{"pageNumber":"216","pageRowStart":"5375","pageSize":"25","recordCount":40783,"records":[{"id":70222088,"text":"70222088 - 2021 - Mapping of suspended sediment transport using acoustic methods in a Pantanal tributary","interactions":[],"lastModifiedDate":"2021-07-19T23:32:45.066778","indexId":"70222088","displayToPublicDate":"2021-07-15T18:24:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Mapping of suspended sediment transport using acoustic methods in a Pantanal tributary","docAbstract":"<p><span>Generally, fluvial systems are used for different objectives including energy production, water supply, recreation, and navigation. Thus, many impacts must be considered with their use. An understanding of sediment dynamics in fluvial systems is often of value for a variety of objectives, given that erosion and depositional processes can change the fluvial system morphology and can substantially alter the fluvial environment. In this sense, sediment monitoring is important because it helps to explain and quantify sediment dynamics in the environment. Hence, this study presents an innovative sediment monitoring technique: the use of the acoustic Doppler current profiler, commonly used to obtain discharge measurements, to obtain suspended sediment concentration (SSC). This paper aims to describe the application of additional corrections to the ADP-M9 signal to obtain SSC from measurement campaigns that used the ADP only for discharge measurements. The analyses were based on traditional sediment sampling methods and discharge measurements, with the ADP-M9, from 7 field campaigns at the Taquari River, a major tributary from the Alto Paraguay Basin, in the Pantanal Biome, known as the largest freshwater wetland system in the world. The correlation was assessed considering the following: (a) the equipment frequency operation mode (Smart Pulse or Fixed Frequency) and (b) by checking the influence of the sediment attenuation coefficient. Furthermore, extrapolation was conducted in filtered and unmeasured areas of the ADP to map the suspended sediment concentration over the entire cross section. Results indicate that ADP correlations can be an effective tool for estimating SSC in the Taquari River when samples cannot be collected. Correlations could be applied to past and future ADP measurements made at the location where the correlation was created, as long as similar environmental conditions are present as when the correlation was developed. The described technique can expand the amount of sediment data available at a monitoring site even with reduced traditional sampling and by leveraging instruments used for other monitoring purposes.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10661-021-09266-w","usgsCitation":"Wosiacki, L.F., Koji Suekame, H., Wood, M.S., Verissimo Goncalves, F., and Bleninger, T., 2021, Mapping of suspended sediment transport using acoustic methods in a Pantanal tributary: Environmental Monitoring and Assessment, v. 193, 493, 19 p., https://doi.org/10.1007/s10661-021-09266-w.","productDescription":"493, 19 p.","ipdsId":"IP-120116","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":387258,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Taquari River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -57.041015625,\n              -22.105998799750566\n            ],\n            [\n              -54.31640625,\n              -19.84939395842278\n            ],\n            [\n              -52.9541015625,\n              -18.437924653474393\n            ],\n            [\n              -53.78906249999999,\n              -17.853290114098\n            ],\n            [\n              -53.7451171875,\n              -17.26672782352052\n            ],\n            [\n              -54.4921875,\n              -17.434510551522894\n            ],\n            [\n              -56.82128906249999,\n              -16.63619187839765\n            ],\n            [\n              -57.041015625,\n              -14.944784875088372\n            ],\n            [\n              -59.501953125,\n              -14.349547837185362\n            ],\n            [\n              -60.16113281250001,\n              -14.902321826141796\n            ],\n            [\n              -60.1171875,\n              -16.1724728083975\n            ],\n            [\n              -58.447265625,\n              -16.13026201203474\n            ],\n            [\n              -58.18359375,\n              -16.762467717941593\n            ],\n            [\n              -57.78808593749999,\n              -17.560246503294888\n            ],\n            [\n              -57.7001953125,\n              -18.729501999072138\n            ],\n            [\n              -58.3154296875,\n              -20.055931265194438\n            ],\n            [\n              -57.919921875,\n              -21.943045533438166\n            ],\n            [\n              -57.041015625,\n              -22.105998799750566\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"193","noUsgsAuthors":false,"publicationDate":"2021-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Wosiacki, Liege F.K.","contributorId":261197,"corporation":false,"usgs":false,"family":"Wosiacki","given":"Liege","email":"","middleInitial":"F.K.","affiliations":[{"id":52772,"text":"Federal University of Parana, Curitiba, Brazil","active":true,"usgs":false}],"preferred":false,"id":819460,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koji Suekame, Hugo","contributorId":261198,"corporation":false,"usgs":false,"family":"Koji Suekame","given":"Hugo","email":"","affiliations":[{"id":52773,"text":"Federal University of Mato Grosso do Sul, Campo Grande, Brazil","active":true,"usgs":false}],"preferred":false,"id":819461,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":819462,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verissimo Goncalves, Fabio","contributorId":261199,"corporation":false,"usgs":false,"family":"Verissimo Goncalves","given":"Fabio","email":"","affiliations":[{"id":52773,"text":"Federal University of Mato Grosso do Sul, Campo Grande, Brazil","active":true,"usgs":false}],"preferred":false,"id":819463,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bleninger, Tobias","contributorId":261200,"corporation":false,"usgs":false,"family":"Bleninger","given":"Tobias","email":"","affiliations":[{"id":52772,"text":"Federal University of Parana, Curitiba, Brazil","active":true,"usgs":false}],"preferred":false,"id":819464,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70224570,"text":"70224570 - 2021 - Down to Earth with nuclear electromagnetic pulse: Realistic surface impedance affects mapping of the E3 geoelectric hazard","interactions":[],"lastModifiedDate":"2021-09-28T12:22:22.806471","indexId":"70224570","displayToPublicDate":"2021-07-15T07:20:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9361,"text":"Earth and Space Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Down to Earth with nuclear electromagnetic pulse: Realistic surface impedance affects mapping of the E3 geoelectric hazard","docAbstract":"<div class=\"article-section__content en main\"><p>An analysis is made of Earth-surface geoelectric fields and voltages on electricity transmission power-grids induced by a late-phase E3 nuclear electromagnetic pulse (EMP). A hypothetical scenario is considered of an explosion of several hundred kilotons set several hundred kilometers above the eastern-midcontinental United States. Ground-level E3 geoelectric fields are estimated by convolving a standard parameterization of E3 geomagnetic field variation with magnetotelluric Earth-surface impedance tensors derived from wideband measurements acquired across the study region during a recent survey. These impedance tensors are a function of subsurface three-dimensional electrical conductivity structure. Results, presented as a movie-map, demonstrate that localized differences in surface impedance strongly distort the amplitude, polarization, and variational phase of induced E3 geoelectric fields. Locations with a high degree of E3 geoelectric polarization tend to have high geoelectric amplitude. Uniform half-space models and one-dimensional, depth-dependent models of Earth-surface impedance, such as those widely used in government and industry reports informing power-grid vulnerability assessment projects, do not provide accurate estimates of the E3 geoelectric hazard in complex geological settings. In particular, for the Eastern-Midcontinent, half-space models can lead to (order-one) overestimates/underestimates of EMP-induced geovoltages on parts of the power grid by as much as<span>&nbsp;</span><img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/8e96158e-c9db-42eb-9c50-0ec06cf1a5bf/ess2899-math-0001.png\" alt=\"urn:x-wiley:23335084:media:ess2899:ess2899-math-0001\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/8e96158e-c9db-42eb-9c50-0ec06cf1a5bf/ess2899-math-0001.png\">1,000&nbsp;volts (a range of 2,000&nbsp;volts)—comparable to the amplitudes of the geovoltages themselves.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EA001792","usgsCitation":"Love, J.J., Lucas, G., Murphy, B.S., Bedrosian, P.A., Rigler, E.J., and Kelbert, A., 2021, Down to Earth with nuclear electromagnetic pulse: Realistic surface impedance affects mapping of the E3 geoelectric hazard: Earth and Space Sciences, v. 8, no. 8, e2021EA001792, 25 p., https://doi.org/10.1029/2021EA001792.","productDescription":"e2021EA001792, 25 p.","ipdsId":"IP-128556","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":451509,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021ea001792","text":"Publisher Index Page"},{"id":389861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":824100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lucas, Greg M. 0000-0003-1331-1863","orcid":"https://orcid.org/0000-0003-1331-1863","contributorId":223556,"corporation":false,"usgs":false,"family":"Lucas","given":"Greg M.","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":824101,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Benjamin Scott 0000-0001-7636-3711","orcid":"https://orcid.org/0000-0001-7636-3711","contributorId":242928,"corporation":false,"usgs":true,"family":"Murphy","given":"Benjamin","email":"","middleInitial":"Scott","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":824102,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":824103,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":824104,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelbert, Anna 0000-0003-4395-398X akelbert@usgs.gov","orcid":"https://orcid.org/0000-0003-4395-398X","contributorId":184053,"corporation":false,"usgs":true,"family":"Kelbert","given":"Anna","email":"akelbert@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":824105,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70221835,"text":"sir20215031 - 2021 - Optimization of the Idaho National Laboratory water-quality aquifer monitoring network, southeastern Idaho","interactions":[],"lastModifiedDate":"2021-07-16T12:31:02.274219","indexId":"sir20215031","displayToPublicDate":"2021-07-15T07:17:18","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5031","displayTitle":"Optimization of the Idaho National Laboratory Water-Quality Aquifer Monitoring Network, Southeastern Idaho","title":"Optimization of the Idaho National Laboratory water-quality aquifer monitoring network, southeastern Idaho","docAbstract":"<p class=\"p1\">Long-term monitoring of water-quality data collected from wells at the Idaho National Laboratory (INL) has provided essential information for delineating the movement of radiochemical and chemical wastes in the eastern Snake River Plain aquifer, southeastern Idaho. Since 1949, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, has maintained as many as 200 wells in the INL water-quality monitoring network. A network design tool, distributed as an R package, was developed to evaluate and optimize groundwater monitoring in the existing network based on water-quality data collected at 153 sampling sites since January 1, 1989. The objective of the optimization design tool is to reduce well monitoring redundancy while retaining sufficient data to reliably characterize water-quality conditions in the aquifer. A spatial optimization was used to identify a set of wells whose removal leads to the smallest increase in the deviation between interpolated concentration maps using the existing and reduced monitoring networks while preserving significant long-term trends and seasonal components in the data. Additionally, a temporal optimization was used to identify reductions in sampling frequencies by minimizing the redundancy in sampling events.</p><p class=\"p1\">Spatial optimization uses an islands genetic algorithm to identify near-optimal network designs removing 10, 20, 30, 40, and 50 wells from the existing monitoring network. With this method, choosing a greater number of wells to remove results in greater cost savings and decreased accuracy of the average relative difference between interpolated maps of the reduced-dataset and the full-dataset. The genetic search algorithm identified reduced networks that best capture the spatial patterns of the average concentration plume while preserving long-term temporal trends at individual wells. Concentration data for 10 analyte types are integrated in a single optimization so that all datasets may be evaluated simultaneously. A constituent was selected for inclusion in the spatial optimization problem when the observations were sufficient to (1) establish a two-range variability model, (2) classify at least one concentration time series as a continuous record block, and (3) make a prediction using the quantile-kriging interpolation method. The selected constituents include sodium, chloride, sulfate, nitrate, carbon tetrachloride, 1,1-dichloroethylene, 1,1,1-trichloroethane, trichloroethylene, tritium, strontium-90, and plutonium-238.</p><p class=\"p2\">In temporal optimization, an iterative-thinning method was used to find an optimal sampling frequency for each analyte-well pair. Optimal frequencies indicate that for many of the wells, samples may be collected less frequently and still be able to characterize the concentration over time. The optimization results indicated that the sample-collection interval may be increased by an of average of 273 days owing to temporal redundancy.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215031","collaboration":"DOE/ID-22252<br />Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Fisher, J.C., Bartholomay, R.C., Rattray, G.W., and Maimer, N.V., 2021, Optimization of the Idaho National Laboratory water-quality aquifer monitoring network, southeastern Idaho: U.S. Geological Survey Scientific Investigations Report 2021–5031 (DOE/ID-22252), 63 p., https://doi.org/10.3133/sir20215031.","productDescription":"Report: vii, 63 p.; Appendix 1-12; 2 Software Releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071486","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":387046,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app02.html","text":"Appendix 2","size":"854 KB","linkFileType":{"id":5,"text":"html"},"description":"SIR 2021-5031 Appendix 2"},{"id":387045,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app01.html","text":"Appendix 1","size":"6.3 MB","linkFileType":{"id":5,"text":"html"},"description":"SIR 2021-5031 Appendix 1"},{"id":387058,"rank":16,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9X71CSU","text":"USGS software release —","description":"USGS software release","linkHelpText":"ObsNetQW—Assessment of a water-quality aquifer monitoring network"},{"id":387057,"rank":15,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9PP9UXZ","text":"USGS software release —","description":"USGS software release","linkHelpText":"inldata—Collection of datasets for the U.S. Geological Survey-Idaho National Laboratory aquifer monitoring networks"},{"id":387056,"rank":14,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app12.pdf","text":"Appendix 12","size":"116 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 12"},{"id":387054,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app10.pdf","text":"Appendix 10","size":"171 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 10"},{"id":387053,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app09.pdf","text":"Appendix 9","size":"12.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 9"},{"id":387052,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app08.pdf","text":"Appendix 8","size":"138 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 8"},{"id":387051,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app07.pdf","text":"Appendix 7","size":"7.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 7"},{"id":387047,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app03.pdf","text":"Appendix 3","size":"354 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 3"},{"id":387043,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5031/coverthb.jpg"},{"id":387048,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app04.pdf","text":"Appendix 4","size":"14.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 4"},{"id":387049,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app05.pdf","text":"Appendix 5","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 5"},{"id":387050,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app06.pdf","text":"Appendix 6","size":"154 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 6"},{"id":387044,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031.pdf","text":"Report","size":"14.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031"},{"id":387055,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app11.pdf","text":"Appendix 11","size":"21.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 11"}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.4393310546875,\n              43.45291889355465\n            ],\n            [\n              -112.4725341796875,\n              43.432977075795606\n            ],\n            [\n              -112.43957519531251,\n              44.06390660801777\n            ],\n            [\n              -113.389892578125,\n              44.09547572946637\n            ],\n            [\n              -113.4393310546875,\n              43.45291889355465\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_id@usgs.gov\" data-mce-href=\"mailto:dc_id@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/id-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/id-water\">Idaho Water Science Center</a><br>U.S. Geological Survey<br>230 Collins Road<br>Boise, Idaho 83702-4520</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Sources and Descriptions of Data</li><li>Temporal Regression</li><li>Spatial Interpolation</li><li>Spatial Optimization</li><li>Temporal Optimization</li><li>Summary and Conclusions</li><li>Acknowledgments</li><li>Appendixes</li></ul>","publishedDate":"2021-07-15","noUsgsAuthors":false,"publicationDate":"2021-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Fisher, Jason C. 0000-0001-9032-8912 jfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-9032-8912","contributorId":2523,"corporation":false,"usgs":true,"family":"Fisher","given":"Jason","email":"jfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rattray, Gordon W. 0000-0002-1690-3218 grattray@usgs.gov","orcid":"https://orcid.org/0000-0002-1690-3218","contributorId":2521,"corporation":false,"usgs":true,"family":"Rattray","given":"Gordon","email":"grattray@usgs.gov","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818876,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maimer, Neil V. 0000-0003-3047-3282 nmaimer@usgs.gov","orcid":"https://orcid.org/0000-0003-3047-3282","contributorId":5659,"corporation":false,"usgs":true,"family":"Maimer","given":"Neil","email":"nmaimer@usgs.gov","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818877,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70224273,"text":"70224273 - 2021 - Electrical properties of carbon dioxide hydrate: Implications for monitoring CO2 in the gas hydrate stability zone","interactions":[],"lastModifiedDate":"2021-09-17T12:22:01.918037","indexId":"70224273","displayToPublicDate":"2021-07-15T07:09:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Electrical properties of carbon dioxide hydrate: Implications for monitoring CO2 in the gas hydrate stability zone","docAbstract":"<div class=\"article-section__content en main\"><p>CO<sub>2</sub><span>&nbsp;</span>and CH<sub>4</sub><span>&nbsp;</span>clathrate hydrates are of keen interest for energy and carbon cycle considerations. While both typically form on Earth as cubic structure I (sI), we find that pure CO<sub>2</sub><span>&nbsp;</span>hydrate exhibits over an order of magnitude higher electrical conductivity (<i>σ</i>) than pure CH<sub>4</sub><span>&nbsp;</span>hydrate at geologically relevant temperatures. The conductivity was obtained from frequency-dependent impedance (<i>Z</i>) measurements made on polycrystalline CO<sub>2</sub><span>&nbsp;</span>hydrate (CO<sub>2</sub>·6.0&nbsp;±&nbsp;0.2H<sub>2</sub>O by methods here) with 25% gas-filled porosity, compared with CH<sub>4</sub><span>&nbsp;</span>hydrate (CH<sub>4</sub>·5.9H<sub>2</sub>O) formed and measured in the same apparatus and exhibiting closely matching grain characteristics. The conductivity of CO<sub>2</sub><span>&nbsp;</span>hydrate is 6.5&nbsp;×&nbsp;10<sup>−4</sup><span>&nbsp;</span>S/m at 273K with an activation energy (<i>E</i><sub>a</sub>) of 46.5&nbsp;kJ/mol at 260–281&nbsp;K, compared with ∼5&nbsp;×&nbsp;10<sup>−5</sup><span>&nbsp;</span>S/m and 34.8&nbsp;kJ/m for CH<sub>4</sub><span>&nbsp;</span>hydrate. Equivalent circuit modeling indicates that different pathways govern conduction in CO<sub>2</sub><span>&nbsp;</span>versus CH<sub>4</sub><span>&nbsp;</span>hydrate. Results show promise for use of electromagnetic methods in monitoring CO<sub>2</sub><span>&nbsp;</span>hydrate formation in certain natural settings or in CO<sub>2</sub>/CH<sub>4</sub><span>&nbsp;</span>exchange efforts.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL093475","usgsCitation":"Stern, L.A., Constable, S., Lu, R., Du Frane, W.L., and Roberts, J., 2021, Electrical properties of carbon dioxide hydrate: Implications for monitoring CO2 in the gas hydrate stability zone: Geophysical Research Letters, v. 48, no. 15, e2021GL093475, 9 p., https://doi.org/10.1029/2021GL093475.","productDescription":"e2021GL093475, 9 p.","ipdsId":"IP-125168","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":451512,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1811333","text":"Publisher Index Page"},{"id":389384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"15","noUsgsAuthors":false,"publicationDate":"2021-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Stern, Laura A. 0000-0003-3440-5674","orcid":"https://orcid.org/0000-0003-3440-5674","contributorId":212238,"corporation":false,"usgs":true,"family":"Stern","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":823427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Constable, S.","contributorId":238841,"corporation":false,"usgs":false,"family":"Constable","given":"S.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":823428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lu, Ryan","contributorId":238835,"corporation":false,"usgs":false,"family":"Lu","given":"Ryan","email":"","affiliations":[{"id":13621,"text":"Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":823429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Du Frane, Wyatt L.","contributorId":23067,"corporation":false,"usgs":false,"family":"Du Frane","given":"Wyatt","email":"","middleInitial":"L.","affiliations":[{"id":13621,"text":"Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":823430,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, J. Murray","contributorId":190580,"corporation":false,"usgs":false,"family":"Roberts","given":"J. Murray","affiliations":[],"preferred":false,"id":823431,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70229177,"text":"70229177 - 2021 - Demographic responses to climate change in a threatened Arctic species","interactions":[],"lastModifiedDate":"2022-03-02T17:55:54.727772","indexId":"70229177","displayToPublicDate":"2021-07-14T11:45:17","publicationYear":"2021","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":"Demographic responses to climate change in a threatened Arctic species","docAbstract":"<p><span>The Arctic is undergoing rapid and accelerating change in response to global warming, altering biodiversity patterns, and ecosystem function across the region. For Arctic endemic species, our understanding of the consequences of such change remains limited. Spectacled eiders (</span><i>Somateria fischeri</i><span>), a large Arctic sea duck, use remote regions in the Bering Sea, Arctic Russia, and Alaska throughout the annual cycle making it difficult to conduct comprehensive surveys or demographic studies. Listed as Threatened under the U.S. Endangered Species Act, understanding the species response to climate change is critical for effective conservation policy and planning. Here, we developed an integrated population model to describe spectacled eider population dynamics using capture–mark–recapture, breeding population survey, nest survey, and environmental data collected between 1992 and 2014. Our intent was to estimate abundance, population growth, and demographic rates, and quantify how changes in the environment influenced population dynamics. Abundance of spectacled eiders breeding in western Alaska has increased since listing in 1993 and responded more strongly to annual variation in first-year survival than adult survival or productivity. We found both adult survival and nest success were highest in years following intermediate sea ice conditions during the wintering period, and both demographic rates declined when sea ice conditions were above or below average. In recent years, sea ice extent has reached new record lows and has remained below average throughout the winter for multiple years in a row. Sea ice persistence is expected to further decline in the Bering Sea. Our results indicate spectacled eiders may be vulnerable to climate change and the increasingly variable sea ice conditions throughout their wintering range with potentially deleterious effects on population dynamics. Importantly, we identified that different demographic rates responded similarly to changes in sea ice conditions, emphasizing the need for integrated analyses to understand population dynamics.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7873","usgsCitation":"Dunham, K., Tucker, A., Koons, D., Abebe, A., Dobson, F., and Grand, J.B., 2021, Demographic responses to climate change in a threatened Arctic species: Ecology and Evolution, v. 11, no. 15, p. 10627-10643, https://doi.org/10.1002/ece3.7873.","productDescription":"17 p.","startPage":"10627","endPage":"10643","ipdsId":"IP-123223","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":451515,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.7873","text":"Publisher Index Page"},{"id":396660,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic Coastal Plain, Arctic Russia, Yukon-Kuskokwim Delta","volume":"11","issue":"15","noUsgsAuthors":false,"publicationDate":"2021-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Dunham, K.D.","contributorId":287550,"corporation":false,"usgs":false,"family":"Dunham","given":"K.D.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":836868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, A.M.","contributorId":287552,"corporation":false,"usgs":false,"family":"Tucker","given":"A.M.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":836869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koons, D.N.","contributorId":287553,"corporation":false,"usgs":false,"family":"Koons","given":"D.N.","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":836870,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abebe, A.","contributorId":287556,"corporation":false,"usgs":false,"family":"Abebe","given":"A.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":836871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dobson, F.S.","contributorId":287558,"corporation":false,"usgs":false,"family":"Dobson","given":"F.S.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":836872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":836873,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70221762,"text":"70221762 - 2021 - Comparison of preservation and extraction methods on five taxonomically disparate coral microbiomes","interactions":[],"lastModifiedDate":"2021-09-15T13:44:45.088065","indexId":"70221762","displayToPublicDate":"2021-07-14T08:42:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of preservation and extraction methods on five taxonomically disparate coral microbiomes","docAbstract":"<p><span>All animals are host to a multitude of microorganisms that are essential to the animal’s health. Host-associated microbes have been shown to defend against potential pathogens, provide essential nutrients, interact with the host’s immune system, and even regulate mood. However, it can be difficult to preserve and obtain nucleic acids from some host-associated microbiomes, making studying their microbial communities challenging. Corals are an example of this, in part due to their potentially remote, underwater locations, their thick surface mucopolysaccharide layer, and various inherent molecular inhibitors. This study examined three different preservatives (RNAlater, DNA/RNA Shield, and liquid nitrogen) and two extraction methods (the Qiagen PowerBiofilm kit and the Promega Maxwell RBC kit with modifications) to determine if there was an optimum combination for examining the coral microbiome. These methods were employed across taxonomically diverse coral species, including deep-sea/shallow, stony/soft, and zooxanthellate/azooxanthellate:&nbsp;</span><i>Lophelia pertusa</i><span>,&nbsp;</span><i>Paragorgia johnsoni</i><span>,&nbsp;</span><i>Montastraea cavernosa</i><span>,&nbsp;</span><i>Porites astreoides</i><span>, and&nbsp;</span><i>Stephanocoenia intersepta</i><span>. Although significant differences were found between preservative types and extraction methods, these differences were subtle, and varied in nature from coral species to coral species. Significant differences between coral species were far more profound than those detected between preservative or extraction method. We suggest that the preservative types presented here and extraction methods using a bead-beating step provide enough consistency to compare coral microbiomes across various studies, as long as subtle differences in microbial communities are attributed to dissimilar methodologies. Additionally, the inclusion of internal controls such as a mock community and extraction blanks can help provide context regarding data quality, improving downstream analyses.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2021.684161","usgsCitation":"Pratte, Z.A., and Kellogg, C.A., 2021, Comparison of preservation and extraction methods on five taxonomically disparate coral microbiomes: Frontiers in Marine Science, v. 8, 684161, 13 p., https://doi.org/10.3389/fmars.2021.684161.","productDescription":"684161, 13 p.","ipdsId":"IP-127754","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451519,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2021.684161","text":"Publisher Index Page"},{"id":436274,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96GBWDM","text":"USGS data release","linkHelpText":"Coral Microbiome Preservation and Extraction Method Comparison-Raw Data"},{"id":389261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2021-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Pratte, Zoe A.","contributorId":214260,"corporation":false,"usgs":false,"family":"Pratte","given":"Zoe","email":"","middleInitial":"A.","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":818655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":818656,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70222564,"text":"70222564 - 2021 - A reactive transport approach to modeling cave seepage water chemistry I: Carbon isotope transformations","interactions":[],"lastModifiedDate":"2021-09-14T16:45:51.996528","indexId":"70222564","displayToPublicDate":"2021-07-14T07:58:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"A reactive transport approach to modeling cave seepage water chemistry I: Carbon isotope transformations","docAbstract":"<p><span>The majority of Critical Zone research has emphasized silicate lithologies, which are typified by relatively slow rates of reactivity and incongruent weathering. However, the relatively simpler weathering of carbonate-dominated lithology can result in secondary mineral deposits, such as speleothems, which provide a long-term archive for Critical Zone processes. In particular, carbon isotopic variability in speleothems has the potential to provide records of changes in vegetation, soil respiration, carbon stabilization in deep soils, and/or chemical weathering in the host rock. Despite this opportunity to reconstruct many Critical Zone processes, multiple influences can also make interpretion of these speleothem carbon isotope records challenging. The integration of observational data and simulations specific to karst systems offers an interpretive framework for these unique time-averaged records accumulated through the evolution of carbonate landscapes. Here, we present a forward and process-based reactive transport simulation based on a multi-year monitoring study of Blue Spring Cave in central Tennessee, USA. The simulations describe the fluid-driven weathering of limestone including explicit tracking of dissolved calcium, stable carbon, and radiocarbon isotope ratios based on reaction rates calibrated through laboratory batch reaction data. We find that calcium concentrations and radiocarbon isotope ratios are strongly influenced by the combination of fluid flow rate and soil CO</span><sub>2</sub><span>&nbsp;content, and require rapid gas phase communication between the overlying soil boundary condition and interior karst to sustain both elevated limestone weathering rates and relatively modern radiocarbon signatures. Stable carbon isotopes are largely dictated by temperature-dependent equilibrium fractionation among contemporaneous species. These simulations are extended to a wide range of parameter space to demonstrate the environmental factors that these isotope proxies record.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2021.06.041","usgsCitation":"Druhan, J., Lawrence, C., Covey, A., Giannetta, M., and Oster, J., 2021, A reactive transport approach to modeling cave seepage water chemistry I: Carbon isotope transformations: Geochimica et Cosmochimica Acta, v. 311, p. 374-400, https://doi.org/10.1016/j.gca.2021.06.041.","productDescription":"27 p.","startPage":"374","endPage":"400","ipdsId":"IP-125015","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":451520,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2021.06.041","text":"Publisher Index Page"},{"id":436277,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90OTSDY","text":"USGS data release","linkHelpText":"Data from a reactive transport modeling study of cave seepage water chemistry"},{"id":387713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"311","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Druhan, Jennifer","contributorId":245460,"corporation":false,"usgs":false,"family":"Druhan","given":"Jennifer","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":820565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Corey 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202373,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":820566,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Covey, Aaron","contributorId":261749,"corporation":false,"usgs":false,"family":"Covey","given":"Aaron","email":"","affiliations":[{"id":36656,"text":"Vanderbilt University","active":true,"usgs":false}],"preferred":false,"id":820567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giannetta, Max","contributorId":261750,"corporation":false,"usgs":false,"family":"Giannetta","given":"Max","email":"","affiliations":[{"id":35161,"text":"University of Illinois, Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":820568,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oster, Jessica","contributorId":223020,"corporation":false,"usgs":false,"family":"Oster","given":"Jessica","email":"","affiliations":[{"id":36656,"text":"Vanderbilt University","active":true,"usgs":false}],"preferred":false,"id":820569,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70222566,"text":"70222566 - 2021 - A reactive transport approach to modeling cave seepage water chemistry II: Elemental signatures","interactions":[],"lastModifiedDate":"2021-09-14T16:44:59.280495","indexId":"70222566","displayToPublicDate":"2021-07-14T07:53:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"A reactive transport approach to modeling cave seepage water chemistry II: Elemental signatures","docAbstract":"<p><span>Karst&nbsp;systems are useful for examining spatial and temporal variability in Critical Zone processes because they provide a window into the subsurface where waters have interacted with vegetation, soils,&nbsp;regolith, and&nbsp;bedrock&nbsp;across a range of length and timescales. These hydrologic pathways frequently include the precipitation of&nbsp;speleothems, which provide long-term archives of climate and environmental change. Trace element ratios in speleothems (Mg/Ca, Sr/Ca, Ba/Ca) have the potential to provide information about past changes in rainfall and&nbsp;infiltration, but controls on them can be complex and their interpretation must be based on an understanding of the modern cave system. Here we integrate observations of surface conditions, bedrock, soil, and drip water chemistry of Blue Spring Cave in Tennessee, USA with the reactive transport model CrunchTope, which we have calibrated for karst systems to investigate the primary controls on trace element variations in cave&nbsp;seepage waters. We find that measured drip water Mg/Ca and Sr/Ca are captured within the model through variable amounts of&nbsp;limestone&nbsp;dissolution followed by precipitation of secondary&nbsp;calcite&nbsp;that happens within the cave rather than the host limestone. However, strong spatial controls on drip water Mg/Ca and Sr/Ca likely reflect seepage water interactions with variable amounts of diagenetic phases in the host rock. In contrast, Ba/Ca values are consistent across the cave and vary with effective rainfall, suggesting that this parameter may be the most consistent metric for limestone dissolution and prior calcite precipitation and can act as a proxy for rainfall and infiltration in this cave system. Our findings emphasize the importance of evaluating spatial heterogeneity in cave drip waters and outline a novel modeling approach for determining the dominant controls on drip water chemistry in support of the interpretations of&nbsp;</span>paleoclimate<span>&nbsp;records.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2021.06.040","usgsCitation":"Oster, J., Covey, A., Lawrence, C., Giannetta, M., and Druhan, J., 2021, A reactive transport approach to modeling cave seepage water chemistry II: Elemental signatures: Geochimica et Cosmochimica Acta, v. 311, p. 353-373, https://doi.org/10.1016/j.gca.2021.06.040.","productDescription":"21 p.","startPage":"353","endPage":"373","ipdsId":"IP-125017","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":451523,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2021.06.040","text":"Publisher Index Page"},{"id":387712,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"311","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oster, Jessica","contributorId":223020,"corporation":false,"usgs":false,"family":"Oster","given":"Jessica","email":"","affiliations":[{"id":36656,"text":"Vanderbilt University","active":true,"usgs":false}],"preferred":false,"id":820570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Covey, Aaron","contributorId":261749,"corporation":false,"usgs":false,"family":"Covey","given":"Aaron","email":"","affiliations":[{"id":36656,"text":"Vanderbilt University","active":true,"usgs":false}],"preferred":false,"id":820571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, Corey 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202373,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":820572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giannetta, Max","contributorId":261750,"corporation":false,"usgs":false,"family":"Giannetta","given":"Max","email":"","affiliations":[{"id":35161,"text":"University of Illinois, Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":820573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Druhan, Jennifer","contributorId":245460,"corporation":false,"usgs":false,"family":"Druhan","given":"Jennifer","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":820574,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70222449,"text":"70222449 - 2021 - An efficient method to calculate depth-integrated, phase-averaged momentum balances in non-hydrostatic models","interactions":[],"lastModifiedDate":"2021-09-07T17:19:28.836874","indexId":"70222449","displayToPublicDate":"2021-07-13T09:05:01","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2925,"text":"Ocean Modelling","active":true,"publicationSubtype":{"id":10}},"title":"An efficient method to calculate depth-integrated, phase-averaged momentum balances in non-hydrostatic models","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"d1e3147\" class=\"abstract author\"><div id=\"d1e3150\"><p id=\"d1e3151\">Analysis of the mean (wave-averaged) momentum balance is a common approach used to explain the physical forcing driving wave set-up and mean currents in the nearshore zone. Traditionally this approach has been applied to phase-averaged models but has more recently been applied to phase-resolving models using post-processing, whereby model output is used to calculate each of the momentum terms. While phase-resolving models have the advantage of capturing the nonlinear properties of waves propagating in the nearshore (making them advantageous to enhance understanding of nearshore processes), the post-processing calculation of the momentum terms does not guarantee that the momentum balance closes. We show that this is largely due to the difficulty (or impossibility) of being consistent with the numerical approach. If the residual is of a similar magnitude as any of the relevant momentum terms (which is common with post-processing methods as we show), the analysis is largely compromised. Here we present a new method to internally calculate and extract the depth-integrated, mean momentum terms in the phase-resolving non-hydrostatic wave-flow model SWASH in a manner that is consistent with the numerical implementation. Further, we demonstrate the utility of the new method with two existing physical model studies. By being consistent with the numerical framework, the internal method calculates the momentum terms with a much lower residual at computer precision, combined with greatly reduced calculation time and output storage requirements compared to post-processing techniques. The method developed here allows the accurate evaluation of the depth-integrated, mean momentum terms of wave-driven flows while taking advantage of the more complete representation of the wave dynamics offered by phase-resolving models. Furthermore, it provides an opportunity for advances in the understanding of nearshore processes particularly at more complex sites where wave nonlinearity and energy transfers are important.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocemod.2021.101846","usgsCitation":"da Silva, R.F., Rijnsdorp, D.P., Hansen, J., Lowe, R.J., Buckley, M.L., and Zijlema, M., 2021, An efficient method to calculate depth-integrated, phase-averaged momentum balances in non-hydrostatic models: Ocean Modelling, v. 165, 101846, 18 p., https://doi.org/10.1016/j.ocemod.2021.101846.","productDescription":"101846, 18 p.","ipdsId":"IP-126521","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451531,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.ocemod.2021.101846","text":"External Repository"},{"id":387595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"165","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"da Silva, Renan F.","contributorId":261462,"corporation":false,"usgs":false,"family":"da Silva","given":"Renan","email":"","middleInitial":"F.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":820066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rijnsdorp, Dirk P.","contributorId":261463,"corporation":false,"usgs":false,"family":"Rijnsdorp","given":"Dirk","email":"","middleInitial":"P.","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":820067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Jeff E.","contributorId":146437,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff E.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":820068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":820069,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":820070,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zijlema, Marcel","contributorId":261465,"corporation":false,"usgs":false,"family":"Zijlema","given":"Marcel","email":"","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":820071,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70224970,"text":"70224970 - 2021 - Maintaining momentum for collaborative working groups in a post-pandemic world","interactions":[],"lastModifiedDate":"2021-10-11T13:21:20.07778","indexId":"70224970","displayToPublicDate":"2021-07-13T08:08:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6505,"text":"Nature Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Maintaining momentum for collaborative working groups in a post-pandemic world","docAbstract":"<div class=\"c-article-section__content\"><p>Scientific progress depends in part on our ability to synthesize heterogeneous data and ideas into new models and paradigms. In environmental sciences, such synthesis has been particularly effective when conducted by collaborative working groups: diverse groups of researchers and practitioners brought together for a concentrated period of collaboration on key questions. Such work is often done at synthesis centres: organizations that promote, fund, organize and host working groups and other collaborative research and training activities<sup><a id=\"ref-link-section-d5956665e652\" title=\"Baron, J. S. et al. 67, 750–759 (2017).\" href=\"https://www.nature.com/articles/s41559-021-01521-0#ref-CR1\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 1\" data-mce-href=\"https://www.nature.com/articles/s41559-021-01521-0#ref-CR1\">1</a></sup>. However, because of the COVID-19 pandemic, synthesis centres have had to rapidly adapt to supporting fully virtual working groups; the eight centres we direct supported 68 virtual working groups in the past year. Based on this experience, we conclude — contrary to a recent editorial on conferences published in this journal<sup><a id=\"ref-link-section-d5956665e656\" title=\"Nat. Ecol. Evol. 4, 1569 (2020).\" href=\"https://www.nature.com/articles/s41559-021-01521-0#ref-CR2\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 2\" data-mce-href=\"https://www.nature.com/articles/s41559-021-01521-0#ref-CR2\">2</a></sup><span>&nbsp;</span>— that virtual gatherings, while providing a bridge during the pandemic, cannot replace immersive, in-person collaborations. In-person working group meetings involve productive and varied interactions for many hours over consecutive days. We have found that virtual sessions lose effectiveness after a few hours, as participants become fatigued from staring at a screen or juggling local demands. While virtual meetings can work for short, well-delineated tasks, they are less suited for unstructured and free-flowing discussions — and thus struggle to create the social cohesion and trust known to fuel creative breakthroughs during week-long in-person meetings<sup><a id=\"ref-link-section-d5956665e660\" title=\"Hackett, E., Parker, J., Conz, D., Rhoten, D. &amp; Parker, A. In Scientific Collaboration on the Internet (eds Olson, G. et al. 277–296 (MIT Press, 2008).\" href=\"https://www.nature.com/articles/s41559-021-01521-0#ref-CR3\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 3\" data-mce-href=\"https://www.nature.com/articles/s41559-021-01521-0#ref-CR3\">3</a></sup>.</p></div>","language":"English","publisher":"Nature","doi":"10.1038/s41559-021-01521-0","usgsCitation":"Srivastava, D., Marten Winter, Gross, L., Metzger, J.P., Baron, J., Mouquet, N., Meagher, T., Halpern, B., and Pillar, V., 2021, Maintaining momentum for collaborative working groups in a post-pandemic world: Nature Ecology and Evolution, v. 5, p. 1188-1189, https://doi.org/10.1038/s41559-021-01521-0.","productDescription":"2 p.","startPage":"1188","endPage":"1189","ipdsId":"IP-129181","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":451534,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41559-021-01521-0","text":"Publisher Index Page"},{"id":390384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2021-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Srivastava, Diane","contributorId":267304,"corporation":false,"usgs":false,"family":"Srivastava","given":"Diane","affiliations":[{"id":36972,"text":"University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":824939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marten Winter","contributorId":267305,"corporation":false,"usgs":false,"family":"Marten Winter","affiliations":[{"id":55469,"text":"University of Leipzig, Germany","active":true,"usgs":false}],"preferred":false,"id":824940,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gross, Louis","contributorId":267306,"corporation":false,"usgs":false,"family":"Gross","given":"Louis","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":824941,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Metzger, Jena Paul","contributorId":267307,"corporation":false,"usgs":false,"family":"Metzger","given":"Jena","email":"","middleInitial":"Paul","affiliations":[{"id":55470,"text":"University of Sao Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":824942,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baron, Jill S. 0000-0002-5902-6251","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":215101,"corporation":false,"usgs":true,"family":"Baron","given":"Jill S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":824943,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mouquet, Nicolas","contributorId":267308,"corporation":false,"usgs":false,"family":"Mouquet","given":"Nicolas","email":"","affiliations":[{"id":55471,"text":"CESAB, Montpelier France","active":true,"usgs":false}],"preferred":false,"id":824944,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meagher, Thomas","contributorId":267309,"corporation":false,"usgs":false,"family":"Meagher","given":"Thomas","affiliations":[{"id":16945,"text":"St. Andrews University, UK","active":true,"usgs":false}],"preferred":false,"id":824945,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Halpern, Ben","contributorId":267310,"corporation":false,"usgs":false,"family":"Halpern","given":"Ben","email":"","affiliations":[{"id":27356,"text":"UC-Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":824946,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pillar, Valerio","contributorId":267311,"corporation":false,"usgs":false,"family":"Pillar","given":"Valerio","affiliations":[{"id":55472,"text":"Universidade Federal do Rio Grande do Sul, Brazil","active":true,"usgs":false}],"preferred":false,"id":824947,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70222607,"text":"70222607 - 2021 - NGA-East Ground-Motion Characterization model part I: Summary of products and model development","interactions":[],"lastModifiedDate":"2021-08-09T12:55:45.893875","indexId":"70222607","displayToPublicDate":"2021-07-13T07:53:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"NGA-East Ground-Motion Characterization model part I: Summary of products and model development","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>In this article, we present an overview of the research project NGA-East, Next Generation Attenuation for Central and Eastern North America (CENA), and summarize the key methodology and products. The project was tasked with developing a new ground motion characterization (GMC) model for CENA. The final NGA-East GMC model includes a set of 17 median ground motion models (GMMs) for peak ground acceleration and velocity (PGA, PGV) and response spectral ordinates for periods ranging from 0.01 to 10 s. The NGA-East GMMs are applicable to horizontal components of ground motions on very hard rock, for the moment magnitude range of 4.0–8.2, and distances of up to 1500 km. The aleatory standard deviations of GMMs are also provided for site-specific analysis (single-station standard deviation) and for general probabilistic seismic hazard analyses (PSHA) applications (ergodic standard deviation). In addition, adjustment factors are provided for source depth and hanging-wall effects, as well as for hazard computations at sites in the Gulf Coast Region. During the course of the project, several innovative technologies were developed and implemented to increase the transparency and repeatability of the GMC building process. This involved expanding on a set of candidate median GMMs to define and capture an appropriate range of epistemic uncertainty in ground motions. We also developed a new approach for modeling the aleatory variability that was completely independent of the median GMMs. The development made extensive use of the CENA database but also borrowed data from other parts of the world when relevant and led to an integrated suite of models. Through this repeatable process, epistemic uncertainty could be quantified more objectively than before, relying less on expert opinion. The NGA-East project went through a comprehensive Seismic Senior Hazard Analysis Committee (SSHAC) Level 3 peer review process before its release.</p></div></div>","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1177/87552930211018723","usgsCitation":"Goulet, C.A., Bozorgnia, Y., Kuehn, N., Al Atik, L., Youngs, R., Graves, R., and Atkinson, G.M., 2021, NGA-East Ground-Motion Characterization model part I: Summary of products and model development: Earthquake Spectra, v. 37, no. 1, p. 1231-1282, https://doi.org/10.1177/87552930211018723.","productDescription":"52 p.","startPage":"1231","endPage":"1282","ipdsId":"IP-128860","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":387768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -105.8203125,\n              47.754097979680026\n            ],\n            [\n              -105.8203125,\n              31.052933985705163\n            ],\n            [\n              -100.546875,\n              26.43122806450644\n            ],\n            [\n              -95.2734375,\n              26.43122806450644\n            ],\n            [\n              -89.296875,\n              26.43122806450644\n            ],\n            [\n              -82.6171875,\n              25.799891182088334\n            ],\n            [\n              -78.75,\n              26.115985925333536\n            ],\n            [\n              -76.9921875,\n              31.653381399664\n            ],\n            [\n              -73.47656249999999,\n              38.272688535980976\n            ],\n            [\n              -67.8515625,\n              41.50857729743935\n            ],\n            [\n              -59.4140625,\n              45.336701909968134\n            ],\n            [\n              -49.92187499999999,\n              47.27922900257082\n            ],\n            [\n              -56.953125,\n              53.74871079689897\n            ],\n            [\n              -62.22656249999999,\n              59.17592824927136\n            ],\n            [\n              -72.0703125,\n              62.75472592723178\n            ],\n            [\n              -81.9140625,\n              63.23362741232569\n            ],\n            [\n              -100.1953125,\n              62.431074232920906\n            ],\n            [\n              -108.6328125,\n              61.270232790000634\n            ],\n            [\n              -105.8203125,\n              47.754097979680026\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"37","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Goulet, Christine A. 0000-0002-7643-357X","orcid":"https://orcid.org/0000-0002-7643-357X","contributorId":194805,"corporation":false,"usgs":false,"family":"Goulet","given":"Christine","email":"","middleInitial":"A.","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":820721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bozorgnia, Yousef","contributorId":40101,"corporation":false,"usgs":false,"family":"Bozorgnia","given":"Yousef","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":820722,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuehn, Nicolas","contributorId":229633,"corporation":false,"usgs":false,"family":"Kuehn","given":"Nicolas","email":"","affiliations":[{"id":6772,"text":"UC Los Angeles","active":true,"usgs":false}],"preferred":false,"id":820723,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Al Atik, Linda","contributorId":140526,"corporation":false,"usgs":false,"family":"Al Atik","given":"Linda","email":"","affiliations":[],"preferred":false,"id":820724,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Youngs, Robert","contributorId":140544,"corporation":false,"usgs":false,"family":"Youngs","given":"Robert","affiliations":[],"preferred":false,"id":820727,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":820726,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Atkinson, Gail M.","contributorId":60515,"corporation":false,"usgs":false,"family":"Atkinson","given":"Gail","email":"","middleInitial":"M.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":820725,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70227321,"text":"70227321 - 2021 - Selection of random vibration theory procedures for the NGA-East project and ground-motion modeling","interactions":[],"lastModifiedDate":"2022-01-10T13:23:28.38076","indexId":"70227321","displayToPublicDate":"2021-07-13T07:19:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Selection of random vibration theory procedures for the NGA-East project and ground-motion modeling","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Traditional ground-motion models (GMMs) are used to compute pseudo-spectral acceleration (PSA) from future earthquakes and are generally developed by regression of PSA using a physics-based functional form. PSA is a relatively simple metric that correlates well with the response of several engineering systems and is a metric commonly used in engineering evaluations; however, characteristics of the PSA calculation make application of scaling factors dependent on the frequency content of the input motion, complicating the development and adaptability of GMMs. By comparison, Fourier amplitude spectrum (FAS) represents ground-motion amplitudes that are completely independent from the amplitudes at other frequencies, making them an attractive alternative for GMM development. Random vibration theory (RVT) predicts the peak response of motion in the time domain based on the FAS and a duration, and thus can be used to relate FAS to PSA. Using RVT to compute the expected peak response in the time domain for given FAS therefore presents a significant advantage that is gaining traction in the GMM field. This article provides recommended RVT procedures relevant to GMM development, which were developed for the Next Generation Attenuation (NGA)-East project. In addition, an orientation-independent FAS metric—called the effective amplitude spectrum (EAS)—is developed for use in conjunction with RVT to preserve the mean power of the corresponding two horizontal components considered in traditional PSA-based modeling (i.e., RotD50). The EAS uses a standardized smoothing approach to provide a practical representation of the FAS for ground-motion modeling, while minimizing the impact on the four RVT properties (<i>zeroth</i><span>&nbsp;</span>moment,<span>&nbsp;</span><span class=\"equationTd\">m0</span>; bandwidth parameter,<span>&nbsp;</span><span class=\"equationTd\">δ</span>; frequency of zero crossings,<span>&nbsp;</span><span class=\"equationTd\">fz</span>; and frequency of extrema,<span>&nbsp;</span><span class=\"equationTd\">fe</span>). Although the recommendations were originally developed for NGA-East, they and the methodology they are based on can be adapted to become portable to other GMM and engineering problems requiring the computation of PSA from FAS.</p></div></div>","language":"English","publisher":"Sage Publications","doi":"10.1177/87552930211019052","usgsCitation":"Kottke, A.R., Abrahamson, N., Boore, D., Bozorgina, Y., Goulet, C.A., Hollenback, J., Kishida, T., Ktenidou, O., Rathje, E., Silva, W., Thompson, E.M., and Wang, X., 2021, Selection of random vibration theory procedures for the NGA-East project and ground-motion modeling: Earthquake Spectra, v. 37, no. 1, p. 1420-1439, https://doi.org/10.1177/87552930211019052.","productDescription":"20 p.","startPage":"1420","endPage":"1439","ipdsId":"IP-129456","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":394095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Kottke, Albert R.","contributorId":271023,"corporation":false,"usgs":false,"family":"Kottke","given":"Albert","email":"","middleInitial":"R.","affiliations":[{"id":56254,"text":"Pacific Gas & Electric, San Francisco, CA 94105","active":true,"usgs":false}],"preferred":false,"id":830440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abrahamson, Norman A.","contributorId":45202,"corporation":false,"usgs":false,"family":"Abrahamson","given":"Norman A.","affiliations":[{"id":13174,"text":"Pacific Gas & Electric","active":true,"usgs":false}],"preferred":false,"id":830441,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boore, David 0000-0002-8605-9673 boore@usgs.gov","orcid":"https://orcid.org/0000-0002-8605-9673","contributorId":140502,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":830442,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bozorgina, Yousef","contributorId":271024,"corporation":false,"usgs":false,"family":"Bozorgina","given":"Yousef","email":"","affiliations":[{"id":56148,"text":"University of California, Los Angeles, CA 90095","active":true,"usgs":false}],"preferred":false,"id":830443,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goulet, Christine A. 0000-0002-7643-357X","orcid":"https://orcid.org/0000-0002-7643-357X","contributorId":194805,"corporation":false,"usgs":false,"family":"Goulet","given":"Christine","email":"","middleInitial":"A.","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":830444,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hollenback, Justin","contributorId":271025,"corporation":false,"usgs":false,"family":"Hollenback","given":"Justin","email":"","affiliations":[],"preferred":false,"id":830445,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kishida, Tadahiro","contributorId":140538,"corporation":false,"usgs":false,"family":"Kishida","given":"Tadahiro","email":"","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":830446,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ktenidou, Olga-Joan","contributorId":271026,"corporation":false,"usgs":false,"family":"Ktenidou","given":"Olga-Joan","email":"","affiliations":[{"id":56255,"text":"National Observatory of Athens","active":true,"usgs":false}],"preferred":false,"id":830447,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rathje, Ellen 0000-0002-4169-7153","orcid":"https://orcid.org/0000-0002-4169-7153","contributorId":197024,"corporation":false,"usgs":false,"family":"Rathje","given":"Ellen","email":"","affiliations":[],"preferred":false,"id":830448,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Silva, Walt","contributorId":271027,"corporation":false,"usgs":false,"family":"Silva","given":"Walt","email":"","affiliations":[{"id":56256,"text":"Pacific Engineering & Analysis","active":true,"usgs":false}],"preferred":false,"id":830449,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":830450,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wang, Xiaoyue","contributorId":271028,"corporation":false,"usgs":false,"family":"Wang","given":"Xiaoyue","email":"","affiliations":[{"id":56257,"text":"Geosyntec Consultants, Inc.","active":true,"usgs":false}],"preferred":false,"id":830451,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70227890,"text":"70227890 - 2021 - Ecological correlates of fecal corticosterone metabolites in female Greater Sage-Grouse (Centrococercus urophasianus)","interactions":[],"lastModifiedDate":"2022-02-01T16:44:04.82136","indexId":"70227890","displayToPublicDate":"2021-07-12T10:37:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Ecological correlates of fecal corticosterone metabolites in female Greater Sage-Grouse (<i>Centrococercus urophasianus</i>)","title":"Ecological correlates of fecal corticosterone metabolites in female Greater Sage-Grouse (Centrococercus urophasianus)","docAbstract":"Measurement of physiological responses can reveal effects of ecological conditions on\nan animal and correlate with demographic parameters. Ecological conditions for many animal\nspecies have deteriorated as a function of invasive plants and habitat fragmentation. Expansion\nof juniper (Juniperus spp.) trees and invasion of annual grasses into sagebrush (Artemisia spp.)\necosystems have contributed to habitat degradation for Greater Sage-Grouse (Centrococercus\nurophasianus (Bonaparte, 1827); hereafter, “Sage-Grouse”), a species of conservation concern\nthroughout its range. We evaluated relationships between habitat use in a landscape modified by juniper expansion and annual grasses and corticosterone metabolite levels (stress responses) in feces (FCORTm) of female Sage-Grouse.  We used remotely sensed data to estimate vegetation cover within hens’ home ranges and accounted for factors that influence FCORTm in other vertebrates, such as age and weather. We collected 36 fecal samples from 22 radio-collared hens during the brood-rearing season (24 May–26 July) in southwestern Idaho 2017–18. Concentrations of corticosterone increased with home range size but decreased with reproductive effort and temperature. The importance of home range size suggests that maintaining or improving habitats that promote smaller home ranges would likely facilitate a lower stress response by hens, which should benefit Sage-Grouse survival and reproduction.","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjz-2020-0258","usgsCitation":"Rabon, J.C., Nunez, C., Coates, P.S., Ricca, M.A., and Johnson, T.N., 2021, Ecological correlates of fecal corticosterone metabolites in female Greater Sage-Grouse (Centrococercus urophasianus): Canadian Journal of Zoology, v. 99, no. 9, p. 812-822, https://doi.org/10.1139/cjz-2020-0258.","productDescription":"11 p.","startPage":"812","endPage":"822","ipdsId":"IP-129805","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":395211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.49902343749999,\n              45.61403741135093\n            ],\n            [\n              -116.883544921875,\n              45.058001435398275\n            ],\n            [\n              -116.883544921875,\n              44.95702412512118\n            ],\n            [\n              -116.98242187499999,\n              44.80132682904856\n            ],\n            [\n              -117.04833984375001,\n              44.77013681219717\n            ],\n            [\n              -117.27905273437499,\n              44.4808302785626\n            ],\n            [\n              -117.257080078125,\n              44.268804788566165\n            ],\n            [\n              -117.13623046874999,\n              44.213709909702054\n            ],\n            [\n              -116.927490234375,\n              44.134913443750726\n            ],\n            [\n              -117.05932617187499,\n              43.858296779161826\n            ],\n            [\n              -117.05932617187499,\n              42.00032514831621\n            ],\n            [\n              -114.071044921875,\n              41.9921602333763\n            ],\n            [\n              -114.14794921875,\n              45.66012730272194\n            ],\n            [\n              -116.49902343749999,\n              45.61403741135093\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"99","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rabon, Jordan C.","contributorId":223734,"corporation":false,"usgs":false,"family":"Rabon","given":"Jordan","email":"","middleInitial":"C.","affiliations":[{"id":40761,"text":"Department of Fish and Wildlife Sciences, University of Idaho, Moscow, ID 83844","active":true,"usgs":false}],"preferred":false,"id":832475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nunez, Cassandra","contributorId":273037,"corporation":false,"usgs":false,"family":"Nunez","given":"Cassandra","email":"","affiliations":[{"id":56418,"text":"University of Memphis, 3774 Walker Avenue, Memphis, TN 38152, USA.","active":true,"usgs":false}],"preferred":false,"id":832476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":832477,"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":832478,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Tracey N. 0000-0003-3480-8596","orcid":"https://orcid.org/0000-0003-3480-8596","contributorId":223735,"corporation":false,"usgs":false,"family":"Johnson","given":"Tracey","email":"","middleInitial":"N.","affiliations":[{"id":40761,"text":"Department of Fish and Wildlife Sciences, University of Idaho, Moscow, ID 83844","active":true,"usgs":false}],"preferred":false,"id":832479,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70221838,"text":"70221838 - 2021 - Optimizing preservation for multiple types of historic structures under climate change","interactions":[],"lastModifiedDate":"2021-07-13T09:54:47.042075","indexId":"70221838","displayToPublicDate":"2021-07-12T06:41:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2603,"text":"Landscape and Urban Planning","active":true,"publicationSubtype":{"id":10}},"title":"Optimizing preservation for multiple types of historic structures under climate change","docAbstract":"<p><span>Cultural resources in coastal parks and recreation areas are vulnerable to climate change. The US National Park Service (NPS) is facing the challenge of insufficient budget allocations for both maintenance and climate adaptation of historic structures. Research on adaptation planning for cultural resources has predominately focused on vulnerability assessments of heritage sites; however, few studies integrate multiple factors (e.g., vulnerability, cultural significance, use potential, and costs) that managers should consider when making tradeoff decisions about which cultural resources to prioritize for adaptation. Moreover, heritage sites typically include multiple types of cultural resources, and researchers have yet to examine such complex tradeoffs. This study applies the Optimal Preservation (OptiPres) Model as a decision support framework to evaluate the tradeoffs of adaptation actions among multiple types of historic structures—wooden buildings, masonry and concrete buildings, forts, and batteries—under varying budget scenarios. Results suggest that the resource values of different types of historic structures vary greatly under a range of budget scenarios, and tradeoffs have to be made among different types of historical structures to achieve optimal planning objectives. Moreover, periodic, incremental funding and partial maintenance are identified as optimal funding strategies for preservation needs of cost-intensive historic structures. Also, adaptative use of historical buildings (e.g., building occupancy) can improve the resource values when budgets are constrained. The OptiPres Model provides managers with a unique framework to inform adaptation planning efforts for a broad range of historic structures, which is transferable across coastal parks to enhance historic preservation planning under climate change.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.landurbplan.2021.104165","usgsCitation":"Xiao, X., Seekamp, E., Lu, J., Eaton, M.J., and van der Burg, M., 2021, Optimizing preservation for multiple types of historic structures under climate change: Landscape and Urban Planning, v. 214, 104165, 14 p., https://doi.org/10.1016/j.landurbplan.2021.104165.","productDescription":"104165, 14 p.","ipdsId":"IP-122847","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":451550,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.landurbplan.2021.104165","text":"Publisher Index Page"},{"id":387064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"214","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Xiao, Xiao","contributorId":212835,"corporation":false,"usgs":false,"family":"Xiao","given":"Xiao","email":"","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":818891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seekamp, Erin","contributorId":212832,"corporation":false,"usgs":false,"family":"Seekamp","given":"Erin","email":"","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":818892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lu, Junyu","contributorId":260820,"corporation":false,"usgs":false,"family":"Lu","given":"Junyu","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":818893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":818894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van der Burg, Max Post 0000-0002-3943-4194","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":219439,"corporation":false,"usgs":true,"family":"van der Burg","given":"Max Post","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":818895,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70238782,"text":"70238782 - 2021 - Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands","interactions":[],"lastModifiedDate":"2022-12-12T14:20:29.236213","indexId":"70238782","displayToPublicDate":"2021-07-10T08:06:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":681,"text":"Agricultural and Forest Meteorology","active":true,"publicationSubtype":{"id":10}},"title":"Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands","docAbstract":"Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2021.108528","usgsCitation":"Irvin, J., Zhou, S., McNicol, G., Lu, F., Liu, V., Fluet-Chouinard, E., Ouyang, Z., Knox, S., Lucas-Moffat, A., Trotta, C., Papale, D., Vitale, D., Mammarella, I., Alekseychik, P., Aurela, M., Avati, A., Baldocchi, D., Bansal, S., Bohrer, G., Campbell, D.I., Chen, J., Chu, H., Dalmagro, H.J., Delwiche, K.B., Desai, A.R., Euskirchen, E.S., Feron, S., Goeckede, M., Heimann, M., Helbig, M., Helfter, C., Hemes, K.S., Hirano, T., Iwata, H., Jurasinski, G., Kalhori, A., Kondrich, A., Lai, D., Lohila, A., Malholtra, A., Merbold, L., Mitra, B., Ng, A., Nilsson, M.B., Noormets, A., Peichl, M., Rey-Sanchez, A.C., Richardson, A.D., Runkle, B.R., Schafer, K.V., Sonnentag, O., Stuart-Haëntjens, E., Sturtevant, C., Ueyama, M., Valach, A.C., Vargas, R., Vourlitis, G.L., Ward, E., Wong, G.X., Zona, D., Alberto, M.C., Billesbach, D.P., Celis, G., Dolman, H., Friborg, T., Fuchs, K., Gogo, S., Gondwe, M.J., Goodrich, J.P., Gottschalk, P., Hortnagl, L., Jacotot, A., Koebsch, F., Kasak, K., Maier, R., Morin, T.H., Nemitz, E., Oechel, W.C., Oikawa, P.Y., Ono, K., Sachs, T., Sakabe, A., Schuur, E.A., Shortt, R., Sullivan, R.C., Szutu, D.J., Tuittila, E., Varlagin, A., Verfaillie, J.G., Wille, C., Windham-Myers, L., Poulter, B., and Jackson, R.B., 2021, Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands: Agricultural and Forest Meteorology, v. 308–309, 108528, 22 p., https://doi.org/10.1016/j.agrformet.2021.108528.","productDescription":"108528, 22 p.","ipdsId":"IP-126298","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":451557,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agrformet.2021.108528","text":"Publisher Index Page"},{"id":410275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"308–309","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Irvin, Jeremy","contributorId":299776,"corporation":false,"usgs":false,"family":"Irvin","given":"Jeremy","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":858602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhou, Sharon","contributorId":299777,"corporation":false,"usgs":false,"family":"Zhou","given":"Sharon","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":858603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McNicol, Gavin 0000-0002-6655-8045","orcid":"https://orcid.org/0000-0002-6655-8045","contributorId":260536,"corporation":false,"usgs":false,"family":"McNicol","given":"Gavin","email":"","affiliations":[],"preferred":false,"id":858604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lu, Fred","contributorId":299807,"corporation":false,"usgs":false,"family":"Lu","given":"Fred","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":858605,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liu, Vincent","contributorId":299778,"corporation":false,"usgs":false,"family":"Liu","given":"Vincent","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":858606,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fluet-Chouinard, Etienne","contributorId":217392,"corporation":false,"usgs":false,"family":"Fluet-Chouinard","given":"Etienne","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":858607,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ouyang, Zutao","contributorId":260556,"corporation":false,"usgs":false,"family":"Ouyang","given":"Zutao","email":"","affiliations":[],"preferred":false,"id":858608,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Knox, Sara Helen 0000-0003-2255-5835","orcid":"https://orcid.org/0000-0003-2255-5835","contributorId":272609,"corporation":false,"usgs":false,"family":"Knox","given":"Sara Helen","affiliations":[{"id":56388,"text":"U. 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Robert","contributorId":299795,"corporation":false,"usgs":false,"family":"Shortt","given":"Robert","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":858685,"contributorType":{"id":1,"text":"Authors"},"rank":84},{"text":"Sullivan, Ryan C.","contributorId":265858,"corporation":false,"usgs":false,"family":"Sullivan","given":"Ryan","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":858686,"contributorType":{"id":1,"text":"Authors"},"rank":85},{"text":"Szutu, Daphne J.","contributorId":299796,"corporation":false,"usgs":false,"family":"Szutu","given":"Daphne","email":"","middleInitial":"J.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":858687,"contributorType":{"id":1,"text":"Authors"},"rank":86},{"text":"Tuittila, Eeva-Stiina 0000-0001-8861-3167","orcid":"https://orcid.org/0000-0001-8861-3167","contributorId":169412,"corporation":false,"usgs":false,"family":"Tuittila","given":"Eeva-Stiina","email":"","affiliations":[{"id":25501,"text":"University of Eastern Finland","active":true,"usgs":false}],"preferred":false,"id":858688,"contributorType":{"id":1,"text":"Authors"},"rank":87},{"text":"Varlagin, Andrej","contributorId":192447,"corporation":false,"usgs":false,"family":"Varlagin","given":"Andrej","email":"","affiliations":[],"preferred":false,"id":858689,"contributorType":{"id":1,"text":"Authors"},"rank":88},{"text":"Verfaillie, Joseph G.","contributorId":265863,"corporation":false,"usgs":false,"family":"Verfaillie","given":"Joseph","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":858690,"contributorType":{"id":1,"text":"Authors"},"rank":89},{"text":"Wille, Christian","contributorId":243134,"corporation":false,"usgs":false,"family":"Wille","given":"Christian","email":"","affiliations":[{"id":48644,"text":"GFZ German Research Center for Geosciences","active":true,"usgs":false}],"preferred":false,"id":858691,"contributorType":{"id":1,"text":"Authors"},"rank":90},{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":858692,"contributorType":{"id":1,"text":"Authors"},"rank":91},{"text":"Poulter, Benjamin","contributorId":298276,"corporation":false,"usgs":false,"family":"Poulter","given":"Benjamin","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":858693,"contributorType":{"id":1,"text":"Authors"},"rank":92},{"text":"Jackson, Robert B. 0000-0001-8846-7147","orcid":"https://orcid.org/0000-0001-8846-7147","contributorId":34252,"corporation":false,"usgs":false,"family":"Jackson","given":"Robert","email":"","middleInitial":"B.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":858694,"contributorType":{"id":1,"text":"Authors"},"rank":93}]}}
,{"id":70223249,"text":"70223249 - 2021 - BERM: A Belowground Ecosystem Resiliency Model for estimating Spartina alterniflora belowground biomass","interactions":[],"lastModifiedDate":"2021-09-14T16:56:06.518591","indexId":"70223249","displayToPublicDate":"2021-07-09T11:26:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"BERM: A Belowground Ecosystem Resiliency Model for estimating <i>Spartina alterniflora</i> belowground biomass","title":"BERM: A Belowground Ecosystem Resiliency Model for estimating Spartina alterniflora belowground biomass","docAbstract":"<h3 class=\"article-section__header main abstractlang_en main\">Summary</h3><div class=\"article-section__content en main\"><ul class=\"unordered-list\"><li>Spatiotemporal patterns of<span>&nbsp;</span><i>Spartina alterniflora</i><span>&nbsp;</span>belowground biomass (BGB) are important for evaluating salt marsh resiliency. To solve this, we created the BERM (Belowground Ecosystem Resiliency Model), which estimates monthly BGB (30-m spatial resolution) from freely available data such as Landsat-8 and Daymet climate summaries.</li><li>Our modeling framework relied on extreme gradient boosting, and used field observations from four Georgia salt marshes as ground-truth data. Model predictors included estimated tidal inundation, elevation, leaf area index, foliar nitrogen, chlorophyll, surface temperature, phenology, and climate data. The final model included 33 variables, and the most important variables were elevation, vapor pressure from the previous four months, Normalized Difference Vegetation Index (NDVI) from the previous five months, and inundation.</li><li>Root mean squared error for BGB from testing data was 313&nbsp;g&nbsp;m<sup>−2</sup><span>&nbsp;</span>(11% of the field data range), explained variance (<i>R</i><sup>2</sup>) was 0.62–0.77. Testing data results were unbiased across BGB values and were positively correlated with ground-truth data across all sites and years (<i>r</i>&nbsp;= 0.56–0.82 and 0.45–0.95, respectively).</li><li>BERM can estimate BGB within<span>&nbsp;</span><i>Spartina alterniflora</i><span>&nbsp;</span>salt marshes where environmental parameters are within the training data range, and can be readily extended through a reproducible workflow. This provides a powerful approach for evaluating spatiotemporal BGB and associated ecosystem function.</li></ul></div>","language":"English","publisher":"New Phytologists Foundation","doi":"10.1111/nph.17607","usgsCitation":"O'Connell, J., Mishra, D., Alber, M., and Byrd, K.B., 2021, BERM: A Belowground Ecosystem Resiliency Model for estimating Spartina alterniflora belowground biomass: New Phytologist, v. 232, no. 1, p. 425-439, https://doi.org/10.1111/nph.17607.","productDescription":"15 p.","startPage":"425","endPage":"439","ipdsId":"IP-130221","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":451565,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.17607","text":"Publisher Index Page"},{"id":388162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"232","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-08-13","publicationStatus":"PW","contributors":{"authors":[{"text":"O'Connell, Jessica L.","contributorId":264435,"corporation":false,"usgs":false,"family":"O'Connell","given":"Jessica L.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":821528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mishra, Deepak","contributorId":264436,"corporation":false,"usgs":false,"family":"Mishra","given":"Deepak","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":821529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alber, Merryl","contributorId":264437,"corporation":false,"usgs":false,"family":"Alber","given":"Merryl","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":821530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":821531,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227093,"text":"70227093 - 2021 - Forecasting the distribution of a range-expanding bat reveals future response to climate change and habitat","interactions":[],"lastModifiedDate":"2021-12-29T14:50:27.623224","indexId":"70227093","displayToPublicDate":"2021-07-09T08:36:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":629,"text":"Acta Chiropterologica","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting the distribution of a range-expanding bat reveals future response to climate change and habitat","docAbstract":"Many terrestrial vertebrate species are exhibiting geographic distribution changes including poleward range limit shifts in response to increases in regional temperature. Bats are a highly mobile taxa capable of rapid responses to changes in abiotic or biotic conditions. In North America, recent extralimital records of the non-hibernating Lasiurus seminolus (Seminole bat) have been attributed to climate change, however such attributions remain speculative and potentially subject to sampling bias in the form of increased recent sampling efforts at latitudes north of the historical range. We used historical occurrence records and simple environmental variables within a Maxent modeling framework to model the historical distribution of suitable areas for this species. We transferred the model using near current environmental conditions and measured the ability of the model to capture the apparent expansion in distribution using recent extralimital occurrence records. This measure indicated a distribution expansion, largely attributed to increasing minimum temperatures. We used the model to forecast the expansion in distribution of suitable areas at three 20-year intervals and various climate change scenarios and provide extrapolation risk maps for each scenario. Although increasing temperatures may increase potentially occupiable areas, the species is associated with forests and often roosts in Pinus spp. (pines). This suitable habitat is reduced in presence to the northwest of the species’ range, which may constrain the future species expansion despite favorable temperatures. We demonstrated this effect by mapping limiting factors through future climate change scenarios. We discovered a broad shift of effects that constrained the distribution from minimum temperature to a metric of evergreen cover type as time and climate intensity increased. Although uncertainties exist, we predict further expansion of the Seminole bat widely over the next 60 years across the eastern United States where suitable habitat and climate conditions converge. Our results appear consistent with other bat species showing similar range extensions and in turn provide further evidence that bats may serve as bioindicators of global change.","language":"English","publisher":"Polish Academy of Sciences, Museum & Institute of Zoology","doi":"10.3161/15081109ACC2021.23.1.011","usgsCitation":"True, M., Perry, R., and Ford, W., 2021, Forecasting the distribution of a range-expanding bat reveals future response to climate change and habitat: Acta Chiropterologica, v. 23, no. 1, p. 139-152, https://doi.org/10.3161/15081109ACC2021.23.1.011.","productDescription":"14 p.","startPage":"139","endPage":"152","ipdsId":"IP-122280","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":451567,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/106685","text":"External 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,{"id":70221816,"text":"sir20215056 - 2021 - Hydraulic modeling at selected dam-removal and culvert-retrofit sites in the northeastern United States","interactions":[],"lastModifiedDate":"2021-07-09T11:58:58.971817","indexId":"sir20215056","displayToPublicDate":"2021-07-08T16:19:59","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5056","displayTitle":"Hydraulic Modeling at Selected Dam-Removal and Culvert-Retrofit Sites in the Northeastern United States","title":"Hydraulic modeling at selected dam-removal and culvert-retrofit sites in the northeastern United States","docAbstract":"<p>Aquatic connectivity projects, such as removing dams and modifying culverts, have substantial benefits. The restoration of natural flow conditions improves water quality, sediment transport, aquatic and riparian habitat, and fish passage. These projects can also decrease hazards faced by communities by lowering water-surface elevations of flood waters and by removing the risk of dam breaches associated with aging or inadequate infrastructure.<br><br>This report documents and provides results of one- and two-dimensional hydraulic models developed for selected rivers and streams in the northeastern United States where a dam was removed or a culvert was retrofitted. The models were developed for conditions before and after the dam removal or culvert modification. The discharges applied in the models included monthly discharges and flood discharges for the annual exceedance probabilities of 50, 20, 10, 4, 2, 1, 0.5, and 0.2 percent.<br><br>This study, by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service, demonstrates the benefits resulting from dam removal and retrofitting undersized culverts in terms of decreased water-surface elevations during flooding and improved fish passage. The U.S. Army Corps of Engineers Hydrologic Engineering Center’s River Analysis System was used to model the sites in one- and two-dimensional hydraulics, and decreases in the 1-percent annual exceedance probability discharge water-surface elevation were found at all sites studied. The decreases in water-surface elevation at sites in which the impoundment was removed ranged from 1.3 to 10.4 feet. One site, Bradford Dam in Westerly, Rhode Island, had only a 0.2-foot decrease, but at that site the dam was replaced by a series of weirs to retain the upstream impoundment and allow fish passage.<br><br>Minimal differences were found between the water-surface elevations computed by the one- and two-dimensional models. The two-dimensional models, however, provide the additional benefit of detailed velocity and depth data throughout the channel at a resolution not possible with a one-dimensional model. These velocity and depth data allowed for assessment of the suitability for fish passage at the sites. Fish passage was improved at all the sites by removing the dams and retrofitting the culvert. Prolonged swim velocity criteria for selected fish species were maintained throughout three of the nine study sites, and burst swim velocity criteria were met at all study sites.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215056","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Olson, S.A., and Simeone, C.E., 2021, Hydraulic modeling at selected dam-removal and culvert-retrofit sites in the northeastern United States: U.S. Geological Survey Scientific Investigations Report 2021–5056, 37 p., https://doi.org/10.3133/sir20215056.","productDescription":"Report: vi, 37 p.; Data Release","numberOfPages":"37","onlineOnly":"Y","ipdsId":"IP-120501","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":387017,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LWIWVO","text":"USGS data 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-71.15295410156249,\n              41.82045509614034\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ nweng@usgs.gov\" data-mce-href=\"mailto:dc_ nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Development of Hydraulic Models</li><li>Model Execution</li><li>Model Results</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2021-07-08","noUsgsAuthors":false,"publicationDate":"2021-07-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Olson, Scott A. 0000-0002-1064-2125 solson@usgs.gov","orcid":"https://orcid.org/0000-0002-1064-2125","contributorId":2059,"corporation":false,"usgs":true,"family":"Olson","given":"Scott","email":"solson@usgs.gov","middleInitial":"A.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simeone, Caelan E. 0000-0003-3263-6452 csimeone@usgs.gov","orcid":"https://orcid.org/0000-0003-3263-6452","contributorId":221126,"corporation":false,"usgs":true,"family":"Simeone","given":"Caelan","email":"csimeone@usgs.gov","middleInitial":"E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818842,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70221785,"text":"ofr20211071 - 2021 - Preliminary assessment of the wave generating potential from landslides at Barry Arm, Prince William Sound, Alaska","interactions":[],"lastModifiedDate":"2021-07-09T11:40:56.783498","indexId":"ofr20211071","displayToPublicDate":"2021-07-08T11:50:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1071","displayTitle":"Preliminary Assessment of the Wave Generating Potential from Landslides at Barry Arm, Prince William Sound, Alaska","title":"Preliminary assessment of the wave generating potential from landslides at Barry Arm, Prince William Sound, Alaska","docAbstract":"<p>We simulated the concurrent rapid motion of landslides on an unstable slope at Barry Arm, Alaska. Movement of landslides into the adjacent fjord displaced fjord water and generated a tsunami, which propagated out of Barry Arm. Rather than assuming an initial sea surface height, velocity, and location for the tsunami, we generated the tsunami directly using a model capable of simulating the dynamics of both water and landslide material. The fjord below most of the landslide source area was occupied by the Barry Glacier until about 2012; therefore, our direct simulation of tsunami generation by landslide motion required new topographic and bathymetric data, which was collected in 2020. The topographic data also constrained landslide geometries and volumes. We considered four scenarios based on two landslide volumes and two landslide mobilities—a more mobile, contractive landslide and a less mobile, noncontractive landslide. The larger of the two volumes is 689 × 10<sup>6</sup> cubic meters (m<sup>3</sup>)—larger than the volume estimate in a previous study—and reflects the largest plausible volume given current observational data. The considered scenario that generated the largest wave heights resulted in forecast wave heights of over 200 meters (m) in the northern part of Barry Arm, adjacent to the landslide source area and runup on the opposite fjord wall in excess of 500 m. Simulated wave heights in excess of 5 m in southern Barry Arm and in Harriman Fjord occurred within 10–15 minutes (min) of landslide motion. The simulated tsunami reached Whittier, Alaska, approximately 20 min after initial rapid landslide motion, with peak heights of just over 2 m in Passage Fjord, 500 m offshore Whittier, occurring 26 min after initial rapid motion. Time of peak wave heights was consistent with previous modeling. Although results are preliminary and can be refined with additional observations and analyses, they provide a refined assessment of the upper bound of the hazard presented by the Barry Arm landslides. The results herein support the National Oceanic and Atmospheric Administration’s National Tsunami Warning Center mission to detect, forecast, and warn for tsunamis in Alaska.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211071","usgsCitation":"Barnhart, K.R., Jones, R.P., George, D.L., Coe, J.A., and Staley, D.M., 2021, Preliminary assessment of the wave generating potential from landslides at Barry Arm, Prince William Sound, Alaska: U.S. Geological Survey Open-File Report 2021–1071, 28 p., https://doi.org/10.3133/ofr20211071.","productDescription":"Report: v, 28 p.; Data Release","ipdsId":"IP-130004","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":386958,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XVJDNP","text":"USGS data release","linkHelpText":"Select model results from simulations of hypothetical rapid failures of landslides into Barry Arm Fjord, Prince William Sound, Alaska"},{"id":386957,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1071/ofr20211071.pdf","text":"Report","size":"13.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1071"},{"id":386956,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1071/coverthb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Barry Arm, Prince William Sound","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -148.90869140625,\n              60.77659627851085\n            ],\n            [\n              -147.95562744140625,\n              60.77659627851085\n            ],\n            [\n              -147.95562744140625,\n              61.18165309177166\n            ],\n            [\n              -148.90869140625,\n              61.18165309177166\n            ],\n            [\n              -148.90869140625,\n              60.77659627851085\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director,&nbsp;<a href=\"https://www.usgs.gov/centers/geohazards/\" data-mce-href=\"https://www.usgs.gov/centers/geohazards/\">Geologic Hazards Science Center</a><br>U.S. Geological Survey<br>Box 25046, Mail Stop 966<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction and Scope</li><li>Model Description</li><li>Data and Data Processing</li><li>Landslide Source Characteristics and Scenario Design</li><li>Model Implementation</li><li>Results</li><li>Discussion</li><li>Conclusions</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishedDate":"2021-07-08","noUsgsAuthors":false,"publicationDate":"2021-07-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnhart, Katherine R. 0000-0001-5682-455X","orcid":"https://orcid.org/0000-0001-5682-455X","contributorId":257870,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":818697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Ryan P. 0000-0001-6363-7592","orcid":"https://orcid.org/0000-0001-6363-7592","contributorId":260774,"corporation":false,"usgs":true,"family":"Jones","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":818698,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":818699,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":818700,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":818701,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70227450,"text":"70227450 - 2021 - Potential effect of low-rise, downcast artificial lights on nocturnally migrating land birds","interactions":[],"lastModifiedDate":"2022-01-17T15:11:05.21635","indexId":"70227450","displayToPublicDate":"2021-07-08T09:04:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2010,"text":"Integrative and Comparative Biology","active":true,"publicationSubtype":{"id":10}},"title":"Potential effect of low-rise, downcast artificial lights on nocturnally migrating land birds","docAbstract":"Artificial light at night (ALAN) on tall or upward-pointed lighting installations affects the flight behavior of night-migrating birds. We hypothesized that common low-rise lights pointing downward also affect the movement of nocturnal migrants. We predicted that birds in flight will react close to low-rise lights, and be attracted and grounded near light sources, with a stronger effect on juveniles during their autumn migration. We conducted a controlled longitudinal experiment with light-emitting diode floodlights and considered nearby structures that turn on lights at night. We analyzed 1501 high-resolution 3D nocturnal flight paths of free-flying migrants and diurnally captured 758–2009 birds around experimental lights during spring and autumn 2016, and spring 2017. We identified change points along flight paths where birds turned horizontally or vertically, and we considered these indicative of reactions. Flight paths with and without reactions were generally closer to our experimental site in spring than in autumn when the lights were on. Reactions were up to 40% more likely to occur in autumn than in spring depending on the threshold magnitude of turning angle. Reactions in spring were up to ∼60% more likely to occur at ∼35 m from the lights than at >1.5 km. In autumn, some vertical reactions were ∼40% more likely to occur at ∼50 m from the lights than at >2.2 km. Interactions between distance to lights and visibility or cloud cover were consistent with known effects of ALAN on nocturnal migrants. Under poor visibility, reactions were up to 50% more likely to occur farthest from structures in spring, but up to 60% more likely to occur closest to lights in autumn. Thus, the effects of ALAN on night-migrating land birds are not limited to bright lights pointing upward or lights on tall structures in urban areas. Diurnal capture rates of birds were not different when lights were on or off for either season. To our knowledge, this is the first study to show that low-rise lights pointing downward affect night-migrating birds. Although the interpreted reactions constitute subtle modifications in the linearity of flight paths, we discuss future work that could verify whether the protection of nocturnal migrants with lights-out programs would have greater impact if implemented beyond urban areas and include management of low-rise lights.","language":"English","publisher":"Oxford University Press","doi":"10.1093/icb/icab154","usgsCitation":"Cabrera-Cruz, S.A., Larkin, R.P., Gimpel, M.E., Gruber, J., Zenzal, T.J., and Buler, J.J., 2021, Potential effect of low-rise, downcast artificial lights on nocturnally migrating land birds: Integrative and Comparative Biology, v. 61, no. 3, p. 1216-1236, https://doi.org/10.1093/icb/icab154.","productDescription":"21 p.","startPage":"1216","endPage":"1236","ipdsId":"IP-127198","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":451580,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/icb/icab154","text":"Publisher Index Page"},{"id":394434,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-07-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Cabrera-Cruz, Sergio A.","contributorId":271139,"corporation":false,"usgs":false,"family":"Cabrera-Cruz","given":"Sergio","email":"","middleInitial":"A.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":830948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larkin, Ronald P.","contributorId":187419,"corporation":false,"usgs":false,"family":"Larkin","given":"Ronald","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":830949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gimpel, Maren E.","contributorId":271140,"corporation":false,"usgs":false,"family":"Gimpel","given":"Maren","email":"","middleInitial":"E.","affiliations":[{"id":56299,"text":"Washington College","active":true,"usgs":false}],"preferred":false,"id":830950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gruber, James G.","contributorId":271141,"corporation":false,"usgs":false,"family":"Gruber","given":"James G.","affiliations":[{"id":56299,"text":"Washington College","active":true,"usgs":false}],"preferred":false,"id":830951,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zenzal, Theodore J. Jr. 0000-0001-7342-1373","orcid":"https://orcid.org/0000-0001-7342-1373","contributorId":224399,"corporation":false,"usgs":true,"family":"Zenzal","given":"Theodore","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":830952,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Buler, Jeffrey J.","contributorId":194648,"corporation":false,"usgs":false,"family":"Buler","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":830953,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70222548,"text":"70222548 - 2021 - Investigation of scale-dependent groundwater/surface-water exchange in rivers by gradient self-potential logging: Numerical modeling and field experiments","interactions":[],"lastModifiedDate":"2021-08-04T12:10:45.87688","indexId":"70222548","displayToPublicDate":"2021-07-08T07:06:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9128,"text":"Journal of Environmental and Engineering Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Investigation of scale-dependent groundwater/surface-water exchange in rivers by gradient self-potential logging: Numerical modeling and field experiments","docAbstract":"<p><span>Exchanges of groundwater and surface-water are fundamental to a wide range of water-supply and water-quality management issues but challenging to map beyond the reach scale. Waterborne gradient self-potential (SP) measurements are directly sensitive to water flow through riverbed sediments and can be used to infer exchange locations, direction (gain versus loss), scale, and relative changes, but to date applications to river corridor hydrology are limited. Numerical modeling and field experiments were therefore performed herein, each emphasizing waterborne gradient SP logging for identifying and locating focused vertical groundwater discharge (surface-water gain) and recharge (surface-water loss) in a river. Two and three-dimensional numerical models were constructed to simulate the polarities, appearances, and peak amplitudes of streaming-potential and electric-field anomalies on a riverbed and in the surface-water that were attributable to steady-state vertical fluxes of groundwater through high-permeability conduits in the riverbed. Effects of varied hydraulic length-scale of exchange and surface-water depth were tested through numerical modeling. Modeling results aided in data acquisition and interpretation for three repeated field experiments performed along a 1.5–2.0 km reach of the Quashnet River in Cape Cod, Massachusetts, where focused, meter-scale groundwater discharges occur at discrete locations within otherwise ubiquitous and more diffuse groundwater upwelling conditions. Strong gradient SP anomalies were repeatedly measured in the Quashnet River at previously confirmed locations of focused groundwater discharge, showing the efficacy of waterborne gradient SP logging in identifying and characterizing groundwater/surface water exchange dynamics at multiple river network scales.</span></p>","language":"English","publisher":"EEGS","doi":"10.32389/JEEG20-066","usgsCitation":"Ikard, S., Briggs, M., and Lane, J.W., 2021, Investigation of scale-dependent groundwater/surface-water exchange in rivers by gradient self-potential logging: Numerical modeling and field experiments: Journal of Environmental and Engineering Geophysics, v. 26, no. 2, 181 p., https://doi.org/10.32389/JEEG20-066.","productDescription":"181 p.","ipdsId":"IP-126186","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":387675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Massachusetts","otherGeospatial":"Quashnet River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.51935195922852,\n              41.57115075028995\n            ],\n            [\n              -70.5057907104492,\n              41.57115075028995\n            ],\n            [\n              -70.5057907104492,\n              41.59400643013302\n            ],\n            [\n              -70.51935195922852,\n              41.59400643013302\n            ],\n            [\n              -70.51935195922852,\n              41.57115075028995\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"26","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ikard, Scott 0000-0002-8304-4935","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":201775,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":820533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":820534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lane, John W. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":219742,"corporation":false,"usgs":true,"family":"Lane","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":820535,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70222423,"text":"70222423 - 2021 - Distributed memory parallel groundwater modeling for the Netherlands Hydrological Instrument","interactions":[],"lastModifiedDate":"2021-07-28T12:01:05.400154","indexId":"70222423","displayToPublicDate":"2021-07-08T06:56:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9115,"text":"Environmental Software & Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Distributed memory parallel groundwater modeling for the Netherlands Hydrological Instrument","docAbstract":"<p><span>Worldwide, billions of people rely on fresh groundwater reserves for their domestic, agricultural and industrial water use. Extreme droughts and excessive groundwater pumping put pressure on water authorities in maintaining sustainable water usage. High-resolution integrated models are valuable assets in supporting them. The Netherlands Hydrological Instrument (NHI) provides the Dutch water authorities with open source modeling software and data. However, NHI integrated&nbsp;</span>groundwater models<span>&nbsp;often require long run times and large memory usage, therefore strongly limiting their application. As a solution, we present a distributed memory&nbsp;parallelization, focusing on the National Hydrological Model. Depending on the level of integration, we show that significant speedups can be obtained up to two orders of magnitude. As far as we know, this is the first reported integrated groundwater parallelization of an operational hydrological model used for national-scale&nbsp;integrated water management&nbsp;and policy making. The parallel model code and data are freely available.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2021.105092","usgsCitation":"Verkaik, J., Hughes, J.D., Walsum, V., Oude Essink, G., Lin, H., and Bierkens, M., 2021, Distributed memory parallel groundwater modeling for the Netherlands Hydrological Instrument: Environmental Software & Modelling, v. 143, 105092, 15 p., https://doi.org/10.1016/j.envsoft.2021.105092.","productDescription":"105092, 15 p.","ipdsId":"IP-129864","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":451594,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2021.105092","text":"Publisher Index Page"},{"id":387499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"143","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Verkaik, Jarno 0000-0001-7420-8304","orcid":"https://orcid.org/0000-0001-7420-8304","contributorId":261418,"corporation":false,"usgs":false,"family":"Verkaik","given":"Jarno","email":"","affiliations":[{"id":52847,"text":"Deltares and Utrecht University","active":true,"usgs":false}],"preferred":false,"id":819993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":819994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsum, van","contributorId":261419,"corporation":false,"usgs":false,"family":"Walsum","given":"van","email":"","affiliations":[{"id":52848,"text":"Wageningen Environmental Research","active":true,"usgs":false}],"preferred":false,"id":819995,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oude Essink, G.H.P. 0000-0003-0931-6944","orcid":"https://orcid.org/0000-0003-0931-6944","contributorId":261420,"corporation":false,"usgs":false,"family":"Oude Essink","given":"G.H.P.","email":"","affiliations":[{"id":52847,"text":"Deltares and Utrecht University","active":true,"usgs":false}],"preferred":false,"id":819996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lin, H.X.","contributorId":261421,"corporation":false,"usgs":false,"family":"Lin","given":"H.X.","email":"","affiliations":[{"id":52849,"text":"Delft Institute of Applied Mathematics and Leiden University","active":true,"usgs":false}],"preferred":false,"id":819997,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bierkens, M.F.P. 0000-0002-7411-6562","orcid":"https://orcid.org/0000-0002-7411-6562","contributorId":261422,"corporation":false,"usgs":false,"family":"Bierkens","given":"M.F.P.","affiliations":[{"id":52850,"text":"Utrecht University and Deltares","active":true,"usgs":false}],"preferred":false,"id":819998,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70240119,"text":"70240119 - 2021 - Factors influencing distributional shifts and abundance at the range core of a climate-sensitive mammal","interactions":[],"lastModifiedDate":"2023-01-27T12:56:42.509076","indexId":"70240119","displayToPublicDate":"2021-07-08T06:54:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing distributional shifts and abundance at the range core of a climate-sensitive mammal","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Species are frequently responding to contemporary climate change by shifting to higher elevations and poleward to track suitable climate space. However, depending on local conditions and species’ sensitivity, the nature of these shifts can be highly variable and difficult to predict. Here, we examine how the American pika (<i>Ochotona princeps</i>), a philopatric, montane lagomorph, responds to climatic gradients at three spatial scales. Using mixed-effects modeling in an information-theoretic approach, we evaluated a priori model suites regarding predictors of site occupancy, relative abundance, and elevational-range retraction across 760 talus patches, nested within 64 watersheds across the Northern Rocky Mountains of North America, during 2017–2020. The top environmental predictors differed across these response metrics. Warmer temperatures in summer and winter were associated with lower occupancy, lower relative abundances, and greater elevational retraction across watersheds. Occupancy was also strongly influenced by habitat patch size, but only when combined with climate metrics such as actual evapotranspiration. Using a second analytical approach, acute heat stress and summer precipitation best explained retraction residuals (i.e., the relative extent of retraction given the original elevational range of occupancy). Despite the study domain occurring near the species’ geographic-range center, where populations might have higher abundances and be at lower risk of climate-related stress, 33.9% of patches showed evidence of recent extirpations. Pika-extirpated sites averaged 1.44℃ warmer in summer than did occupied sites. Additionally, the minimum elevation of pika occupancy has retracted upslope in 69% of watersheds (mean: 281&nbsp;m). Our results emphasize the nuance associated with evaluating species’ range dynamics in response to climate gradients, variability, and temperature exceedances, especially in regions where species occupy gradients of conditions that may constitute multiple range edges. Furthermore, this study highlights the importance of evaluating diverse drivers across response metrics to improve the predictive accuracy of widely used, correlative models.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15793","usgsCitation":"Billman, P., Beever, E.A., McWethy, D.B., Thurman, L., and Wilson, K.C., 2021, Factors influencing distributional shifts and abundance at the range core of a climate-sensitive mammal: Global Change Biology, v. 27, no. 19, p. 4498-4515, https://doi.org/10.1111/gcb.15793.","productDescription":"18 p.","startPage":"4498","endPage":"4515","ipdsId":"IP-123267","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":451597,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.15793","text":"Publisher Index Page"},{"id":412400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -115.96912848281637,\n              47.81775925984073\n            ],\n            [\n              -115.96912848281637,\n              43.011789546894505\n            ],\n            [\n              -111.0932694765071,\n              43.011789546894505\n            ],\n            [\n              -111.0932694765071,\n              47.81775925984073\n            ],\n            [\n              -115.96912848281637,\n              47.81775925984073\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"27","issue":"19","noUsgsAuthors":false,"publicationDate":"2021-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Billman, Peter D","contributorId":301821,"corporation":false,"usgs":false,"family":"Billman","given":"Peter D","affiliations":[{"id":65350,"text":"Dept. of Earth Sciences, Montana State University","active":true,"usgs":false}],"preferred":false,"id":862646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beever, Erik A. 0000-0002-9369-486X ebeever@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-486X","contributorId":2934,"corporation":false,"usgs":true,"family":"Beever","given":"Erik","email":"ebeever@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":862647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McWethy, Dave B.","contributorId":301822,"corporation":false,"usgs":false,"family":"McWethy","given":"Dave","email":"","middleInitial":"B.","affiliations":[{"id":65350,"text":"Dept. of Earth Sciences, Montana State University","active":true,"usgs":false}],"preferred":false,"id":862648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurman, Lindsey 0000-0003-3142-4909","orcid":"https://orcid.org/0000-0003-3142-4909","contributorId":269425,"corporation":false,"usgs":true,"family":"Thurman","given":"Lindsey","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Kenny C","contributorId":301823,"corporation":false,"usgs":false,"family":"Wilson","given":"Kenny","email":"","middleInitial":"C","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":862650,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70263693,"text":"70263693 - 2021 - Robust earthquake early warning at a fraction of the cost: ASTUTI Costa Rica","interactions":[],"lastModifiedDate":"2025-02-20T15:44:13.799057","indexId":"70263693","displayToPublicDate":"2021-07-08T00:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7751,"text":"AGU Advances","active":true,"publicationSubtype":{"id":10}},"title":"Robust earthquake early warning at a fraction of the cost: ASTUTI Costa Rica","docAbstract":"<p><span>We show that a fixed smartphone network can provide robust Earthquake Early Warning for at least two orders of magnitude less cost than scientific-grade networks. Our software and cloud-based data architecture that we have constructed for the Alerta Sismica Temprana Utilizando Teléfonos Inteligentes (ASTUTI; Earthquake Early Warning Utilizing Smartphones) network in Costa Rica is easily scaled and exported. Implementation comprises provisioning and installing modern smartphones in judicious locations. Stand-up time for regionally operational networks can be on the order of days. We evaluated a non-parametric ground-motion detection and alerting strategy that would alert the entire Costa Rican population of any event with a ground motion detection threshold of 0.55–0.65 %g at four neighboring stations. During a 6-month evaluation period ASTUTI detected and alerted on five of 13 earthquakes with M</span><sub>w</sub><span>&nbsp;4.8–5.3 that caused felt Modified Mercalli Intensity shaking levels of 4.3–6. The system did not produce any false alerts and the undetected events did not produce wide-spread or significant felt shaking. System latencies were less than or similar to scientific-grade latencies. Alerts for all five detected events would have reached the capital city, San Jose, before strong&nbsp;</span><i>S</i><span>-wave shaking. This would have afforded time for Drop Cover Hold On actions by most residents. Two of the five alerts were triggered by&nbsp;</span><i>P</i><span>-waves suggesting that smartphone-based networks could approach the fastest theoretical EEW performance, especially with future expected improvements in smartphone sensors and processing algorithms.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021AV000407","usgsCitation":"Brooks, B.A., Protti, M., Ericksen, T., Bunn, J., Vega, F., Cochran, E.S., Duncan, C., Avery, J., Minson, S.E., Chaves, E.J., Baez, J., Foster, J.H., and Glennie, C.L., 2021, Robust earthquake early warning at a fraction of the cost: ASTUTI Costa Rica: AGU Advances, v. 2, no. 3, e2021AV000407, 16 p., https://doi.org/10.1029/2021AV000407.","productDescription":"e2021AV000407, 16 p.","ipdsId":"IP-126171","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":489863,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021av000407","text":"Publisher Index Page"},{"id":482273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Costa Rica","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-82.96578,8.22503],[-83.50844,8.44693],[-83.71147,8.65684],[-83.59631,8.83044],[-83.63264,9.05139],[-83.90989,9.2908],[-84.3034,9.48735],[-84.64764,9.61554],[-84.71335,9.90805],[-84.97566,10.08672],[-84.91137,9.79599],[-85.11092,9.55704],[-85.33949,9.83454],[-85.66079,9.93335],[-85.79744,10.13489],[-85.79171,10.43934],[-85.65931,10.75433],[-85.94173,10.89528],[-85.71254,11.08844],[-85.56185,11.21712],[-84.903,10.9523],[-84.67307,11.08266],[-84.35593,10.99923],[-84.19018,10.79345],[-83.89505,10.72684],[-83.65561,10.93876],[-83.40232,10.39544],[-83.01568,9.99298],[-82.5462,9.56613],[-82.93289,9.47681],[-82.92715,9.07433],[-82.71918,8.92571],[-82.86866,8.80727],[-82.82977,8.6263],[-82.91318,8.42352],[-82.96578,8.22503]]]},\"properties\":{\"name\":\"Costa Rica\"}}]}","volume":"2","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-07-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Brooks, Benjamin A. 0000-0001-7954-6281 bbrooks@usgs.gov","orcid":"https://orcid.org/0000-0001-7954-6281","contributorId":5237,"corporation":false,"usgs":true,"family":"Brooks","given":"Benjamin","email":"bbrooks@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Protti, Marino","contributorId":351073,"corporation":false,"usgs":false,"family":"Protti","given":"Marino","affiliations":[{"id":34121,"text":"Observatorio Vulcanologico y Sismologico de Costa Rica","active":true,"usgs":false}],"preferred":false,"id":927849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ericksen, Todd 0000-0001-9340-575X","orcid":"https://orcid.org/0000-0001-9340-575X","contributorId":217363,"corporation":false,"usgs":true,"family":"Ericksen","given":"Todd","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927850,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bunn, Julian","contributorId":216379,"corporation":false,"usgs":false,"family":"Bunn","given":"Julian","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":927851,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vega, Floribeth","contributorId":351075,"corporation":false,"usgs":false,"family":"Vega","given":"Floribeth","affiliations":[{"id":34121,"text":"Observatorio Vulcanologico y Sismologico de Costa Rica","active":true,"usgs":false}],"preferred":false,"id":927852,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927853,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Duncan, Chris","contributorId":351077,"corporation":false,"usgs":false,"family":"Duncan","given":"Chris","affiliations":[{"id":83911,"text":"GISMatters","active":true,"usgs":false}],"preferred":false,"id":927854,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Avery, Jonathan","contributorId":244557,"corporation":false,"usgs":false,"family":"Avery","given":"Jonathan","email":"","affiliations":[{"id":48939,"text":"Hawaii Institute of Geophysics and Planetology, University of Hawaii at Manoa, HI, USA","active":true,"usgs":false}],"preferred":false,"id":927855,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927856,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Chaves, Esteban J.","contributorId":236655,"corporation":false,"usgs":false,"family":"Chaves","given":"Esteban","email":"","middleInitial":"J.","affiliations":[{"id":47499,"text":"Volcanological and Seismological Observatory of Costa Rica at Universidad Nacional (OVSICORI-UNA)","active":true,"usgs":false}],"preferred":false,"id":927999,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Baez, Juan Carlos","contributorId":351079,"corporation":false,"usgs":false,"family":"Baez","given":"Juan Carlos","affiliations":[{"id":83913,"text":"Centro Sismologico Nacional de Chile","active":true,"usgs":false}],"preferred":false,"id":927857,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Foster, James H.","contributorId":244553,"corporation":false,"usgs":false,"family":"Foster","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":48939,"text":"Hawaii Institute of Geophysics and Planetology, University of Hawaii at Manoa, HI, USA","active":true,"usgs":false}],"preferred":false,"id":927858,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Glennie, Craig L.","contributorId":198143,"corporation":false,"usgs":false,"family":"Glennie","given":"Craig","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":927859,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70228931,"text":"70228931 - 2021 - Juvenile moose stress and nutrition dynamics related to winter ticks, landscape characteristics, climate-mediated factors and survival","interactions":[],"lastModifiedDate":"2022-02-24T17:14:48.527888","indexId":"70228931","displayToPublicDate":"2021-07-07T11:08:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3919,"text":"Conservation Physiology","onlineIssn":"2051-1434","active":true,"publicationSubtype":{"id":10}},"title":"Juvenile moose stress and nutrition dynamics related to winter ticks, landscape characteristics, climate-mediated factors and survival","docAbstract":"<p><span>Moose populations in the northeastern United States have declined over the past 15&nbsp;years, primarily due to the impacts of winter ticks. Research efforts have focused on the effects of winter tick infestation on moose survival and reproduction, but stress and nutritional responses to ticks and other stressors remain understudied. We examined the influence of several environmental factors on moose calf stress hormone metabolite concentrations and nutritional restriction in Vermont, USA. We collected 407 fecal and 461 snow urine samples from 84 radio-collared moose calves in the winters of 2017–2019 (January–April) to measure fecal glucocorticoid metabolites (fGCM) concentrations and urea nitrogen:creatinine (UN:C) ratios. We used generalized mixed-effects models to evaluate the influence of individual condition, winter ticks, habitat, climate and human development on stress and nutrition in calf moose. We then used these physiological data to build generalized linear models to predict calf winter survival. Calf fGCM concentrations increased with nutritional restriction and snow depth during adult winter tick engorgement. Calf UN:C ratios increased in calves with lighter weights and higher tick loads in early winter. Calf UN:C ratios also increased in individuals with home ranges composed of little deciduous forests during adult winter tick engorgement. Our predictive models estimated that winter survival was negatively related to UN:C ratios and positively related to fGCM concentrations, particularly in early winter. By late March, as winter ticks are having their greatest toll and endogenous resources become depleted, we estimated a curvilinear relationship between fGCM concentrations and survival. Our results provide novel evidence linking moose calf stress and nutrition, a problematic parasite and challenging environment and winter survival. Our findings provide a baseline to support the development of non-invasive physiological monitoring for assessing environmental impacts on moose populations.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/conphys/coab048","usgsCitation":"Rosenblatt, E., Debow, J., Blouin, J., Donovan, T.M., Murdoch, J., Creel, S., Rogers, W., Gieder, K., Fortin, N., and Alexander, C., 2021, Juvenile moose stress and nutrition dynamics related to winter ticks, landscape characteristics, climate-mediated factors and survival: Conservation Physiology, v. 9, no. 1, coab048, 20 p., https://doi.org/10.1093/conphys/coab048.","productDescription":"coab048, 20 p.","ipdsId":"IP-123406","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":451599,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coab048","text":"Publisher Index Page"},{"id":396433,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.212890625,\n              43.6599240747891\n            ],\n            [\n              -71.7626953125,\n              43.6599240747891\n            ],\n            [\n              -71.7626953125,\n              44.98811302615805\n            ],\n            [\n              -73.212890625,\n              44.98811302615805\n            ],\n            [\n              -73.212890625,\n              43.6599240747891\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenblatt, Elias","contributorId":276324,"corporation":false,"usgs":false,"family":"Rosenblatt","given":"Elias","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":835945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Debow, Jacob","contributorId":276321,"corporation":false,"usgs":false,"family":"Debow","given":"Jacob","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":835946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blouin, Joshua","contributorId":276322,"corporation":false,"usgs":false,"family":"Blouin","given":"Joshua","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":835947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":835944,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murdoch, James","contributorId":276325,"corporation":false,"usgs":false,"family":"Murdoch","given":"James","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":835948,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Creel, 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Department","active":true,"usgs":false}],"preferred":false,"id":835952,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Alexander, Cedric","contributorId":280058,"corporation":false,"usgs":false,"family":"Alexander","given":"Cedric","email":"","affiliations":[{"id":27622,"text":"Vermont Fish and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":835953,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
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