and estimated total phosphorus loads were 104 and 128 tons, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195087","collaboration":"Prepared in cooperation with the Iroquois River Conservancy District","usgsCitation":"Lathrop, T.R., Bunch, A.R., Downhour, M.S., and Perkins, D.M., 2019, Regression models for estimating sediment and nutrient concentrations and loads at the Iroquois River near Foresman, Indiana, March 2015 through July 2018: U.S. Geological Survey Scientific Investigation Report 2019–5087, 14 p., https://doi.org/10.3133/sir20195087.","productDescription":"Report: vi, 14 p.; Data Releases","numberOfPages":"24","ipdsId":"IP-107470","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":368030,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YCAELC","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data and regression models for total nitrogen and total phosphorus for the Iroquois River near Foresman, Indiana, March 20, 2015, to July 19, 2018"},{"id":368029,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RFLONI","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data and regression model for suspended sediment for Iroquois River near Foresman, Indiana, March 20, 2015, to July 19, 2018"},{"id":368028,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91FL2GY","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Suspended sediment, total nitrogen, and total phosphorus loads for Iroquois River near Foresman, Indiana, April 2015 to July 2018"},{"id":368027,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5087/sir20195087.pdf","text":"Report","size":"855 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5087"},{"id":368026,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5087/coverthb.jpg"}],"country":"United States","state":"Indiana","county":"Newton County","city":"Foresman","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-87.5263,41.1661],[-87.4801,41.1701],[-87.4587,41.1702],[-87.4484,41.1744],[-87.4466,41.174],[-87.4411,41.1731],[-87.4147,41.1619],[-87.4055,41.1625],[-87.4,41.1625],[-87.394,41.1625],[-87.38,41.1726],[-87.3448,41.1824],[-87.3405,41.1824],[-87.3313,41.1829],[-87.3241,41.1862],[-87.2859,41.2154],[-87.2762,41.2187],[-87.2757,41.1733],[-87.2754,41.0866],[-87.275,40.9991],[-87.2768,40.9405],[-87.2759,40.9133],[-87.268,40.9134],[-87.2664,40.8249],[-87.2655,40.7383],[-87.3807,40.738],[-87.4905,40.7381],[-87.5263,40.7378],[-87.5263,40.741],[-87.5265,40.839],[-87.5262,40.981],[-87.5262,40.9832],[-87.5265,41.0142],[-87.5264,41.1231],[-87.5263,41.1661]]]},\"properties\":{\"name\":\"Newton\",\"state\":\"IN\"}}]}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278
Understanding how stream fishes respond to changes in habitat availability is complicated by low occurrence rates of many species, which in turn reduces the ability to quantify species–habitat relationships and account for imperfect detection in estimates of species richness. Multispecies occupancy models have been used sparingly in the analysis of fisheries data, but address the aforementioned deficiencies by allowing information to be shared among ecologically similar species, thereby enabling species–habitat relationships to be estimated for entire fish communities, including rare species. Here, we highlight the utility of hierarchical multispecies occupancy models for the analysis of fish community data and demonstrate the modeling framework on a stream fish community dataset collected in the Delaware Water Gap National Recreation Area, USA. In particular, we demonstrate the ability of the modeling framework to make inferences at the species-, guild-, and community-levels, thereby making it a powerful tool for understanding and predicting how environmental variables influence species occupancy probabilities and structure fish assemblages.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2019-0125","collaboration":"National Park Service","usgsCitation":"White, S., Faulk, E., Tzilkowski, C., Weber, A., Marshall, M., and Wagner, T., 2019, Predicting fish species richness and habitat relationships using Bayesian hierarchical multispecies occupancy models: Canadian Journal Fisheries and Aquatic Sciences, v. 77, no. 3, 9 p., https://doi.org/10.1139/cjfas-2019-0125.","productDescription":"9 p.","ipdsId":"IP-101955","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":388400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York New Jersey, Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.12451171875,\n 40.96330795307353\n ],\n [\n -74.15771484375,\n 40.96330795307353\n ],\n [\n -74.15771484375,\n 41.60722821271717\n ],\n [\n -75.12451171875,\n 41.60722821271717\n ],\n [\n -75.12451171875,\n 40.96330795307353\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"77","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"White, Shannon","contributorId":264595,"corporation":false,"usgs":false,"family":"White","given":"Shannon","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":821720,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faulk, Evan","contributorId":264596,"corporation":false,"usgs":false,"family":"Faulk","given":"Evan","email":"","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":821721,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tzilkowski, Caleb","contributorId":264597,"corporation":false,"usgs":false,"family":"Tzilkowski","given":"Caleb","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":821722,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weber, Andrew","contributorId":264598,"corporation":false,"usgs":false,"family":"Weber","given":"Andrew","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":821723,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marshall, Matt","contributorId":264599,"corporation":false,"usgs":false,"family":"Marshall","given":"Matt","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":821724,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":821719,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208122,"text":"70208122 - 2019 - Estimating sightability of greater sage-grouse at leks using an aerial infrared system and N-mixture models","interactions":[],"lastModifiedDate":"2020-01-29T16:24:01","indexId":"70208122","displayToPublicDate":"2019-10-03T13:36:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3766,"text":"Wildlife Biology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating sightability of greater sage-grouse at leks using an aerial infrared system and N-mixture models","docAbstract":"Counts of grouse present at leks (breeding grounds) during spring are widely used to monitor population numbers and assess trends. However, only a proportion of birds available to count are detected resulting in a biased population index. We designed a study using an aerial integrated infrared imaging system (AIRIS) and experimental pseudo-leks to quantify sightability (proportion of birds detected) of conventional ground-based visual (GBV) surveys for greater sage-grouse Centrocercus urophasianus. Specifically, we calibrated AIRIS at pseudo-leks composed of known numbers of captively-raised birds, primarily ring-necked pheasant Phasianus colchicus. We then carried out AIRIS and GBV surveys, simultaneously, on nearby sage-grouse leks, allowing us to model AIRIS and GBV sightability. AIRIS detected ∼93% of birds on pseudo-leks while GBV detected ∼86% of sage-grouse on leks. Thus, the ground count observation error was –14% from the ‘true' number of male sage-grouse attending the leks. We also found sagebrush cover decreased sightability for GBV counts but did not influence sightability by AIRIS. Because standard GBV protocols typically make repeated counts of sage-grouse in a single morning, we also modeled repeated GBV counts using N-mixture models and found an 88% sightability, which was nearly the same as GBV sightability from the AIRIS analysis. This suggests that the use of repeated morning counts can potentially account for imperfect detection in the standard GBV surveys currently implemented. We also provide generalized correction values that could be employed by resource managers using either GBV or AIRIS to better estimate ‘true’ numbers of sage-grouse attending leks within similar environments to this study. The findings and interpretation presented can help guide effective monitoring protocols that account for observation error and improve accuracy of data used for population trend and abundance estimation.
","language":"English","publisher":"BioONE","doi":"10.2981/wlb.00552","usgsCitation":"Coates, P.S., Wann, G.T., Gillette, G.L., Ricca, M.A., Prochazka, B.G., Severson, J.P., Andrle, K.M., Espinosa, S.P., Casazza, M.L., and Delehanty, D.J., 2019, Estimating sightability of greater sage-grouse at leks using an aerial infrared system and N-mixture models: Wildlife Biology, v. 2019, no. 1, wlb.00552, 11 p., https://doi.org/10.2981/wlb.00552.","productDescription":"wlb.00552, 11 p.","ipdsId":"IP-100795","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":459615,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2981/wlb.00552","text":"Publisher Index Page"},{"id":371652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.81640624999999,\n 39.16414104768742\n ],\n [\n -112.08251953125,\n 39.16414104768742\n ],\n [\n -112.08251953125,\n 44.88701247981298\n ],\n [\n -121.81640624999999,\n 44.88701247981298\n ],\n [\n -121.81640624999999,\n 39.16414104768742\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2019","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wann, Gregory T. 0000-0001-9076-7819 wanng@usgs.gov","orcid":"https://orcid.org/0000-0001-9076-7819","contributorId":3855,"corporation":false,"usgs":true,"family":"Wann","given":"Gregory","email":"wanng@usgs.gov","middleInitial":"T.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gillette, Gifford L.","contributorId":221864,"corporation":false,"usgs":false,"family":"Gillette","given":"Gifford","email":"","middleInitial":"L.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":780572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Severson, John P. 0000-0002-1754-6689","orcid":"https://orcid.org/0000-0002-1754-6689","contributorId":213469,"corporation":false,"usgs":true,"family":"Severson","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780575,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Andrle, Katie M.","contributorId":221865,"corporation":false,"usgs":false,"family":"Andrle","given":"Katie","email":"","middleInitial":"M.","affiliations":[{"id":27489,"text":"Nevada Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":780576,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Espinosa, Shawn P.","contributorId":195583,"corporation":false,"usgs":false,"family":"Espinosa","given":"Shawn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":780577,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780578,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Delehanty, David J.","contributorId":195584,"corporation":false,"usgs":false,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":780579,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70205773,"text":"70205773 - 2019 - Prediction and inference of flow-duration curves using multi-output neural networks","interactions":[],"lastModifiedDate":"2019-10-02T12:09:28","indexId":"70205773","displayToPublicDate":"2019-10-02T12:06:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Prediction and inference of flow-duration curves using multi-output neural networks","docAbstract":"We develop multi-output neural network models (MNNs) to predict flow-duration curves (FDCs) in 9,203 ungaged locations in the Southeastern United States for six decades between 1950-2009. The model architecture contains multiple response variables in the output layer that correspond to individual quantiles along the FDC. During training, predictions are made for each quantile, and a combined loss function is used for back propagation and parameter updating. The loss function accounts for the covariance between the quantiles and generates physically consistent outputs (i.e., monotonically increasing quantiles with increasing nonexceedance probabilities). We use neural-network dropout to generate posterior-predictive distributions for FDCs, and test model performance under cross validation. Finally, we demonstrate how local surrgotate models, via the Local Interpretable Model-agnostic Explanations (LIME) method, can be used to infer the relation between basin characteristics and the predicted FDCs. Results suggest that MNNs can learn the monotonic relations between adjacent quantiles on an FDC, they result in better predictions than single output neural-network models that predict each quantile independently, and basin characteristics are most useful for predicting smaller quantiles, whereas bias terms from neighboring quantiles are most informative for predicting higher quantiles.","language":"English","publisher":"Wiley","doi":"10.1029/2018WR024463","usgsCitation":"Worland, S.C., Steinschneider, S., Asquith, W.H., Knight, R., and Wieczorek, M., 2019, Prediction and inference of flow-duration curves using multi-output neural networks: Water Resources Research, v. 55, no. 8, p. 6850-6868, https://doi.org/10.1029/2018WR024463.","productDescription":"19 p.","startPage":"6850","endPage":"6868","onlineOnly":"N","ipdsId":"IP-091599","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":459623,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018wr024463","text":"Publisher Index Page"},{"id":437314,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YGKZZV","text":"USGS data release","linkHelpText":"Estimated quantiles for the pour points of 9,203 level-12 Hydrologic Unit Code in the Southeastern United States--1950--2010"},{"id":367923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Worland, Scott C. 0000-0001-6384-2457 scworland@usgs.gov","orcid":"https://orcid.org/0000-0001-6384-2457","contributorId":5802,"corporation":false,"usgs":true,"family":"Worland","given":"Scott","email":"scworland@usgs.gov","middleInitial":"C.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steinschneider, Scott 0000-0002-8882-1908","orcid":"https://orcid.org/0000-0002-8882-1908","contributorId":206359,"corporation":false,"usgs":false,"family":"Steinschneider","given":"Scott","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":772283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772284,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knight, Rodney 0000-0001-9588-0167 rrknight@usgs.gov","orcid":"https://orcid.org/0000-0001-9588-0167","contributorId":152422,"corporation":false,"usgs":true,"family":"Knight","given":"Rodney","email":"rrknight@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772285,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wieczorek, Michael E. 0000-0003-0999-5457 mewieczo@usgs.gov","orcid":"https://orcid.org/0000-0003-0999-5457","contributorId":178736,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael E.","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772286,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70205674,"text":"70205674 - 2019 - A multidisciplinary coastal vulnerability assessment for local government focused on ecosystems, Santa Barbara area, California","interactions":[],"lastModifiedDate":"2019-11-13T13:43:35","indexId":"70205674","displayToPublicDate":"2019-10-02T11:26:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2926,"text":"Ocean and Coastal Management","active":true,"publicationSubtype":{"id":10}},"title":"A multidisciplinary coastal vulnerability assessment for local government focused on ecosystems, Santa Barbara area, California","docAbstract":"Incorporating coastal ecosystems in climate adaptation planning is needed to maintain the well-being of both natural and human systems. Our vulnerability study uses a multidisciplinary approach to evaluate climate change vulnerability of an urbanized coastal community that could serve as a model approach for communities worldwide, particularly in similar Mediterranean climates. We synthesize projected changes in climate, coastal erosion and flooding, watershed runoff and impacts to two important coastal ecosystems, sandy beaches and coastal salt marshes. Using downscaled climate models along with other regional models, we find that temperature, extreme heat events, and sea level are expected to increase in the future, along with more intense rainfall events, despite a negligible change in annual rainfall. Consequently, more droughts are expected but the magnitude of larger flood events will increase. Associated with the continuing rise of mean sea level, extreme coastal water levels will occur with increasingly greater magnitudes and frequency. Severe flooding will occur for both natural (wetlands, beaches) and built environments (airport, harbor, freeway, and residential areas). Adaptation actions can reduce the impact of rising sea level, which will cause losses of sandy beach zones and salt marsh habitats that support the highest biodiversity in these ecosystems, including regionally rare and endangered species, with substantial impacts occurring by 2050. Providing for inland transgression of coastal habitats, effective sediment management, reduced beach grooming and removal of shoreline armoring are adaptations that would help maintain coastal ecosystems and the beneficial services they provide.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocecoaman.2019.104921","usgsCitation":"Myers, M., Barnard, P., Beighley, E., Cayan, D., Dugan, J.E., Feng, D., Iacobellis, S.F., Melack, J.M., and Page, H.M., 2019, A multidisciplinary coastal vulnerability assessment for local government focused on ecosystems, Santa Barbara area, California: Ocean and Coastal Management, v. 182, 104921, https://doi.org/10.1016/j.ocecoaman.2019.104921.","productDescription":"104921","ipdsId":"IP-107676","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459626,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ocecoaman.2019.104921","text":"Publisher Index Page"},{"id":367925,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Santa Barbara","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.48249816894531,\n 34.41370754457088\n ],\n [\n -119.47906494140624,\n 34.4142740103038\n ],\n [\n -119.86564636230467,\n 34.44485746154028\n ],\n [\n -119.8773193359375,\n 34.36384353883067\n ],\n [\n -119.47631835937499,\n 34.36100946506246\n ],\n [\n -119.48249816894531,\n 34.41370754457088\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"182","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Myers, Monique","contributorId":219345,"corporation":false,"usgs":false,"family":"Myers","given":"Monique","email":"","affiliations":[{"id":39996,"text":"California Sea Grant","active":true,"usgs":false}],"preferred":false,"id":772060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":772059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beighley, Edward","contributorId":219346,"corporation":false,"usgs":false,"family":"Beighley","given":"Edward","email":"","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":772061,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cayan, Daniel R.","contributorId":219347,"corporation":false,"usgs":false,"family":"Cayan","given":"Daniel R.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":772062,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dugan, Jenifer E.","contributorId":219348,"corporation":false,"usgs":false,"family":"Dugan","given":"Jenifer","email":"","middleInitial":"E.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":772063,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Feng, Dongmei","contributorId":219349,"corporation":false,"usgs":false,"family":"Feng","given":"Dongmei","email":"","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":772064,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Iacobellis, Samuel F.","contributorId":219350,"corporation":false,"usgs":false,"family":"Iacobellis","given":"Samuel","email":"","middleInitial":"F.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":772065,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Melack, John M.","contributorId":219351,"corporation":false,"usgs":false,"family":"Melack","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":772066,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Page, Henry M.","contributorId":219352,"corporation":false,"usgs":false,"family":"Page","given":"Henry","email":"","middleInitial":"M.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":772067,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70205702,"text":"70205702 - 2019 - A spatio-contextual probabilistic model for extracting linear features in hilly terrain from high-resolution DEM data","interactions":[],"lastModifiedDate":"2019-10-02T11:26:38","indexId":"70205702","displayToPublicDate":"2019-10-02T11:26:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2046,"text":"International Journal of Geographical Information Science","active":true,"publicationSubtype":{"id":10}},"title":"A spatio-contextual probabilistic model for extracting linear features in hilly terrain from high-resolution DEM data","docAbstract":"This paper introduces our research in developing a probabilistic model to extract linear terrain features from high resolution DEM (Digital Elevation Model) data. The proposed model takes full advantage of spatio-contextual information to characterize terrain changes. It first derives a quantifiable measure of spatio-contextual patterns of linear terrain feature, such as ridgelines, valley lines and crater boundaries, and then adopts multiple neighborhood analysis and a probability model to address data uncertainty in terrain surface modeling. Different from traditional approaches, the proposed model has the ability to achieve near-automated processing, and to support effective extraction of terrain features in both smooth and rough surfaces. Through a series of experiments, we demonstrate that the proposed approach outperforms existing techniques, including: thresholding, stream/drainage network analysis, visual descriptor, object-based image analysis and edge detection. We hope this work contributes to both the geospatial data science and geomorphology communities with a new way of utilizing high-resolution imagery in terrain analysis.","language":"English","publisher":"Taylor and Francis","doi":"10.1080/13658816.2018.1554814","usgsCitation":"Zhou, X., Li, W., and Arundel, S., 2019, A spatio-contextual probabilistic model for extracting linear features in hilly terrain from high-resolution DEM data: International Journal of Geographical Information Science, v. 33, no. 4, p. 666-686, https://doi.org/10.1080/13658816.2018.1554814.","productDescription":"21 p.","startPage":"666","endPage":"686","ipdsId":"IP-085062","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":367920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhou, Xiran","contributorId":219357,"corporation":false,"usgs":false,"family":"Zhou","given":"Xiran","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":772121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Wenwen 0000-0003-2237-9499","orcid":"https://orcid.org/0000-0003-2237-9499","contributorId":219356,"corporation":false,"usgs":false,"family":"Li","given":"Wenwen","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":772120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":772119,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205665,"text":"70205665 - 2019 - Modeling sediment bypassing around idealized rocky headlands","interactions":[],"lastModifiedDate":"2019-10-02T11:19:58","indexId":"70205665","displayToPublicDate":"2019-10-02T11:19:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Modeling sediment bypassing around idealized rocky headlands","docAbstract":"Alongshore sediment bypassing rocky headlands remains understudied despite the importance of characterizing littoral processes for erosion abatement, beach management, and climate change adaptation. To address this gap, a numerical model sediment transport study was developed to identify controlling factors and mechanisms for sediment headland bypassing potential. Four idealized headlands were designed to investigate sediment flux around the headlands using the process-based hydrodynamic model Delft-3D and spectral wave model SWAN. The 120 simulations explored morphologies, substrate compositions, sediment grain sizes, and physical forcings (i.e., tides, currents, and waves) commonly observed in natural settings. A generalized analytical framework based on flow disruption and sediment volume was used to refine which factors and conditions were more useful to address sediment bypassing. A bypassing parameter was developed for alongshore sediment flux between upstream and downstream cross-shore transects to determine the degree of blockage by a headland. The shape of the headland heavily influenced the fate of the sediment by changing the local angle between the shore and the incident waves, with oblique large waves generating the most flux. All headlands may allow sediment flux, although larger ones blocked sediment more effectively, promoting their ability to be littoral cell boundaries. The controlling factors on sediment bypassing were determined to be wave angle, size, and shape of the headland, and sediment grain size.
","language":"English","publisher":"MDPI","doi":"10.3390/jmse7020040","usgsCitation":"Douglas A. George, John L. Largier, Pasternack, G.B., Barnard, P., Storlazzi, C.D., and Erikson, L.H., 2019, Modeling sediment bypassing around idealized rocky headlands: Journal of Marine Science and Engineering, v. 7, no. 2, 40; 37 p., https://doi.org/10.3390/jmse7020040.","productDescription":"40; 37 p.","ipdsId":"IP-111887","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459632,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse7020040","text":"Publisher Index Page"},{"id":367918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Douglas A. George","contributorId":219341,"corporation":false,"usgs":false,"family":"Douglas A. George","affiliations":[{"id":39994,"text":"Bodega Marine Laboratory, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":772020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"John L. Largier","contributorId":219342,"corporation":false,"usgs":false,"family":"John L. Largier","affiliations":[{"id":39994,"text":"Bodega Marine Laboratory, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":772021,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pasternack, Greg B.","contributorId":219343,"corporation":false,"usgs":false,"family":"Pasternack","given":"Greg","email":"","middleInitial":"B.","affiliations":[{"id":39995,"text":"Department of Hydrologic Sciences, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":772022,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":772019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":772023,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":772024,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70205666,"text":"70205666 - 2019 - Regionalization of groundwater residence time using metamodeling","interactions":[],"lastModifiedDate":"2019-10-02T11:09:04","indexId":"70205666","displayToPublicDate":"2019-10-02T11:00:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Regionalization of groundwater residence time using metamodeling","docAbstract":"Groundwater residence-time distributions (RTDs) are critical for assessing susceptibility of water resources to degradation. A novel combination of numerical modeling and statistical methods allows estimation of regional RTDs with unprecedented speed. In this method, particle RTDs are generated in 30 type locales in the northeastern glaciated U.S using automated generalized finite-difference groundwater flow and advective transport models. Targets for statistical learning were created from particle RTDs by fitting Weibull, gamma, and inverse Gaussian distributions. Whole-basin flux-weighted RTDs were well fit by one-component Weibull distributions. Flux-weighted RTDs at stressed receptors such as wells often produced more complicated RTDs that required a two-component mixture to fit. A Multitask Lasso regression was trained on the parametric RTDs using hydrogeographic features of the modeled areas as explanatory features. In this way, RTDs are regionalized using mappable physical features such as recharge and aquifer volume. The shape, location, and scale parameters of the parametric RTDs are strongly related to the mean exponential age. The shape parameter of the distribution, which controls deviation from exponential, is additionally a function of aquifer heterogeneity and hydrologic features. Regionalized RTDs provide useful metrics with respect to groundwater lag times and solute loading to streams. The lag time between input and output contained in the RTD is critical to understanding the relation between the land surface and human and ecological receptors.","language":"English","publisher":"Wiley","doi":"10.1029/2017WR021531","usgsCitation":"Starn, J., and Belitz, K., 2019, Regionalization of groundwater residence time using metamodeling: Water Resources Research, v. 54, no. 9, p. 6357-6373, https://doi.org/10.1029/2017WR021531.","productDescription":"17 p.","startPage":"6357","endPage":"6373","ipdsId":"IP-086784","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":459636,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017wr021531","text":"Publisher Index Page"},{"id":367916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"9","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Starn, J. Jeffrey 0000-0001-5909-0010 jjstarn@usgs.gov","orcid":"https://orcid.org/0000-0001-5909-0010","contributorId":1916,"corporation":false,"usgs":true,"family":"Starn","given":"J. Jeffrey","email":"jjstarn@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":false,"id":772025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":772026,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70215329,"text":"70215329 - 2019 - Genomic pedigree reconstruction identifies predictors of mating and reproductive success in an invasive vertebrate","interactions":[],"lastModifiedDate":"2020-10-16T14:03:28.428405","indexId":"70215329","displayToPublicDate":"2019-10-02T08:59:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Genomic pedigree reconstruction identifies predictors of mating and reproductive success in an invasive vertebrate","docAbstract":"The persistence of an invasive species is influenced by its reproductive ecology, and a successful control program must operate on this premise. However, the reproductive ecology of invasive species may be enigmatic due to factors that also limit their management, such as cryptic coloration and behavior. We explored the mating and reproductive ecology of the invasive Brown Treesnake (BTS: Boiga irregularis) by reconstructing a multigenerational genomic pedigree based on 654 single nucleotide polymorphisms for a geographically closed population established in 2004 on Guam (N = 426). The pedigree allowed annual estimates of individual mating and reproductive success to be inferred for snakes in the study population over a 14‐year period. We then employed generalized linear mixed models to gauge how well phenotypic and genomic data could predict sex‐specific annual mating and reproductive success. Average snout–vent length (SVL), average body condition index (BCI), and trappability were significantly related to annual mating success for males, with average SVL also related to annual mating success for females. Male and female annual reproductive success was positively affected by SVL, BCI, and trappability. Surprisingly, the degree to which individuals were inbred had no effect on annual mating or reproductive success. When juxtaposed with current control methods, these results indicate that baited traps, a common interdiction tool, may target fecund BTS in some regards but not others. Our study emphasizes the importance of reproductive ecology as a focus for improving BTS control and promotes genomic pedigree reconstruction for such an endeavor in this invasive species and others.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5694","usgsCitation":"Levine, B., Douglas, M.R., Yackel Adams, A.A., Lardner, B., Reed, R., Savidge, J.A., and Douglas, M.E., 2019, Genomic pedigree reconstruction identifies predictors of mating and reproductive success in an invasive vertebrate: Ecology and Evolution, v. 9, no. 20, p. 11863-11877, https://doi.org/10.1002/ece3.5694.","productDescription":"15 p.","startPage":"11863","endPage":"11877","ipdsId":"IP-110981","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":459638,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5694","text":"Publisher Index Page"},{"id":437315,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X1AKVJ","text":"USGS data release","linkHelpText":"Brown Treesnake mating and reproductive success on Guam, 2004-2018"},{"id":379463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 144.86709594726562,\n 13.548212606976776\n ],\n [\n 144.9594497680664,\n 13.548212606976776\n ],\n [\n 144.9594497680664,\n 13.630138790321915\n ],\n [\n 144.86709594726562,\n 13.630138790321915\n ],\n [\n 144.86709594726562,\n 13.548212606976776\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"20","noUsgsAuthors":false,"publicationDate":"2019-10-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Levine, Brenna A","contributorId":243207,"corporation":false,"usgs":false,"family":"Levine","given":"Brenna A","affiliations":[{"id":38022,"text":"University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":801737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, Marlis R","contributorId":243208,"corporation":false,"usgs":false,"family":"Douglas","given":"Marlis","email":"","middleInitial":"R","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":801739,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":801738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lardner, Bjorn","contributorId":225066,"corporation":false,"usgs":false,"family":"Lardner","given":"Bjorn","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":801740,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":801741,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Savidge, Julie A.","contributorId":175196,"corporation":false,"usgs":false,"family":"Savidge","given":"Julie","email":"","middleInitial":"A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":801742,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Douglas, Michael E","contributorId":243209,"corporation":false,"usgs":false,"family":"Douglas","given":"Michael","email":"","middleInitial":"E","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":801743,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70205764,"text":"70205764 - 2019 - In vitro immune function in laboratory-reared age-0 smallmouth bass (Micropterus dolomieu) relative to diet","interactions":[],"lastModifiedDate":"2020-01-03T10:15:03","indexId":"70205764","displayToPublicDate":"2019-10-01T16:55:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1644,"text":"Fish & Shellfish Immunology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"In vitro immune function in laboratory-reared age-0 smallmouth bass (Micropterus dolomieu) relative to diet","title":"In vitro immune function in laboratory-reared age-0 smallmouth bass (Micropterus dolomieu) relative to diet","docAbstract":"Smallmouth bass (Micropterus dolomieu) are used as an indicator species in environmental monitoring and assessment studies. However, laboratory-based studies for methods development and effector assessment are limited for this species. Nutrition, a known modulator of teleost physiological responses including immune function, is a critical knowledge-gap sometimes overlooked in the design of laboratory studies. We report the results from a study evaluating a commercially available artificial pelleted diet for bass and live feed (fathead minnows). Following a six-month diet-acclimation period, age-0 smallmouth bass were assessed using morphometric measures, histologic and immune-function end points using conventional methods, miniaturized cell isolation and assay methods as well as imaging flow cytometry. Fish on the two diets did not significantly differ in length, weight, or condition factor, indicating that growth was similar in the two groups. Histologic examination revealed relatively higher levels of macrophage aggregates and accumulation of ceroid/lipofuscin in the spleen as well as hepatocyte changes in the pellet-fed group. Leukocytes from the pellet-fed group exhibited significantly elevated bactericidal activity and significantly depressed mitogen response compared to fish fed live feed. Following exposure to a known inducer of inflammatory responses, bacterial lipopolysaccharide, responses including the transition of leukocytes to an apoptotic/necrotic condition differed significantly based on diet. Histologic findings were consistent with the occurrence of diet-related oxidative stress in the pellet-fed fish. Oxidative stress can be induced by multiple factors including environmental pollutants. For a diet to be useful in laboratory-based studies, it cannot elicit response that could also be induced by experimental treatments. To do so greatly complicates the detection of experimental effects. Until an artificial diet is developed for smallmouth bass that does not produce potentially confounding conditions for laboratory-based studies, use of a live feed appears to be the best option.
","language":"English","publisher":"Elseiver","doi":"10.1016/j.fsi.2019.10.005","usgsCitation":"Ottinger, C., Smith, C.R., and Blazer, V., 2019, In vitro immune function in laboratory-reared age-0 smallmouth bass (Micropterus dolomieu) relative to diet: Fish & Shellfish Immunology, v. 95, p. 1-10, https://doi.org/10.1016/j.fsi.2019.10.005.","productDescription":"10 p.","startPage":"1","endPage":"10","ipdsId":"IP-109860","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":459644,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fsi.2019.10.005","text":"Publisher Index Page"},{"id":368726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"95","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ottinger, Christopher 0000-0003-2551-1985","orcid":"https://orcid.org/0000-0003-2551-1985","contributorId":205874,"corporation":false,"usgs":true,"family":"Ottinger","given":"Christopher","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":772251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Cheyenne R. 0000-0002-7226-1774","orcid":"https://orcid.org/0000-0002-7226-1774","contributorId":219236,"corporation":false,"usgs":true,"family":"Smith","given":"Cheyenne","email":"","middleInitial":"R.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":772252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":772253,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227809,"text":"70227809 - 2019 - Landscape genetics reveals unique and shared effects of urbanization for two sympatric pool-breeding amphibians","interactions":[],"lastModifiedDate":"2022-02-01T20:31:57.099474","indexId":"70227809","displayToPublicDate":"2019-10-01T15:31:35","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Landscape genetics reveals unique and shared effects of urbanization for two sympatric pool-breeding amphibians","docAbstract":"Metapopulation-structured species can be negatively affected when landscape fragmentation impairs connectivity. We investigated the effects of urbanization on genetic diversity and gene flow for two sympatric amphibian species, spotted salamanders (Ambystoma maculatum) and wood frogs (Lithobates sylvaticus), across a large (>35,000 km2) landscape in Maine, USA, containing numerous natural and anthropogenic gradients. Isolation-by-distance (IBD) patterns differed between the species. Spotted salamanders showed a linear and relatively high variance relationship between genetic and geographic distances (r = .057, p < .001), whereas wood frogs exhibited a strongly nonlinear and lower variance relationship (r = 0.429, p < .001). Scale dependence analysis of IBD found gene flow has its most predictable influence (strongest IBD correlations) at distances up to 9 km for spotted salamanders and up to 6 km for wood frogs. Estimated effective migration surfaces revealed contrasting patterns of high and low genetic diversity and gene flow between the two species. Population isolation, quantified as the mean IBD residuals for each population, was associated with local urbanization and less genetic diversity in both species. The influence of geographic proximity and urbanization on population connectivity was further supported by distance-based redundancy analysis and multiple matrix regression with randomization. Resistance surface modeling found interpopulation connectivity to be influenced by developed land cover, light roads, interstates, and topography for both species, plus secondary roads and rivers for wood frogs. Our results highlight the influence of anthropogenic landscape features within the context of natural features and broad spatial genetic patterns, in turn supporting the premise that while urbanization significantly restricts interpopulation connectivity for wood frogs and spotted salamanders, specific landscape elements have unique effects on these two sympatric species.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5685","usgsCitation":"Homola, J.J., Loftin, C., and Kinnison, M., 2019, Landscape genetics reveals unique and shared effects of urbanization for two sympatric pool-breeding amphibians: Ecology and Evolution, v. 9, no. 20, p. 11799-11823, https://doi.org/10.1002/ece3.5685.","productDescription":"25 p.","startPage":"11799","endPage":"11823","ipdsId":"IP-098892","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":459647,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5685","text":"Publisher Index Page"},{"id":395242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","city":"Bangor, Portland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.57891845703125,\n 43.530629170442424\n ],\n [\n -70.11474609375,\n 43.530629170442424\n ],\n [\n -70.11474609375,\n 43.83650797709095\n ],\n [\n -70.57891845703125,\n 43.83650797709095\n ],\n [\n -70.57891845703125,\n 43.530629170442424\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.994140625,\n 44.67646564865964\n ],\n [\n -68.57666015625,\n 44.67646564865964\n ],\n [\n -68.57666015625,\n 44.953136827528816\n ],\n [\n -68.994140625,\n 44.953136827528816\n ],\n [\n -68.994140625,\n 44.67646564865964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"20","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Homola, Jared J.","contributorId":264547,"corporation":false,"usgs":false,"family":"Homola","given":"Jared","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":832349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Cynthia S. 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":2167,"corporation":false,"usgs":true,"family":"Loftin","given":"Cynthia S.","email":"cyndy_loftin@usgs.gov","affiliations":[],"preferred":true,"id":832348,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinnison, Michael T.","contributorId":264555,"corporation":false,"usgs":false,"family":"Kinnison","given":"Michael T.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":832350,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217792,"text":"70217792 - 2019 - Burial history reconstruction of the Appalachian Basin in Kentucky, West Virginia, Ohio, Pennsylvania, and New York, using 1D petroleum system models","interactions":[],"lastModifiedDate":"2021-02-02T19:47:44.189506","indexId":"70217792","displayToPublicDate":"2019-10-01T14:47:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2789,"text":"Mountain Geologist","active":true,"publicationSubtype":{"id":10}},"title":"Burial history reconstruction of the Appalachian Basin in Kentucky, West Virginia, Ohio, Pennsylvania, and New York, using 1D petroleum system models","docAbstract":"Nine 1D burial history models were built across the Appalachian Basin to reconstruct the burial, erosional, and thermal maturation histories of contained petroleum source rocks. Models were calibrated to measured downhole temperature and to vitrinite reflectance (% Ro) data from Devonian through Pennsylvanian petroleum source rocks. The highest levels of thermal maturity in Devonian and Mississippian source rocks are within and proximal to the Rome trough in the deep basin, which is also within the confluence of increased structural complexity and associated faulting, overpressured Devonian shales, and thick intervals of salt in the underlying Silurian Salina Group.
Models incorporate minor erosion from 260 to 140 million years ago (Ma) that allows for extended burial and heating of underlying strata and generally results in less eroded thickness, compared to previously published models. Two modeled times of increased erosion, from 140 to 90 Ma and 23 to 5.3 Ma, are followed by less erosion from 5.3 Ma to Present. Absent strata are mainly Permian shales and sandstone; thickness of these removed layers increased from about 6,200 ft (1,890 m) west of the Rome trough to as much as 9,650 ft (2,940 m) within the trough. The onset of oil generation is based on 0.6% Ro for Pennsylvanian coal samples; time of onset for the Ordovician Utica Shale ranges from 387 to 306 Ma, and 359 to 282 Ma for Middle Devonian to basal Mississippian shales. The ∼1.2% Ro onset of wet gas generation ranges from 360 to 281 Ma in the Utica Shale, and 298 to 150 Ma for Middle Devonian to lowermost Mississippian shales.
","language":"English","publisher":"The Rocky Mountain Association of Geologists","doi":"10.31582/rmag.mg.56.4.365","usgsCitation":"Higley, D.K., and Enomoto, C.B., 2019, Burial history reconstruction of the Appalachian Basin in Kentucky, West Virginia, Ohio, Pennsylvania, and New York, using 1D petroleum system models: Mountain Geologist, v. 56, no. 4, p. 365-396, https://doi.org/10.31582/rmag.mg.56.4.365.","productDescription":"32 p.","startPage":"365","endPage":"396","ipdsId":"IP-098203","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":382896,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky, New York, Ohio, Pennsylvania, West 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\"}}]}","volume":"56","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Higley, Debra K. 0000-0001-8024-9954 higley@usgs.gov","orcid":"https://orcid.org/0000-0001-8024-9954","contributorId":152663,"corporation":false,"usgs":true,"family":"Higley","given":"Debra","email":"higley@usgs.gov","middleInitial":"K.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":809726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Enomoto, Catherine B. 0000-0002-4119-1953 cenomoto@usgs.gov","orcid":"https://orcid.org/0000-0002-4119-1953","contributorId":2126,"corporation":false,"usgs":true,"family":"Enomoto","given":"Catherine","email":"cenomoto@usgs.gov","middleInitial":"B.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":809727,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70209090,"text":"70209090 - 2019 - Spatial fingerprinting of biogenic and anthropogenic volatile organic compounds in an arid unsaturated zone","interactions":[],"lastModifiedDate":"2020-03-16T06:20:18","indexId":"70209090","displayToPublicDate":"2019-10-01T13:42:44","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Spatial fingerprinting of biogenic and anthropogenic volatile organic compounds in an arid unsaturated zone","docAbstract":"Subsurface volatile organic compounds (VOCs) can pose risks to human and environmental health and mediate biological processes. VOCs have both anthropogenic and biogenic origins, but the relative importance of these sources has not been explored in subsurface environments. This study synthesizes 17 years of VOC data from the Amargosa Desert Research Site (ADRS) with the goal of improving understanding of spatial and temporal variations that distinguish sources of VOCs from a landfill and surrounding ambient sources including biogenic VOCs (bVOCs). Gas samples were collected from 1999 to 2016 from an array of shallow sample points (0.5 m and 1.5 m depth) and from vertical profiles at three deep boreholes, two (109 m deep) near the border of a waste facility (33 and 100 m distant), and one (29 m deep) in a remote area 3 km to the south. Samples were analyzed for target VOCs and a subset was analyzed for non-target VOCs to enumerate a greater variety of potential bVOCs. Principal components analysis of the target and non-target VOCs provided an assessment of spatial variability of VOCs originating from the landfill site and from ambient sources. Ambient VOCs occurred at all sample sites over a range of depths and most were consistent with biogenic origins, indicating, for the first time, presence of bVOCs in the deep unsaturated zone. Because some VOCs have both anthropogenic and biogenic sources, discrimination of sources can be important for estimating the extent and migration of anthropogenic plumes in arid unsaturated zones.","language":"English","publisher":"Wiley","doi":"10.2136/vzj2019.05.0047","usgsCitation":"Green, C., Luo, W., Conaway, C., Haase, K., Baker, R., and Andraski, B.J., 2019, Spatial fingerprinting of biogenic and anthropogenic volatile organic compounds in an arid unsaturated zone: Vadose Zone Journal, v. 18, no. 1, 190047, https://doi.org/10.2136/vzj2019.05.0047.","productDescription":"190047","ipdsId":"IP-106246","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":459654,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2136/vzj2019.05.0047","text":"Publisher Index Page"},{"id":373272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","county":"Nye County","otherGeospatial":"Amargosa Desert Research Site","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-115.9082,39.1615],[-115.5191,38.9578],[-115.4725,38.9325],[-115.4433,38.9162],[-115.3694,38.8769],[-115.363,38.874],[-115.242,38.8093],[-115.0969,38.7309],[-115.0777,38.721],[-115.0604,38.7107],[-115.0291,38.6937],[-114.999,38.6777],[-114.9996,38.592],[-114.9997,38.4315],[-114.9994,38.3894],[-115.0004,38.0507],[-115.1185,38.0508],[-115.1436,38.0508],[-115.326,38.0515],[-115.3453,38.0514],[-115.4003,38.051],[-115.4587,38.0506],[-115.6394,38.0512],[-115.6581,38.051],[-115.8404,38.0504],[-115.8931,38.0507],[-115.8938,37.723],[-115.8969,37.5498],[-115.8975,37.2796],[-115.8982,37.1926],[-115.8942,36.8425],[-115.8941,36.686],[-115.8945,36.6702],[-115.8949,36.598],[-115.8949,36.5962],[-115.8946,36.5858],[-115.8947,36.5005],[-115.8945,36.4806],[-115.8949,36.462],[-115.8944,36.457],[-115.8948,36.3087],[-115.8945,36.2923],[-115.8943,36.1957],[-115.8945,36.1608],[-115.8948,36.1163],[-115.8948,36.0927],[-115.895,36.0015],[-115.9178,36.0192],[-115.9518,36.0457],[-115.9925,36.0773],[-116.049,36.1211],[-116.0624,36.1314],[-116.1039,36.1636],[-116.1287,36.1829],[-116.1702,36.2152],[-116.173,36.2174],[-116.2311,36.2626],[-116.2834,36.3028],[-116.2954,36.3122],[-116.3752,36.373],[-116.5107,36.4764],[-116.5247,36.4871],[-116.5589,36.5131],[-116.574,36.5245],[-116.5946,36.54],[-116.6556,36.5867],[-116.6583,36.5888],[-116.6764,36.6024],[-116.706,36.6248],[-116.7895,36.6877],[-116.8424,36.7276],[-116.8453,36.7298],[-116.8806,36.7568],[-116.8912,36.7648],[-116.9237,36.7891],[-116.9641,36.8193],[-116.9783,36.8299],[-116.981,36.8319],[-117.0046,36.8495],[-117.164,36.9688],[-117.1639,36.9698],[-117.1637,37.0182],[-117.164,37.0894],[-117.1642,37.171],[-117.1641,37.1909],[-117.1641,37.1936],[-117.1665,37.6995],[-117.1664,37.714],[-117.1663,37.7285],[-117.1663,37.7435],[-117.1662,37.7585],[-117.1657,38.0019],[-117.2198,38.0482],[-117.2397,38.0483],[-117.239,38.0641],[-117.2408,38.0705],[-117.2653,38.0932],[-117.6896,38.4731],[-118.0197,38.7599],[-118.197,38.9154],[-118.1972,38.9993],[-117.8559,39.0746],[-117.7748,39.092],[-117.7008,39.1058],[-117.6409,39.1149],[-117.5946,39.1231],[-117.4742,39.1431],[-117.3823,39.1562],[-117.3609,39.1585],[-117.3318,39.1629],[-117.3063,39.1634],[-117.2849,39.1633],[-117.1995,39.1632],[-117.0856,39.1628],[-117.0322,39.1626],[-117.0144,39.1626],[-116.9871,39.1625],[-116.9158,39.1631],[-116.7562,39.1622],[-116.7301,39.1625],[-116.5996,39.1616],[-116.5859,39.162],[-116.4815,39.1616],[-116.3497,39.1618],[-116.2358,39.1616],[-116.0548,39.1624],[-115.9082,39.1615]]]},\"properties\":{\"name\":\"Nye\",\"state\":\"NV\"}}]}","volume":"18","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Green, Christopher 0000-0002-6480-8194","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":201642,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":784891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luo, Wentai 0000-0003-3421-4958","orcid":"https://orcid.org/0000-0003-3421-4958","contributorId":222128,"corporation":false,"usgs":false,"family":"Luo","given":"Wentai","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":784892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conaway, Christopher H. 0000-0002-0991-033X","orcid":"https://orcid.org/0000-0002-0991-033X","contributorId":201932,"corporation":false,"usgs":true,"family":"Conaway","given":"Christopher H.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":784893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haase, Karl B. 0000-0002-6897-6494","orcid":"https://orcid.org/0000-0002-6897-6494","contributorId":216317,"corporation":false,"usgs":true,"family":"Haase","given":"Karl B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":784894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baker, Ronald J. 0000-0001-5966-554X","orcid":"https://orcid.org/0000-0001-5966-554X","contributorId":223375,"corporation":false,"usgs":false,"family":"Baker","given":"Ronald J.","affiliations":[{"id":36625,"text":"Emeritus","active":true,"usgs":false}],"preferred":false,"id":784895,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Andraski, Brian J. 0000-0002-2086-0417 andraski@usgs.gov","orcid":"https://orcid.org/0000-0002-2086-0417","contributorId":168800,"corporation":false,"usgs":true,"family":"Andraski","given":"Brian","email":"andraski@usgs.gov","middleInitial":"J.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":false,"id":784896,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70205890,"text":"70205890 - 2019 - Wetland biomass and productivity in Coastal Louisiana: Base line data (1976-2015) and knowledge gaps for the development of spatially explicit models for ecosystem restoration and rehabilitation initiatives","interactions":[],"lastModifiedDate":"2019-10-10T08:13:33","indexId":"70205890","displayToPublicDate":"2019-10-01T13:21:54","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Wetland biomass and productivity in Coastal Louisiana: Base line data (1976-2015) and knowledge gaps for the development of spatially explicit models for ecosystem restoration and rehabilitation initiatives","docAbstract":"Coastal Louisiana host 37% of the coastal wetland area in the conterminous US, including one of the deltaic coastal regions more susceptible to the synergy of human and natural impacts causing wetland loss. As a result of the construction of flood protection infrastructure, dredging of channels across wetlands for oil/gas exploration and maritime transport activities, coastal Coastal Louisiana hosts 37% of the coastal wetland area in the conterminous US, including one of the deltaic coastal regions more susceptible to the synergy of human and natural impacts causing wetland loss. As a result of the construction of flood protection infrastructure, dredging of channels across wetlands for oil/gas exploration and maritime transport activities, coastal Louisiana has lost approximately 4900 km2 of wetland area since the early 1930s. Despite the economic relevance of both wetland biomass and net primary productivity (NPP) as ecosystem services, there is a lack of vegetation simulation models to forecast the trends of those functional attributes at the landscape level as hydrological restoration projects are implemented. Here, we review the availability of peer-reviewed biomass and NPP wetland data (below and aboveground) published during the period 1976–2015 for use in the development, calibration and validation of high spatial resolution (<200 m × 200 m) vegetation process-based ecological models. We discuss and list the knowledge gaps for those species that represent vegetation community associations of ecological importance, including the long-term research issues associated to limited number of paired belowground biomass and productivity studies across hydrological basins currently undergoing different freshwater diversions management regimes and hydrological restoration priorities.","language":"English","publisher":"MDPI","doi":"10.3390/w11102054","usgsCitation":"Rivera-Monroy, V.H., Elliton, C., Narra, S., Meselhe, E., Zhao, X., White, E., Sasser, C.E., Visser, J.M., Meng, X., Wang, H., Xue, Z., and Jaramillo, F., 2019, Wetland biomass and productivity in Coastal Louisiana: Base line data (1976-2015) and knowledge gaps for the development of spatially explicit models for ecosystem restoration and rehabilitation initiatives: Water, v. 11, no. 10, 2054, https://doi.org/10.3390/w11102054.","productDescription":"2054","ipdsId":"IP-108198","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":459655,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w11102054","text":"Publisher Index Page"},{"id":368202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.8671875,\n 30.278044377800153\n ],\n [\n -94.02099609375,\n 29.57345707301757\n ],\n [\n -88.61572265625,\n 28.65203063036226\n ],\n [\n -87.62695312499999,\n 29.458731185355344\n ],\n [\n -88.92333984375,\n 30.259067203213018\n ],\n [\n -89.71435546875,\n 30.29701788337205\n ],\n [\n 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University","active":true,"usgs":false}],"preferred":false,"id":772885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Narra, Siddhartha","contributorId":219695,"corporation":false,"usgs":false,"family":"Narra","given":"Siddhartha","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":772886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meselhe, Ehab","contributorId":95333,"corporation":false,"usgs":true,"family":"Meselhe","given":"Ehab","email":"","affiliations":[],"preferred":false,"id":772887,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhao, Xiaochen","contributorId":219696,"corporation":false,"usgs":false,"family":"Zhao","given":"Xiaochen","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":772888,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"White, Eric","contributorId":194507,"corporation":false,"usgs":false,"family":"White","given":"Eric","affiliations":[],"preferred":false,"id":772889,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sasser, Charles E.","contributorId":86858,"corporation":false,"usgs":true,"family":"Sasser","given":"Charles","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":772890,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Visser, Jenneke M.","contributorId":90397,"corporation":false,"usgs":true,"family":"Visser","given":"Jenneke","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":772891,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Meng, X.","contributorId":56962,"corporation":false,"usgs":true,"family":"Meng","given":"X.","email":"","affiliations":[],"preferred":false,"id":772892,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":140432,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":772893,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Xue, Zuo","contributorId":47216,"corporation":false,"usgs":true,"family":"Xue","given":"Zuo","affiliations":[],"preferred":false,"id":772894,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jaramillo, Fernando","contributorId":219697,"corporation":false,"usgs":false,"family":"Jaramillo","given":"Fernando","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":772895,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70206767,"text":"70206767 - 2019 - Seasonal, spring-neap, and tidal variation in cohesive sediment transport parameters in estuarine shallows","interactions":[],"lastModifiedDate":"2020-01-03T10:44:49","indexId":"70206767","displayToPublicDate":"2019-10-01T10:55:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2321,"text":"Journal of Geophysical Research: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal, spring-neap, and tidal variation in cohesive sediment transport parameters in estuarine shallows","docAbstract":"Numerical models for predicting sediment concentrations and transport rely on parameters such as settling velocity and bed erodibility that describe sediment characteristics, yet these parameters are rarely probed directly. We investigated temporal and spatial variation in sediment parameters in the shallows of San Pablo Bay, CA. Flow, turbulence, and suspended sediment data were measured at sites located at 1 and 2 m below mean lower low water (MLLW) from November 2013 through April 2015, supplemented by monthlong periods in 2011, 2012, and 2016. Maximum current velocities were 0.40–0.47 m s-1 at these depths; the strongest currents decreased to 0.27–0.34 m s-1 during neap periods. Winters 2013–2014 and 2014–2015 experienced strong drought conditions, limiting the potential for seasonal impact on sediment conditions during this experiment. Despite this, the more storm‐influenced site showed clear changes during the winter: the roughness parameter decreased from 10−4 to 10−5 m, from hydrodynamically rough to smooth conditions, and bed erodibility increased by an order of magnitude. Median settling velocity was 2.05·10−4 m s-1; it varied twofold within a tidal cycle, decreasing as current velocity grew during flood and ebb. This tidal control on floc size affected settling velocity on the spring‐neap timescale, possibly driving a spring‐neap oscillation in erodibility. Our findings highlight variation in sediment dynamics that is commonly ignored in numerical models and the need for field observations to ground truth ongoing modeling efforts.
","language":"English","publisher":"Wiley","doi":"10.1029/2018JC014825","usgsCitation":"Allen, R., Lacy, J.R., Stacey, M.T., and Variano, E.A., 2019, Seasonal, spring-neap, and tidal variation in cohesive sediment transport parameters in estuarine shallows: Journal of Geophysical Research: Oceans, v. 124, no. 11, p. 7265-7284, https://doi.org/10.1029/2018JC014825.","productDescription":"20 p.","startPage":"7265","endPage":"7284","ipdsId":"IP-103807","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":369464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Pablo Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.57858276367186,\n 37.95827503526034\n ],\n [\n -122.23251342773438,\n 37.95827503526034\n ],\n [\n -122.23251342773438,\n 38.16479533621134\n ],\n [\n -122.57858276367186,\n 38.16479533621134\n ],\n [\n -122.57858276367186,\n 37.95827503526034\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Rachel 0000-0002-0287-6466","orcid":"https://orcid.org/0000-0002-0287-6466","contributorId":216002,"corporation":false,"usgs":true,"family":"Allen","given":"Rachel","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":775714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":775715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stacey, Mark T. 0000-0002-0952-2812","orcid":"https://orcid.org/0000-0002-0952-2812","contributorId":220770,"corporation":false,"usgs":false,"family":"Stacey","given":"Mark","email":"","middleInitial":"T.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":775716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Variano, Evan A 0000-0001-5102-238X","orcid":"https://orcid.org/0000-0001-5102-238X","contributorId":216003,"corporation":false,"usgs":false,"family":"Variano","given":"Evan","email":"","middleInitial":"A","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":775717,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70259333,"text":"70259333 - 2019 - Monitoring, forecasting collapse events, and mapping pyroclastic deposits at Sinabung volcano with satellite imagery","interactions":[],"lastModifiedDate":"2024-10-04T13:56:02.834055","indexId":"70259333","displayToPublicDate":"2019-10-01T08:47:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring, forecasting collapse events, and mapping pyroclastic deposits at Sinabung volcano with satellite imagery","docAbstract":"During the ongoing (2013–present) eruption of Sinabung volcano, north Sumatra, we have routinely used a variety of satellite remote sensing data to observe and forecast lava dome and lava flow collapse events, to map the resulting pyroclastic deposits, and to estimate effusion rates. In this paper, we focus on the first two years of the current eruption (September 2013–December 2015), and we summarize major events in 2016. We divide the eruption into 5 major phases: 1) phreatomagmatic (July 2013–18 December 2013), 2) first dome growth and collapse (18 December 2013–10 January 2014), 3) lava-flow (10 January 2014–mid-September 2014), 4) second lava dome and collapse (mid-September 2014–July 2015), 5) lava dome collapse and ash explosion phase (August 2015–present). Throughout the eruption, remotely sensed information has been instrumental in assessing the stability of the lava dome and flow and to forecast collapse events that produce pyroclastic density currents (PDCs: block-and-ash flows, co-ignimbrite surges, and blasts). Forecasts based on remote sensing data in combination with seismic, geodetic and gas-monitoring data have also helped inform decisions related to alert levels and evacuations. Relatively unusual aspects of the Sinabung eruption include the transition from dome to flow morphology (phase 2 to phase 3 transition) and the frequent occurrence during phase 3 of collapses from the lava flow-front and flow-margins—collapses that produced extensive pyroclastic density currents. By analogy to the well-known “Merapi type” collapses and pyroclastic deposits, we propose that lava flow-front and flow-margin collapses with associated PDCs be known as “Sinabung type.” Although detailed study of deposits has not been possible due to continuing hazards, our observations suggest that the transition from lava dome to lava flow and the occurrence of flow-front and flow-margin collapses reflect a particular combination of lava viscosity and steepness of slope. Our observations also show clear evidence of at least one slope-parallel high-velocity and dilute PDC (a “blast”) that emanated from a lava-margin collapse site 500 m downslope from the vent. This 1 February 2014 blast downed and singed a forest out to at least 3.9 km from the collapse site and killed 16 people. We also use a combination of field and remotely sensed data to map the distribution of Sinabung deposits. We estimate eruptive volumes and extrusion rates by combining sequential measurements of lava surface and pyroclastic flow areas with thickness estimates derived from simple geometric assumptions, oblique photographs and Digital Elevation Models (DEMs) derived from remotely sensed data. Our estimates of short-term effusion rates vary widely on a daily to weekly basis, from <1 to >20 m3 s−1. In a few cases, periods of increased extrusion precede lava flow-front collapses by a few days to a week, suggesting delays in transmittance of effusion pulses as lava moves from vent to flow front. We find that, as of 1 January 2016, the total area of deposits is 107 m2, and their approximate deposit volume is about 0.3 km3, equivalent to 0.2 km3 Dense Rock Equivalent (DRE). We anticipate that our deposit maps will be valuable in the future as a framework for the study of the magmatic and textural evolution of eruptive products through time.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2018.05.012","usgsCitation":"Pallister, J.S., Wessels, R., Griswold, J.P., McCausland, W.A., Kartadinata, N., Gunawan, H., Budianto, A., and Primulyana, S., 2019, Monitoring, forecasting collapse events, and mapping pyroclastic deposits at Sinabung volcano with satellite imagery: Journal of Volcanology and Geothermal Research, v. 382, p. 149-163, https://doi.org/10.1016/j.jvolgeores.2018.05.012.","productDescription":"15 p.","startPage":"149","endPage":"163","ipdsId":"IP-077545","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467319,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2018.05.012","text":"Publisher Index Page"},{"id":462593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Sinabung volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 97.99743834932508,\n 3.449644799978927\n ],\n [\n 97.99743834932508,\n 2.1401582830417425\n ],\n [\n 99.24416582769311,\n 2.1401582830417425\n ],\n [\n 99.24416582769311,\n 3.449644799978927\n ],\n [\n 97.99743834932508,\n 3.449644799978927\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"382","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pallister, John S. 0000-0002-2041-2147 jpallist@usgs.gov","orcid":"https://orcid.org/0000-0002-2041-2147","contributorId":2024,"corporation":false,"usgs":true,"family":"Pallister","given":"John","email":"jpallist@usgs.gov","middleInitial":"S.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":914964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wessels, Rick 0000-0001-9711-6402 rwessels@usgs.gov","orcid":"https://orcid.org/0000-0001-9711-6402","contributorId":198602,"corporation":false,"usgs":true,"family":"Wessels","given":"Rick","email":"rwessels@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":914965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Griswold, Julia P. 0000-0001-5597-5030 griswold@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-5030","contributorId":202823,"corporation":false,"usgs":true,"family":"Griswold","given":"Julia","email":"griswold@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":914966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCausland, Wendy A. 0000-0002-8683-1440","orcid":"https://orcid.org/0000-0002-8683-1440","contributorId":204380,"corporation":false,"usgs":true,"family":"McCausland","given":"Wendy","email":"","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":914967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kartadinata, Nugraha","contributorId":344903,"corporation":false,"usgs":false,"family":"Kartadinata","given":"Nugraha","email":"","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":914968,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gunawan, Hendra","contributorId":344904,"corporation":false,"usgs":false,"family":"Gunawan","given":"Hendra","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":914969,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Budianto, Agus","contributorId":344905,"corporation":false,"usgs":false,"family":"Budianto","given":"Agus","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":914970,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Primulyana, Sofyan","contributorId":344906,"corporation":false,"usgs":false,"family":"Primulyana","given":"Sofyan","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":914971,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70206800,"text":"70206800 - 2019 - Formation pressure and fluid flow measurements in marine gas hydrate reservoirs, NGHP-02 expedition, offshore India","interactions":[],"lastModifiedDate":"2019-11-22T08:28:35","indexId":"70206800","displayToPublicDate":"2019-10-01T08:26:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2382,"text":"Journal of Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Formation pressure and fluid flow measurements in marine gas hydrate reservoirs, NGHP-02 expedition, offshore India","docAbstract":"Open Hole Modular Dynamic Testing (MDT) measurements were conducted in a gas hydrate-bearing sand-rich reservoir offshore India during the National Gas Hydrate Program 02 (NGHP-02) Expedition. The primary goal of this test was to obtain effective reservoir petrophysical properties in the presence of gas hydrates. The test plan included a series of pre-hydrate dissociation flow and build-up (shut-in) tests, and an attempt to dissociate gas hydrate in a sand-rich reservoir by depressurization to collect formation fluid samples and to further characterize in situ gas hydrate stability conditions. Schlumberger’s wireline MDT tool was used in a dual-packer configuration to isolate the formation being tested.\n\nThis paper presents the results of the open hole MDT measurements that were conducted in Hole NGHP-02-23-C in Krishna-Godavari Basin at a water depth of 2553.5 m. The MDT dual packer test was conducted in 27 cm (10.63 in) diameter open hole section of the borehole within a 1-m interval isolated between two inflatable packers with the midpoint of the test interval at 2853.0 meter below rig floor (mbrf) (271.0 meter below sea floor (mbsf)). This was the first gas hydrate MDT test ever conducted in ultradeep water to characterize a gas hydrate reservoir system. Pre-hydrate dissociation testing was performed with a drawdown period (depressurization) of 20 minutes followed by a build-up (shut-in) of 20 minutes. The measured formation pressure was 4090.7 psia and the formation fluid (i.e., water) mobility was calculated at 1.98 mD/cP. During the second dissociation phase of the same test a maximum pressure drawdown of 840 psia was achieved; however, falling short of the 1120 psia drawdown required for dissociation. During the dissociation test the flow line pressure stabilized at a flowing pressure of 3250 psia which can be attributed to the relatively high mobility of the free water phase in the hydrate-bearing reservoir. Good quality formation pressure and near well bore mobility data was acquired that yielded a “high confidence” reservoir effective radial permeability-thickness product of 0.2 mD.m (or a horizontal effective permeability of 0.1 mD assuming a reservoir thicknees of 1.8 m) using pressure transient analysis (radial flow regime was achieved) despite unstable borehole conditions and complex operations in these shallow unconsolidated sedimentary sections.","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.11.035","usgsCitation":"Kumar, P., Collett, T.S., Yadav, U., and Singh, J., 2019, Formation pressure and fluid flow measurements in marine gas hydrate reservoirs, NGHP-02 expedition, offshore India: Journal of Marine and Petroleum Geology, v. 108, p. 609-618, https://doi.org/10.1016/j.marpetgeo.2018.11.035.","productDescription":"10 p.","startPage":"609","endPage":"618","ipdsId":"IP-103515","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":459669,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1636237","text":"Publisher Index Page"},{"id":369450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[77.83745,35.49401],[78.91227,34.32194],[78.81109,33.5062],[79.20889,32.99439],[79.17613,32.48378],[78.45845,32.61816],[78.73889,31.51591],[79.72137,30.88271],[81.11126,30.18348],[80.47672,29.72987],[80.08842,28.79447],[81.0572,28.4161],[81.99999,27.92548],[83.30425,27.36451],[84.67502,27.2349],[85.25178,26.7262],[86.02439,26.63098],[87.22747,26.3979],[88.06024,26.41462],[88.1748,26.81041],[88.04313,27.44582],[88.12044,27.87654],[88.73033,28.08686],[88.81425,27.29932],[88.83564,27.09897],[89.74453,26.7194],[90.37327,26.87572],[91.21751,26.80865],[92.03348,26.83831],[92.10371,27.45261],[91.69666,27.77174],[92.50312,27.89688],[93.41335,28.64063],[94.56599,29.27744],[95.4048,29.03172],[96.11768,29.4528],[96.58659,28.83098],[96.24883,28.41103],[97.32711,28.26158],[97.40256,27.88254],[97.05199,27.69906],[97.134,27.08377],[96.41937,27.26459],[95.12477,26.57357],[95.15515,26.00131],[94.60325,25.1625],[94.55266,24.67524],[94.10674,23.85074],[93.32519,24.07856],[93.28633,23.04366],[93.06029,22.70311],[93.16613,22.27846],[92.67272,22.04124],[92.14603,23.6275],[91.86993,23.62435],[91.70648,22.98526],[91.15896,23.50353],[91.46773,24.07264],[91.91509,24.13041],[92.3762,24.97669],[91.7996,25.14743],[90.87221,25.1326],[89.92069,25.26975],[89.83248,25.96508],[89.35509,26.01441],[88.56305,26.44653],[88.20979,25.76807],[88.93155,25.23869],[88.30637,24.86608],[88.08442,24.50166],[88.69994,24.23371],[88.52977,23.63114],[88.87631,22.87915],[89.03196,22.05571],[88.88877,21.69059],[88.2085,21.70317],[86.9757,21.49556],[87.03317,20.74331],[86.49935,20.15164],[85.06027,19.47858],[83.94101,18.30201],[83.18922,17.67122],[82.19279,17.01664],[82.19124,16.55666],[81.69272,16.31022],[80.792,15.95197],[80.3249,15.89918],[80.02507,15.13641],[80.23327,13.83577],[80.28629,13.00626],[79.86255,12.05622],[79.858,10.35728],[79.34051,10.30885],[78.88535,9.54614],[79.18972,9.21654],[78.27794,8.93305],[77.94117,8.25296],[77.5399,7.96553],[76.59298,8.89928],[76.13006,10.29963],[75.74647,11.30825],[75.3961,11.78125],[74.86482,12.74194],[74.61672,13.99258],[74.44386,14.61722],[73.5342,15.99065],[73.11991,17.92857],[72.82091,19.20823],[72.82448,20.4195],[72.63053,21.35601],[71.17527,20.75744],[70.47046,20.87733],[69.16413,22.0893],[69.64493,22.45077],[69.3496,22.84318],[68.17665,23.69197],[68.8426,24.35913],[71.04324,24.35652],[70.8447,25.2151],[70.28287,25.72223],[70.16893,26.49187],[69.51439,26.94097],[70.6165,27.9892],[71.77767,27.91318],[72.82375,28.96159],[73.45064,29.97641],[74.42138,30.97981],[74.40593,31.69264],[75.25864,32.27111],[74.45156,32.7649],[74.10429,33.44147],[73.74995,34.3177],[74.2402,34.74889],[75.75706,34.50492],[76.87172,34.65354],[77.83745,35.49401]]]},\"properties\":{\"name\":\"India\"}}]}","volume":"108","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kumar, Pushpendra","contributorId":212239,"corporation":false,"usgs":false,"family":"Kumar","given":"Pushpendra","affiliations":[{"id":38465,"text":"Oil and Natural Gas Corp. Panvel, Navi Mumbai, India","active":true,"usgs":false}],"preferred":false,"id":775823,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":775824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yadav, U.S.","contributorId":127763,"corporation":false,"usgs":false,"family":"Yadav","given":"U.S.","email":"","affiliations":[{"id":7141,"text":"Oil and Natural Gas Corporation Ltd, KDM Institute of Petroleum Exploration, India","active":true,"usgs":false}],"preferred":false,"id":775825,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singh, Juli","contributorId":220817,"corporation":false,"usgs":false,"family":"Singh","given":"Juli","email":"","affiliations":[],"preferred":false,"id":775826,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70206802,"text":"70206802 - 2019 - India National Gas Hydrate Program Expedition-02: Operational and technical summary","interactions":[],"lastModifiedDate":"2019-11-22T08:25:02","indexId":"70206802","displayToPublicDate":"2019-10-01T08:23:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2382,"text":"Journal of Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"India National Gas Hydrate Program Expedition-02: Operational and technical summary","docAbstract":"The India National Gas Hydrate Program is being steered by the government of India's Ministry of Petroleum and Natural Gas (MoPNG) with participation of Directorate General of Hydrocarbons (DGH), Oil and Natural Gas Corporation Limited (ONGC), and the National Oil Companies and Research Institutes of India. The India National Gas Hydrate Program Expedition 01 (NGHP-01) established the presence of gas hydrate in the Krishna Godavari (KG) and Mahanadi Basins and in the offshore area of the Andaman Sea Basin. However, the gas hydrates discovered during NGHP-01 were mainly distributed as fracture-filling material in fine-grained clay-rich sediments. The India National Gas Hydrate Program Expedition 02 (NGHP-02) was carried out with an objective to discover gas hydrate in sand-rich sediment along the eastern offshore margin of India. ONGC planned and executed NGHP-02 on the behalf of the MoPNG.\n\nNGHP-02 started on March 3, 2015 and was completed on July 28, 2015 (total 147 days) using the Japanese scientific Drilling Vessel Chikyu (D/V Chikyu). During NGHP-02, 42 holes at 25 sites were drilled, cored, and/or surveyed with downhole logging tools. These sites were located in four areas along the eastern margin of India and formally named Area A (Mahanadi Basin, three sites), Area B (northern part of the KG-Basin, twelve sites), Area C (central part of the KG-Basin, six sites), and Area E (southern part to the KG-Basin, four sites). All 25 sites established during NGHP-02 were first drilled and logged with logging-while-drilling (LWD) tools and an additional 17 holes were then drilled and/or cored with conventional coring tools (HPCS/ESCS) or pressure coring tools (PCTB). Wireline logging was conducted in 10 holes and formation tests using a dual packer Modular Formation Dynamics Tester (MDT) tool were carried out in two holes.\n\nThe onboard science team used the laboratory facilities on the D/V Chikyu to examine and analyse the physical properties, geochemistry, and sedimentology of all the cores collected during the expedition. Core samples were also analysed in additional post-expedition shore-based studies conducted in numerous domestic and international gas hydrate research laboratories. The NGHP-02 sediment cores were archived at the National Gas Hydrate Core Repository in Mumbai (India), which is associated with the ONGC Gas Hydrate Research and Technology Centre (GHRTC). The necessary data for characterizing the occurrence of gas hydrate, such as interstitial water chlorinities, core-derived gas chemistry, physical and sedimentological properties, thermal images of the recovered cores, pressure core and downhole measured logging data (LWD and/or conventional wireline log data), were obtained from most of the drill sites established during NGHP-02. Almost all the drill sites yielded evidence for the occurrence of gas hydrate; however, the inferred in situ concentration of gas hydrate varied substantially from site to site. For the most part, the interpretation of downhole logging data, core thermal images, interstitial water analyses, and pressure core images from the sites established during NGHP-02 indicate that the occurrence of concentrated gas hydrate is mostly associated with coarser grained (sand-rich) sediments. This paper presents the operational and technical summary of NGHP-02.\n\nNGHP-02 started on March 3, 2015 and was completed on July 28, 2015 (total 147 days) using the Japanese scientific Drilling Vessel Chikyu (D/V Chikyu). During NGHP-02, 42 holes at 25 sites were drilled, cored, and/or surveyed with downhole logging tools. These sites were located in four areas along the eastern margin of India and formally named Area A (Mahanadi Basin, three sites), Area B (northern part of the KG-Basin, twelve sites), Area C (central part of the KG-Basin, six sites), and Area E (southern part to the KG-Basin, four sites). All 25 sites established during NGHP-02 were first drilled and logged with logging-while-drilling (LWD) to","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.11.021","usgsCitation":"Kumar, P., Collett, T.S., K. M. Shukla, Yadav, U.S., Lall, M.V., and Krishna Vishwanath, 2019, India National Gas Hydrate Program Expedition-02: Operational and technical summary: Journal of Marine and Petroleum Geology, v. 108, p. 3-38, https://doi.org/10.1016/j.marpetgeo.2018.11.021.","productDescription":"36 p.","startPage":"3","endPage":"38","ipdsId":"IP-103513","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":459672,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1636323","text":"Publisher Index Page"},{"id":369449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[77.83745,35.49401],[78.91227,34.32194],[78.81109,33.5062],[79.20889,32.99439],[79.17613,32.48378],[78.45845,32.61816],[78.73889,31.51591],[79.72137,30.88271],[81.11126,30.18348],[80.47672,29.72987],[80.08842,28.79447],[81.0572,28.4161],[81.99999,27.92548],[83.30425,27.36451],[84.67502,27.2349],[85.25178,26.7262],[86.02439,26.63098],[87.22747,26.3979],[88.06024,26.41462],[88.1748,26.81041],[88.04313,27.44582],[88.12044,27.87654],[88.73033,28.08686],[88.81425,27.29932],[88.83564,27.09897],[89.74453,26.7194],[90.37327,26.87572],[91.21751,26.80865],[92.03348,26.83831],[92.10371,27.45261],[91.69666,27.77174],[92.50312,27.89688],[93.41335,28.64063],[94.56599,29.27744],[95.4048,29.03172],[96.11768,29.4528],[96.58659,28.83098],[96.24883,28.41103],[97.32711,28.26158],[97.40256,27.88254],[97.05199,27.69906],[97.134,27.08377],[96.41937,27.26459],[95.12477,26.57357],[95.15515,26.00131],[94.60325,25.1625],[94.55266,24.67524],[94.10674,23.85074],[93.32519,24.07856],[93.28633,23.04366],[93.06029,22.70311],[93.16613,22.27846],[92.67272,22.04124],[92.14603,23.6275],[91.86993,23.62435],[91.70648,22.98526],[91.15896,23.50353],[91.46773,24.07264],[91.91509,24.13041],[92.3762,24.97669],[91.7996,25.14743],[90.87221,25.1326],[89.92069,25.26975],[89.83248,25.96508],[89.35509,26.01441],[88.56305,26.44653],[88.20979,25.76807],[88.93155,25.23869],[88.30637,24.86608],[88.08442,24.50166],[88.69994,24.23371],[88.52977,23.63114],[88.87631,22.87915],[89.03196,22.05571],[88.88877,21.69059],[88.2085,21.70317],[86.9757,21.49556],[87.03317,20.74331],[86.49935,20.15164],[85.06027,19.47858],[83.94101,18.30201],[83.18922,17.67122],[82.19279,17.01664],[82.19124,16.55666],[81.69272,16.31022],[80.792,15.95197],[80.3249,15.89918],[80.02507,15.13641],[80.23327,13.83577],[80.28629,13.00626],[79.86255,12.05622],[79.858,10.35728],[79.34051,10.30885],[78.88535,9.54614],[79.18972,9.21654],[78.27794,8.93305],[77.94117,8.25296],[77.5399,7.96553],[76.59298,8.89928],[76.13006,10.29963],[75.74647,11.30825],[75.3961,11.78125],[74.86482,12.74194],[74.61672,13.99258],[74.44386,14.61722],[73.5342,15.99065],[73.11991,17.92857],[72.82091,19.20823],[72.82448,20.4195],[72.63053,21.35601],[71.17527,20.75744],[70.47046,20.87733],[69.16413,22.0893],[69.64493,22.45077],[69.3496,22.84318],[68.17665,23.69197],[68.8426,24.35913],[71.04324,24.35652],[70.8447,25.2151],[70.28287,25.72223],[70.16893,26.49187],[69.51439,26.94097],[70.6165,27.9892],[71.77767,27.91318],[72.82375,28.96159],[73.45064,29.97641],[74.42138,30.97981],[74.40593,31.69264],[75.25864,32.27111],[74.45156,32.7649],[74.10429,33.44147],[73.74995,34.3177],[74.2402,34.74889],[75.75706,34.50492],[76.87172,34.65354],[77.83745,35.49401]]]},\"properties\":{\"name\":\"India\"}}]}","volume":"108","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kumar, Pushpendra","contributorId":220793,"corporation":false,"usgs":false,"family":"Kumar","given":"Pushpendra","email":"","affiliations":[{"id":40268,"text":"Oil and Natural Gas Corporation, Panvel, Navi Mumbai, India","active":true,"usgs":false}],"preferred":false,"id":775784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":775783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"K. M. Shukla","contributorId":220795,"corporation":false,"usgs":false,"family":"K. M. Shukla","affiliations":[{"id":40269,"text":"Oil and Natural Gas Corporation Ltd","active":true,"usgs":false}],"preferred":false,"id":775785,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yadav, U. S.","contributorId":220796,"corporation":false,"usgs":false,"family":"Yadav","given":"U.","email":"","middleInitial":"S.","affiliations":[{"id":40270,"text":"Oil and Natural Gas Corporation Ltd.","active":true,"usgs":false}],"preferred":false,"id":775786,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lall, M. V.","contributorId":220797,"corporation":false,"usgs":false,"family":"Lall","given":"M.","email":"","middleInitial":"V.","affiliations":[{"id":40270,"text":"Oil and Natural Gas Corporation Ltd.","active":true,"usgs":false}],"preferred":false,"id":775787,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Krishna Vishwanath","contributorId":220798,"corporation":false,"usgs":false,"family":"Krishna Vishwanath","affiliations":[{"id":40271,"text":"Directorate General of Hydrocarbons","active":true,"usgs":false}],"preferred":false,"id":775788,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70206804,"text":"70206804 - 2019 - National Gas Hydrate Program expedition 02: Identification of gas hydrate prospects in the Krishna-Godavari Basin, offshore India","interactions":[],"lastModifiedDate":"2019-11-22T08:16:58","indexId":"70206804","displayToPublicDate":"2019-10-01T08:15:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2382,"text":"Journal of Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"National Gas Hydrate Program expedition 02: Identification of gas hydrate prospects in the Krishna-Godavari Basin, offshore India","docAbstract":"After completing the first expedition of India's National Gas Hydrate Program (NGHP-01) in 2006, it was concluded that for the next expedition (National Gas Hydrate Program 02; NGHP-02), a new drill site review effort should focus on identifying potential deep-water offshore gas hydrate accumulations in sand dominated depositional environments. Therefore, geological and geophysical data analysis and 3D seismic data interpretation along with associated seismic modeling were carried out in three areas of the Krishna-Godavari Basin: Areas B, C, and E. Conventional petroleum exploration approaches of seismic amplitude evaluation were adapted to prospect for potential sand-rich depositional systems within the gas hydrate stability zone. Subsequently, these prospective areas were further assessed through the geological and geophysical evaluation of depositional setting, gas sources, and gas migration pathways. In Area B, prospecting focused on a large anticlinal structure with a prominent bottom-simulating reflector and several key horizons that indicated evidence for potential sand-hosted hydrate occurrences. In Area C, the prospects were distributed throughout various settings within a very large deep-water channel-levee-fan system with complex indications of potential gas hydrate occurrence in sand-prone seismic facies. In Area E, prospects were associated with high amplitude events within inferred channel-levee sequences. Based on the pre-expedition/onboard drill-site evaluation, the 22 most promising sites in the Krishna-Godavari Basin were identified and prioritized to investigate and delineate a total of 17 identified gas hydrate prospects. This paper describes the geo-scientific studies carried out prior to NGHP-02 for site identification, evaluation and prioritization. An important outcome of this study is the identification of two potentially producible gas hydrate systems inferred to host significant quantity of gas hydrate in stratigraphic-structural traps.","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.11.013","usgsCitation":"Shukla, K., U.S. Yadav, Kumar, P., Collett, T., Boswell, R., Frye, M., M. Riedel, Kaurf, I., and Vishwanathf, K., 2019, National Gas Hydrate Program expedition 02: Identification of gas hydrate prospects in the Krishna-Godavari Basin, offshore India: Journal of Marine and Petroleum Geology, v. 108, p. 167-184, https://doi.org/10.1016/j.marpetgeo.2018.11.013.","productDescription":"18 p.","startPage":"167","endPage":"184","ipdsId":"IP-102093","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":459677,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"text":"Publisher Index 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Riedel","contributorId":220809,"corporation":false,"usgs":false,"family":"M. Riedel","affiliations":[{"id":40275,"text":"GEOMAR, Helmhotz Center for Ocean Research","active":true,"usgs":false}],"preferred":false,"id":775806,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kaurf, I.","contributorId":220810,"corporation":false,"usgs":false,"family":"Kaurf","given":"I.","email":"","affiliations":[{"id":40276,"text":"Directorate General of Hydrocarbon","active":true,"usgs":false}],"preferred":false,"id":775807,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vishwanathf, K.","contributorId":220811,"corporation":false,"usgs":false,"family":"Vishwanathf","given":"K.","email":"","affiliations":[{"id":40276,"text":"Directorate General of Hydrocarbon","active":true,"usgs":false}],"preferred":false,"id":775808,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70206805,"text":"70206805 - 2019 - Numerical simulations of depressurization-induced gas production from an interbedded turbidite gas hydrate-bearing sedimentary section in the offshore India: Site NGHP-02-16 (Area-B)","interactions":[],"lastModifiedDate":"2019-11-22T08:11:09","indexId":"70206805","displayToPublicDate":"2019-10-01T08:06:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2382,"text":"Journal of Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Numerical simulations of depressurization-induced gas production from an interbedded turbidite gas hydrate-bearing sedimentary section in the offshore India: Site NGHP-02-16 (Area-B)","docAbstract":"The recent National Gas Hydrate Program Expedition 02 (NGHP-02) identified the existence of gas hydrate-bearing sand reservoirs at a number of sites in the offshore of India including Site NGHP-02-16 in Area-B of the Krishna-Godavari Basin. The architecture of that gas hydrate accumulation is characterized by thin, gas hydrate-bearing, high quality sand layers interbedded with mud layers within a turbidite interval. The lowest gas hydrate-bearing layer contacting a thinly-interbedded saline aquifer designates the base of the gas hydrate stability zone (BGHSZ). The proximity of the BGHSZ and the average temperature around 20oC make the reservoir a favorable target for hydrate destabilization by means of the depressurization method. The results of the reservoir simulations indicate high gas production potential from this marine gas hydrate deposit with manageable concomitant water production using a well completion design that hydraulically isolates layers with water-saturated sands. Using a detailed geological input model, the predicted cumulative gas rates reach 3.1 x 104 m3/day (1.1 mmscf/day) after 90 days of continuous depressurization and demonstrate sustained production rates of 3.0 x 104 m3/day (1.0 mmscf/day) after 5 years of production. The interbedded nature of this gas hydrate occurrence promotes the development of horizontal dissociation interfaces between gas hydrate-bearing sand and mud layers. As a result, non-uniform gas production along the horizontal interfaces becomes a primary determinant of reservoir performance. Simulation cases have been executed to determine the impact of the uncertainty in in situ reservoir permeability and the manner in which intrinsic permeability dynamically changes during dissociation in response to the imposed effective stress increase. The cases where effective permeability is initially low and compaction is highly sensitive to stress result in the least favorable production predictions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.10.047","usgsCitation":"Myshakin, E.M., Seol, Y., Lin, J., Uchida, S., Collett, T., and Boswell, R., 2019, Numerical simulations of depressurization-induced gas production from an interbedded turbidite gas hydrate-bearing sedimentary section in the offshore India: Site NGHP-02-16 (Area-B): Journal of Marine and Petroleum Geology, v. 108, p. 619-638, https://doi.org/10.1016/j.marpetgeo.2018.10.047.","productDescription":"20 p.","startPage":"619","endPage":"638","ipdsId":"IP-100825","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":459680,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1607771","text":"Publisher Index 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Shun","contributorId":195142,"corporation":false,"usgs":false,"family":"Uchida","given":"Shun","email":"","affiliations":[],"preferred":false,"id":775813,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collett, Timothy 0000-0002-7598-4708","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":220812,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":775809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boswell, Ray","contributorId":195143,"corporation":false,"usgs":false,"family":"Boswell","given":"Ray","affiliations":[],"preferred":false,"id":775814,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70206806,"text":"70206806 - 2019 - India National Gas Hydrate Program Expedition 02 summary of scientific results: Numerical simulation of reservoir response to depressurization","interactions":[],"lastModifiedDate":"2019-11-22T08:04:12","indexId":"70206806","displayToPublicDate":"2019-10-01T08:02:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2382,"text":"Journal of Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"India National Gas Hydrate Program Expedition 02 summary of scientific results: Numerical simulation of reservoir response to depressurization","docAbstract":"The India National Gas Hydrate Program Expedition 02 (NGHP-02) discovered gas hydrate at high saturation in sand reservoirs at several sites in the deepwater Bay of Bengal. To assess the potential response of those deposits to scientific depressurization experiments, comprehensive geologic models were constructed to enable numerical simulation for two sites. Both sites (NGHP-02-09 and NGHP-02-16) feature thick sequences of thinly-interbedded reservoir and non-reservoir facies at sub-seafloor depths of less than 300 m and sub-sea depths of 2,400 m or more. These settings pose significant challenges to current modeling capabilities. First, the thinly-bedded reservoir architecture complicates the determination of basic reservoir parameters from both log and core data due to measurement resolution issues. Secondly, the fine-scale variation in sediment properties imparts great contrasts in key parameters over very short distances, creating high gradients at multiple scales and varying orientations that necessitate careful design of high-definition simulation grids. Thirdly, the deposits include internal sources of water, as well as a range of complex boundary conditions, including variable permeability within the overlying mud-rich “seals”, that complicate reservoir depressurization. Lastly, because of the unique combination of great water depth and relatively shallow sub-seafloor depth, models designed to maximize the dissociation rate impose large pressure drawdowns on relatively low-strength sediments. This condition renders the proper evaluation and integration of the geomechanical response to hydrate dissociation critical. In this report, we review the history of gas hydrate reservoir simulation, discuss methods for creating geologic input models, and summarize the key findings and implications of the collaborative NGHP-02 numerical simulation effort. Together, the studies confirm the viability of the modeled accumulations for scientific testing and identify key challenges related to the selection of specific test sites and the design of test wells.","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.09.026","usgsCitation":"Boswell, R., Myshakin, E., Moridis, G., Konno, Y., Collett, T.S., Reagan, M., Ajayi, T., and Seol, Y., 2019, India National Gas Hydrate Program Expedition 02 summary of scientific results: Numerical simulation of reservoir response to depressurization: Journal of Marine and Petroleum Geology, v. 108, p. 154-166, https://doi.org/10.1016/j.marpetgeo.2018.09.026.","productDescription":"13 p.","startPage":"154","endPage":"166","ipdsId":"IP-099199","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":459683,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Boswell, Ray","contributorId":195143,"corporation":false,"usgs":false,"family":"Boswell","given":"Ray","affiliations":[],"preferred":false,"id":775816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Myshakin, Evgeniy","contributorId":195140,"corporation":false,"usgs":false,"family":"Myshakin","given":"Evgeniy","affiliations":[],"preferred":false,"id":775818,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moridis, George","contributorId":220814,"corporation":false,"usgs":false,"family":"Moridis","given":"George","email":"","affiliations":[{"id":40278,"text":"Lawrence Berkeley National Laboratory, Berkeley, CA, USA","active":true,"usgs":false}],"preferred":false,"id":775817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Konno, Yoshihiro","contributorId":220815,"corporation":false,"usgs":false,"family":"Konno","given":"Yoshihiro","email":"","affiliations":[{"id":40279,"text":"The University of Tokyo, Chiba, Japan","active":true,"usgs":false}],"preferred":false,"id":775821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":775815,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reagan, Matthew","contributorId":220816,"corporation":false,"usgs":false,"family":"Reagan","given":"Matthew","email":"","affiliations":[{"id":40278,"text":"Lawrence Berkeley National Laboratory, Berkeley, CA, USA","active":true,"usgs":false}],"preferred":false,"id":775822,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ajayi, Taiwo","contributorId":178324,"corporation":false,"usgs":false,"family":"Ajayi","given":"Taiwo","email":"","affiliations":[],"preferred":false,"id":775819,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Seol, Yongkoo","contributorId":195139,"corporation":false,"usgs":false,"family":"Seol","given":"Yongkoo","email":"","affiliations":[],"preferred":false,"id":775820,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70205831,"text":"70205831 - 2019 - Discrete Zr and REE mineralization of the Baerzhe rare-metal deposit, China","interactions":[],"lastModifiedDate":"2019-10-08T07:50:17","indexId":"70205831","displayToPublicDate":"2019-10-01T07:49:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Discrete Zr and REE mineralization of the Baerzhe rare-metal deposit, China","docAbstract":"Although REE (lanthanides + Y) mineralization in alkaline silicate systems is commonly accompanied with Zr mineralization worldwide, our understanding of the relationship between Zr and REE mineralization is still incomplete (e.g. Škoda and Novák, 2007; Linnen et al., 2014; Petrella et al., 2014; Möller and Williams-Jones, 2016; Wu et al., 2018). The Baerzhe deposit in NE China is a source of Zr, REE, and Nb linked to the formation of an early Cretaceous, silica-saturated, alkaline intrusive complex. In-situ laser ablation–inductively coupled plasma mass spectrometry (LA-ICP-MS) analyses of zircon and monazite crystals constrain the relationship between Zr and REE mineralization at Baerzhe.\nThree populations of zircon are identified and are differentiated based upon textural observations and compositional characteristics. Type I zircon display well-developed oscillatory zoning are are typically found as inclusions within sodic amphibole. Type II zircons are darker than Type I zircons in CL images, can overgrow Type I zircon, and have more irregular zoning and resorption features. Type III zircons contain irregular but translucent cores and rims with oscillatory zoning that are murky brown in color and grow in aggregates. Textural features and compositional data suggest that Types I and II zircon crystallized at the magmatic stage, with Type 1 being least altered and Type II being strongly altered, and Type III precipitated during the magmatic to magmatic-hydrothermal transition.\nWhereas the magnitude of the Eu anomaly is moderate in the barren alkaline granite, all three populations of zircon exhibit pronounced negative anomalies. Such features are difficult to explain exclusively by feldspar fractionation and could indicate the presence of fluid modification of the rocks. Monazite crystals occur mostly through replacement of zircon and sodic amphibole; monazite clusters are also present. Textural and compositional evidence suggests that monazite at Baerzhe is hydrothermal.\nLeast and strongly altered magmatic zircon yield 207Pb-corrected 206Pb/238U ages of 127.3±1.2 Ma and 125.67±0.76 Ma, respectively. Deuteric zircon precipitated at 125.11±0.69 Ma. The chronological data suggest that the magmatic stage of the highly-evolved Baerzhe alkaline granite lasted less than two million years. Hydrothermal monazite records REE mineralization at 123.41±0.63 Ma, approximately 1 or 2 million years later than Zr mineralization. We therefore propose a model in which parental magmas underwent extensive magmatic differentiation while residual melts interacted with aqueous hydrothermal fluids. Deuteric zircon precipitated from a hydrosilicate liquid, and subsequent REE mineralization, exemplified by hydrothermal monazite, correlates with the metasomatic alteration from external fluid sources. Such interplay between magmatic and hydrothermal processes resulted in the formation of discrete Zr and REE mineralization at Baerzhe.","language":"English","publisher":"GeoScienceWorld","doi":"10.2138/am-2019-6890","usgsCitation":"Qiu, K., Yu, H., Wu, M., Geng, J., Ge, X., Gou, Z., and Taylor, R., 2019, Discrete Zr and REE mineralization of the Baerzhe rare-metal deposit, China: American Mineralogist, v. 104, no. 10, p. 1487-1502, https://doi.org/10.2138/am-2019-6890.","productDescription":"16 p.","startPage":"1487","endPage":"1502","ipdsId":"IP-103418","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Qiu, Kunfeng","contributorId":219546,"corporation":false,"usgs":false,"family":"Qiu","given":"Kunfeng","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":772528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yu, Haocheng","contributorId":219547,"corporation":false,"usgs":false,"family":"Yu","given":"Haocheng","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":772529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wu, Mingqian","contributorId":219548,"corporation":false,"usgs":false,"family":"Wu","given":"Mingqian","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":772530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Geng, Jianzhen","contributorId":219549,"corporation":false,"usgs":false,"family":"Geng","given":"Jianzhen","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":772531,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ge, Xiangkun","contributorId":219550,"corporation":false,"usgs":false,"family":"Ge","given":"Xiangkun","email":"","affiliations":[{"id":40023,"text":"Beijing Research Institute of Uranium Geology, Beijing","active":true,"usgs":false}],"preferred":false,"id":772532,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gou, Zongyang","contributorId":219551,"corporation":false,"usgs":false,"family":"Gou","given":"Zongyang","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":772533,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Taylor, Ryan D. 0000-0002-8845-5290","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":201948,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":772527,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70206403,"text":"70206403 - 2019 - Ensembles of ETAS models provide optimal operational earthquake forecasting during swarms: Insights from the 2015 San Ramon, California swarm","interactions":[],"lastModifiedDate":"2019-12-03T10:01:11","indexId":"70206403","displayToPublicDate":"2019-10-01T06:48:33","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Ensembles of ETAS models provide optimal operational earthquake forecasting during swarms: Insights from the 2015 San Ramon, California swarm","docAbstract":"Earthquake swarms, typically modeled as time-varying changes in background seismicity that are driven by external processes such as fluid flow or aseismic creep, present challenges for operational earthquake forecasting. While the time decay of aftershock sequences can be estimated with the modified Omori law, it is difficult to forecast the temporal behavior of seismicity rates during a swarm. To explore these issues, we apply the Epidemic-Type Aftershock Sequence (ETAS) model (Ogata, JASA, 1988) to the 2015 San Ramon, California swarm, which lasted several weeks and had almost 100 2≤M≤3.6 earthquakes. We develop 3-day forecasts during the swarm based on an ETAS model fit to all prior seismicity in the region as well as an ETAS model fit only to previous swarms in the region, which is better at capturing the higher background rate during the swarm. We also explore forecasts where the background rate is updated periodically during the swarm using data over different lookback windows and find that generally these models perform better than the models where the background rate is fixed. Finally, we construct ensemble forecasts by combining the different models weighted according to their performance. The ensemble forecasts outperform all of the individual models and allow us to avoid making arbitrary choices at the outset of a swarm as to which single model will perform the best.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120190020","usgsCitation":"Llenos, A.L., and Michael, A.J., 2019, Ensembles of ETAS models provide optimal operational earthquake forecasting during swarms: Insights from the 2015 San Ramon, California swarm: Bulletin of the Seismological Society of America, v. 109, no. 6, p. 2145-2158, https://doi.org/10.1785/0120190020.","productDescription":"14 p.","startPage":"2145","endPage":"2158","ipdsId":"IP-101090","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":368858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Contra Costa County","city":"San 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