{"pageNumber":"476","pageRowStart":"11875","pageSize":"25","recordCount":184569,"records":[{"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":"

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 \"urn:x-wiley:23335084:media:ess2899:ess2899-math-0001\"1,000 volts (a range of 2,000 volts)—comparable to the amplitudes of the geovoltages themselves.

","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":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics 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":"

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.

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.

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.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215031","collaboration":"DOE/ID-22252
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":"

Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520

","tableOfContents":"","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":"

CO2 and CH4 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 CO2 hydrate exhibits over an order of magnitude higher electrical conductivity (σ) than pure CH4 hydrate at geologically relevant temperatures. The conductivity was obtained from frequency-dependent impedance (Z) measurements made on polycrystalline CO2 hydrate (CO2·6.0 ± 0.2H2O by methods here) with 25% gas-filled porosity, compared with CH4 hydrate (CH4·5.9H2O) formed and measured in the same apparatus and exhibiting closely matching grain characteristics. The conductivity of CO2 hydrate is 6.5 × 10−4 S/m at 273K with an activation energy (Ea) of 46.5 kJ/mol at 260–281 K, compared with ∼5 × 10−5 S/m and 34.8 kJ/m for CH4 hydrate. Equivalent circuit modeling indicates that different pathways govern conduction in CO2 versus CH4 hydrate. Results show promise for use of electromagnetic methods in monitoring CO2 hydrate formation in certain natural settings or in CO2/CH4 exchange efforts.

","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":70229411,"text":"70229411 - 2021 - Introduced mangroves along the coast of Moloka‘i, Hawai‘i may represent novel habitats for megafaunal communities","interactions":[],"lastModifiedDate":"2022-03-07T12:17:20.037004","indexId":"70229411","displayToPublicDate":"2021-07-15T06:14:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2990,"text":"Pacific Science","active":true,"publicationSubtype":{"id":10}},"title":"Introduced mangroves along the coast of Moloka‘i, Hawai‘i may represent novel habitats for megafaunal communities","docAbstract":"

Mangrove forests are prevalent along tropical/subtropical coastlines and provide valuable ecosystem services including coastline stabilization, storm impact reduction, and enhanced coastal productivity. However, mangroves were absent from the Hawaiian Islands and their introduction to Moloka‘i in 1902 has provided an opportunity to examine their unique influence on coastal landscapes. Previous studies indicate an inability of native detritivores to utilize tannin-rich substrates, yielding poor cycling of mangrove-derived detritus in Hawaiian tidal zones. We hypothesize that in addition to altering detrital inputs, introduced mangroves facilitate the persistence of introduced species in the Hawaiian coastal zone by providing novel habitat for juvenile megafauna. To determine whether mangrove-dominated tidal zones harbor megafaunal assemblages distinct from open sandflats, we sampled in two mangrove (M1 and M2) and two adjacent sandflat (S1 and S2) sites along the southern coast of Moloka‘i, where the most mature mangrove forests occur in Hawai‘i. There were no statistical differences in total abundances between M1 and M2 or S1 and S2; therefore, results from individual deployments were pooled across the sites in order to conduct between-habitat (mangrove vs. sandflat) comparisons. Our mangrove study site had significantly higher abundances of megafauna, including several shrimp and crab species, compared to the sandflat site. The community composition within the mangrove site differed from the sandflat site, including higher abundances of non-native mangrove crabs (Scylla serrata), as well as native fish Bathygobius cocosensis and crustaceans (Thalamita crenata, Palaemon pacificus, P. debilis) than in the sandflat site, indicating that the mangrove site may provide niches for both invasive and native species. In addition, mean body length for several similar species was smaller in the mangrove site than in the sandflat site, suggesting that these mangroves may be providing a habitat for juvenile species. While our study was spatially limited to two mangrove and two adjacent sandflat sites, our results suggest that introduced mangroves in Moloka‘i may support small-bodied, native, and non-native megafauna, influencing coastal Hawaiian trophic dynamics. Our case study provides a baseline for megafaunal fish and invertebrate communities present prior to non-native mangrove removal as well as for monitoring potential community changes following expansion of mangrove habitats due to climate change.

","language":"English","publisher":"University of Hawai'i Press","usgsCitation":"Nakahara, B.A., Demopoulos, A., Rii, Y.M., Alegado, R.A., Fraiola, K., and Smith, C.R., 2021, Introduced mangroves along the coast of Moloka‘i, Hawai‘i may represent novel habitats for megafaunal communities: Pacific Science, v. 75, no. 2, p. 205-223.","productDescription":"19 p.","startPage":"205","endPage":"223","ipdsId":"IP-113945","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":396774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396768,"type":{"id":15,"text":"Index Page"},"url":"https://www.muse.jhu.edu/article/798100"}],"country":"United States","state":"Hawaii","otherGeospatial":"Coast of Moloka‘i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.35855102539062,\n 20.987085584914595\n ],\n [\n -156.68975830078125,\n 20.987085584914595\n ],\n [\n -156.68975830078125,\n 21.288094774609725\n ],\n [\n -157.35855102539062,\n 21.288094774609725\n ],\n [\n -157.35855102539062,\n 20.987085584914595\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nakahara, Bryan A.","contributorId":288059,"corporation":false,"usgs":false,"family":"Nakahara","given":"Bryan","email":"","middleInitial":"A.","affiliations":[{"id":61694,"text":"Hawaiian Electric Corporation","active":true,"usgs":false}],"preferred":false,"id":837312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":210508,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":837313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rii, Yoshimi M.","contributorId":288060,"corporation":false,"usgs":false,"family":"Rii","given":"Yoshimi","email":"","middleInitial":"M.","affiliations":[{"id":61695,"text":"Hawai'i Institute of Marine Biology, University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":837314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alegado, Rosanna A.","contributorId":288061,"corporation":false,"usgs":false,"family":"Alegado","given":"Rosanna","email":"","middleInitial":"A.","affiliations":[{"id":61696,"text":"Department of Oceanography, Sea Grant College Program, University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":837315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fraiola, Kauaoa","contributorId":288062,"corporation":false,"usgs":false,"family":"Fraiola","given":"Kauaoa","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":837316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Craig R.","contributorId":288063,"corporation":false,"usgs":false,"family":"Smith","given":"Craig","email":"","middleInitial":"R.","affiliations":[{"id":61698,"text":"Department of Oceanography, University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":837317,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70221916,"text":"ofr20211051 - 2021 - Groundwater and surface-water data from the C-aquifer monitoring program, Northeastern Arizona, 2012–2019","interactions":[],"lastModifiedDate":"2021-07-15T10:09:37.240431","indexId":"ofr20211051","displayToPublicDate":"2021-07-14T14:13:29","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":"2021-1051","displayTitle":"Groundwater and Surface-Water Data from the C-Aquifer Monitoring Program, Northeastern Arizona, 2012–2019","title":"Groundwater and surface-water data from the C-aquifer monitoring program, Northeastern Arizona, 2012–2019","docAbstract":"

The Coconino aquifer (C aquifer) is a regionally extensive multiple-aquifer system supplying water for municipal, agricultural, and industrial use in northeastern Arizona, northwestern New Mexico, and southeastern Utah. This report focuses on the C aquifer in the arid to semi-arid area between St. Johns, Ariz., and Flagstaff, Ariz., along the Interstate-40 corridor where an increase in groundwater withdrawals coupled with ongoing drought conditions increase the potential for substantial water-level decline within the aquifer.

The U.S. Geological Survey (USGS) C-aquifer Monitoring Program began in 2005 to establish baseline groundwater and surface-water conditions and to quantify physical and water-chemistry responses to pumping stresses and climate. This report presents data previously reported in Brown and Macy (2012) that extend back as far as the 1950s, along with new data collected from the USGS C-aquifer Monitoring Program since that publication, from water years 2012 to 2019.

Water levels in 17 wells are measured quarterly as part of the C-aquifer Monitoring Program, and five of those are continuously monitored at 15-minute intervals. Water levels in an additional 18 wells in the study area are measured periodically by the USGS or other agencies. The largest historical change in water level in the study area was a decrease of 81.20 feet in Lake Mary 1 Well near Flagstaff between 1962 and 2018. Changes in water levels were greatest around major pumping centers and in the eastern extent of the study area.

Surface-water water-quality parameters (pH, water temperature, specific conductance, and dissolved oxygen) and streamflow discharge measurements were collected and analyzed along perennial, groundwater-fed reaches of Clear Creek, Chevelon Creek, and the Little Colorado River during nine baseflow investigations of varying extent between 2005 and 2019. Both Clear Creek and Chevelon Creek gain in flow from the beginning of their perennial reaches to their outflow into the Little Colorado River. The Little Colorado River has relatively steady streamflow in the reach between where the two tributaries enter the river. Chevelon Creek showed an increase in median specific conductance during all baseflow investigations of nearly 4,000 microsiemens per centimeter (μS/cm) from near the headwaters to the confluence with the Little Colorado River; Clear Creek also showed an increase in median specific conductance of almost 5,000 μS/cm from headwaters to confluence. Water temperature, dissolved oxygen, and pH do not show substantial trends along the reaches of Clear Creek, Chevelon Creek, or the Little Colorado River.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211051","collaboration":"Prepared in cooperation with the Navajo Nation and the City of Flagstaff","usgsCitation":"Jones, C.J.R., and Robinson, M.J., 2021, Groundwater and surface-water data from the C-aquifer monitoring program, Northeastern Arizona, 2012–2019: U.S. Geological Survey Open-File Report 2021–1051, 34 p., https://doi.org/10.3133/ofr20211051.","productDescription":"vi, 34 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-115787","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":387185,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20121196","text":"Open-File Report 2012-1196","linkHelpText":"- Groundwater, Surface-Water, and Water-Chemistry Data from C-aquifer Monitoring Program, Northeastern Arizona, 2005-11"},{"id":387177,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1051/covrthb.jpg"},{"id":387178,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1051/ofr20211051.pdf","text":"Report","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.829833984375,\n 34.27083595165\n ],\n [\n -109.149169921875,\n 34.27083595165\n ],\n [\n -109.149169921875,\n 36.146746777814364\n ],\n [\n -111.829833984375,\n 36.146746777814364\n ],\n [\n -111.829833984375,\n 34.27083595165\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2021-07-14","noUsgsAuthors":false,"publicationDate":"2021-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Casey J.R. 0000-0002-6991-8026","orcid":"https://orcid.org/0000-0002-6991-8026","contributorId":223364,"corporation":false,"usgs":true,"family":"Jones","given":"Casey","email":"","middleInitial":"J.R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819293,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Michael J. 0000-0003-3855-3914","orcid":"https://orcid.org/0000-0003-3855-3914","contributorId":240588,"corporation":false,"usgs":true,"family":"Robinson","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819294,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"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":"

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 (Somateria fischeri), 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.

","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":70237744,"text":"70237744 - 2021 - Event scale relationships of DOC and TDN fluxes in throughfall and stemflow diverge from stream exports in a forested catchment","interactions":[],"lastModifiedDate":"2023-08-03T21:28:06.924605","indexId":"70237744","displayToPublicDate":"2021-07-14T08:53:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Event scale relationships of DOC and TDN fluxes in throughfall and stemflow diverge from stream exports in a forested catchment","docAbstract":"

Aquatic fluxes of carbon and nutrients link terrestrial and aquatic ecosystems. Within forests, storm events drive both the delivery of carbon and nitrogen to the forest floor and the export of these solutes from the land via streams. To increase understanding of the relationships between hydrologic event character and the relative fluxes of carbon and nitrogen in throughfall, stemflow and streams, we measured dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) concentrations in each flow path for 23 events in a forested watershed in Vermont, USA. DOC and TDN concentrations increased with streamflow, indicating their export was limited by water transport of catchment stores. DOC and TDN concentrations in throughfall and stemflow decreased exponentially with increasing precipitation, suggesting that precipitation removed a portion of available sources from tree surfaces during the events. DOC and TDN fluxes were estimated for 76 events across a 2-year period. For most events, throughfall and stemflow fluxes greatly exceeded stream fluxes, but the imbalance narrowed for larger storms (>30 mm). The largest 10 stream events exported 40% of all stream event DOC whereas those same 10 events contributed 14% of all throughfall export. Approximately 2–5 times more DOC and TDN was exported from trees during rain events than left the catchment via streams annually. The diverging influence of event size on tree versus stream fluxes has important implications for forested ecosystems as hydrological events increase in intensity and frequency due to climate change.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JG006281","usgsCitation":"Ryan, K.A., Adler, T., Chalmers, A.T., Perdrial, J., Shanley, J.B., and Stubbins, A., 2021, Event scale relationships of DOC and TDN fluxes in throughfall and stemflow diverge from stream exports in a forested catchment: Journal of Geophysical Research: Biogeosciences, v. 126, no. 7, e2021JG006281, 23 p., https://doi.org/10.1029/2021JG006281.","productDescription":"e2021JG006281, 23 p.","ipdsId":"IP-128922","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":436273,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OCS8P7","text":"USGS data release","linkHelpText":"Storm Event Dissolved Organic Carbon and Total Dissolved Nitrogen Concentrations and Yields for Precipitation, Throughfall, Stemflow, and Stream Water and Hourly Streamflow and Precipitation Record for the W-9 Catchment, Sleepers River Research Watershed, 2017 and 2018 (ver. 2.0, September 2022)"},{"id":408603,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Sleepers River Research Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.32144973179821,\n 44.56971018097872\n ],\n [\n -72.32144973179821,\n 44.37610677503369\n ],\n [\n -72.000598189831,\n 44.37610677503369\n ],\n [\n -72.000598189831,\n 44.56971018097872\n ],\n [\n -72.32144973179821,\n 44.56971018097872\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"126","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Ryan, Kevin A.","contributorId":298331,"corporation":false,"usgs":false,"family":"Ryan","given":"Kevin","email":"","middleInitial":"A.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":855421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adler, Thomas","contributorId":244156,"corporation":false,"usgs":false,"family":"Adler","given":"Thomas","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":855422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chalmers, Ann T. 0000-0002-5199-8080","orcid":"https://orcid.org/0000-0002-5199-8080","contributorId":217381,"corporation":false,"usgs":true,"family":"Chalmers","given":"Ann","email":"","middleInitial":"T.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":855423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perdrial, Julia","contributorId":190445,"corporation":false,"usgs":false,"family":"Perdrial","given":"Julia","affiliations":[],"preferred":false,"id":855424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":855425,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stubbins, Aron","contributorId":191244,"corporation":false,"usgs":false,"family":"Stubbins","given":"Aron","email":"","affiliations":[],"preferred":false,"id":855426,"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":"

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: Lophelia pertusa, Paragorgia johnsoni, Montastraea cavernosa, Porites astreoides, and Stephanocoenia intersepta. 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.

","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":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818656,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70222456,"text":"70222456 - 2021 - Long-term year-round observations of magmatic CO2 emissions on Mammoth Mountain, California, USA","interactions":[],"lastModifiedDate":"2021-07-30T13:39:50.498578","indexId":"70222456","displayToPublicDate":"2021-07-14T08:37:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Long-term year-round observations of magmatic CO2 emissions on Mammoth Mountain, California, USA","docAbstract":"

Diffuse emission of magmatic CO2 is one of the main indicators of volcanic unrest at Mammoth Mountain, but the presence of deep seasonal snowpack at the site has hindered year-round CO2 flux observations. A permanent eddy covariance station was established at the largest area of diffuse CO2 degassing on Mammoth Mountain (Horseshoe Lake tree kill) that measured CO2 fluxes (Fc) and meteorological parameters on a half-hourly basis. From July 22, 2014 to May 24, 2020, Fc ranged from −35 to 10,546 g m−2 d−1. Fc decreased on average by 53% over the study period, tracking the long-term decline in CO2 emissions following the last major increase that occurred at the Horseshoe Lake tree kill area from 2009 to 2011. Statistical and spectral analyses were applied to the Fc and ancillary meteorological parameter time series to understand (1) relationships between these parameters, (2) their dominant periodicities, and (3) changes in Fc that may be unexplained by meteorological forcing. Variations in detrended Fc (Fcdt) were most strongly correlated with wind direction and atmospheric temperature, followed by atmospheric pressure on diurnal to annual time scales, but wind direction likely exerted the most direct control on Fcdt. Comparison of the smoothed (180-d span) Fcdt time series to the time series of average-daily snow water equivalent measured ~1 km away suggested that snowpack may have suppressed CO2 emissions. No evidence of a change in CO2 emissions related to the last major seismic swarm beneath Mammoth Mountain on February 2–18, 2014 was observed.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107347","usgsCitation":"Lewicki, J.L., 2021, Long-term year-round observations of magmatic CO2 emissions on Mammoth Mountain, California, USA: Journal of Volcanology and Geothermal Research, v. 418, 107347, 13 p., https://doi.org/10.1016/j.jvolgeores.2021.107347.","productDescription":"107347, 13 p.","ipdsId":"IP-128355","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":436276,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OJ3KFK","text":"USGS data release","linkHelpText":"Long-term CO2 emissions measurements, Horseshoe Lake tree kill area, Mammoth Mountain, CA"},{"id":387587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mammoth Mountain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.25659179687499,\n 37.42252593456307\n ],\n [\n -118.564453125,\n 37.42252593456307\n ],\n [\n -118.564453125,\n 37.89219554724437\n ],\n [\n -119.25659179687499,\n 37.89219554724437\n ],\n [\n -119.25659179687499,\n 37.42252593456307\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"418","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":820097,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"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":"

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 CO2 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.

","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":70222526,"text":"70222526 - 2021 - Urbanization impacts on evapotranspiration across various spatio-temporal scales","interactions":[],"lastModifiedDate":"2021-08-03T12:57:40.484127","indexId":"70222526","displayToPublicDate":"2021-07-14T07:55:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Urbanization impacts on evapotranspiration across various spatio-temporal scales","docAbstract":"

Urbanization has been shown to locally increase the nighttime temperatures creating urban heat islands, which partly arise due to evapotranspiration (ET) reduction. It is unclear how the direction and magnitude of the change in local ET due to urbanization varies globally across different climatic regimes. This knowledge gap is critical, both for the key role of ET in the energy and water balance accounting for the majority of local precipitation, and for reducing the urban heat island effect. We explore and assess the impacts of urbanization on monthly and mean annual ET across a range of landscapes from local to global spatial scales. Remotely sensed land cover and ET available at 1 km resolution are used to quantify the differences in ET between urban and surrounding non-urban areas across the globe. The observed patterns show that the statistically significant difference between urban and non-urban ET can be estimated to first order as a function of local hydroclimate, with arid regions seeing increased ET, and humid regions showing decreased ET. Cities under cold climates also evaporate more than their non-urban surroundings during the winter, as the urban micro-climate has increased energy availability resulting from human activities. Increased ET in arid cities arises from municipal water withdrawals and increased irrigation during drought conditions. These results can help inform planners to improve the integration of environmental conditions into the design and management of urban landscapes.

","language":"English","publisher":"Wiley","doi":"10.1029/2021EF002045","usgsCitation":"Mazrooei, A., Reitz, M., Wang, D., and Sankarasubramanian, A., 2021, Urbanization impacts on evapotranspiration across various spatio-temporal scales: Earth's Future, v. 9, no. 8, e2021EF002045, 15 p., https://doi.org/10.1029/2021EF002045.","productDescription":"e2021EF002045, 15 p.","ipdsId":"IP-116430","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":489022,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021ef002045","text":"Publisher Index Page"},{"id":436278,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93SYCF4","text":"USGS data release","linkHelpText":"Urbanization Impacts on Evapotranspiration Across Various Spatio-temporal Scales"},{"id":387653,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Mazrooei, Amirhossein","contributorId":241036,"corporation":false,"usgs":false,"family":"Mazrooei","given":"Amirhossein","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":820466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reitz, Meredith 0000-0001-9519-6103 mreitz@usgs.gov","orcid":"https://orcid.org/0000-0001-9519-6103","contributorId":196694,"corporation":false,"usgs":true,"family":"Reitz","given":"Meredith","email":"mreitz@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":820467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Dingbao","contributorId":166993,"corporation":false,"usgs":false,"family":"Wang","given":"Dingbao","email":"","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":820468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sankarasubramanian, A. 0000-0002-7668-1311","orcid":"https://orcid.org/0000-0002-7668-1311","contributorId":241034,"corporation":false,"usgs":false,"family":"Sankarasubramanian","given":"A.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":820469,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"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":"

Karst 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, regolith, and bedrock across a range of length and timescales. These hydrologic pathways frequently include the precipitation of 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 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 seepage waters. We find that measured drip water Mg/Ca and Sr/Ca are captured within the model through variable amounts of limestone dissolution followed by precipitation of secondary calcite 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 paleoclimate records.

","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":70222111,"text":"70222111 - 2021 - Influence of invasive submerged aquatic vegetation (E. densa) on currents and sediment transport in a freshwater tidal system","interactions":[],"lastModifiedDate":"2021-09-14T16:29:41.086323","indexId":"70222111","displayToPublicDate":"2021-07-14T06:57:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Influence of invasive submerged aquatic vegetation (E. densa) on currents and sediment transport in a freshwater tidal system","title":"Influence of invasive submerged aquatic vegetation (E. densa) on currents and sediment transport in a freshwater tidal system","docAbstract":"

We present a field study combining measurements of vegetation density, vegetative drag, and reduction of suspended-sediment concentration (SSC) within patches of the invasive submerged aquatic plant Egeria densa. Our study was motivated by concern that sediment trapping by E. densa, which has proliferated in the Sacramento–San Joaquin Delta, is impacting marsh accretion and reducing turbidity. In the freshwater tidal Delta, E. densa occupies shallow regions, frequently along channel margins. We investigated two sites: Lindsey Slough, a muddy low-energy backwater, and the lower Mokelumne River, with stronger currents and sandy bed sediments. At the two sites biomass density, frontal area, and areal density of the submerged aquatic vegetation (SAV) were similar. Current attenuation within E. densa exceeded 90% and the vegetative drag coefficient followed \"urn:x-wiley:00431397:media:wrcr25436:wrcr25436-math-0001\", where \"urn:x-wiley:00431397:media:wrcr25436:wrcr25436-math-0002\" is stem Reynolds number. The SAV reduced SSC by an average of 18% in Lindsey Slough. At Mokelumne River the reduction ranged 0–40%, with greatest trapping when discharge and SSC were elevated. This depletion of SSC decreases the transport of sediment to marshes by the same percentage, as the rising tide must pass through fringing SAV before reaching marshes. Sediment trapping in E. densa in the Delta is limited by low flux through the canopy and low settling velocity of suspended sediment (mostly flocculated mud). Sediment trapping by SAV has the potential to reduce channel SSC, but the magnitude and sign of the effect can vary with local factors including vegetative coverage and the depositional or erosional nature of the setting.

","language":"English","publisher":"Wiley","doi":"10.1029/2020WR028789","usgsCitation":"Lacy, J.R., Foster-Martinez, M.R., Allen, R.M., and Drexler, J.Z., 2021, Influence of invasive submerged aquatic vegetation (E. densa) on currents and sediment transport in a freshwater tidal system: Water Resources Research, v. 57, e2020WR028789, 22 p., https://doi.org/10.1029/2020WR028789.","productDescription":"e2020WR028789, 22 p.","ipdsId":"IP-119960","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":387286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.83288574218749,\n 37.67512527892127\n ],\n [\n -120.311279296875,\n 37.67512527892127\n ],\n [\n -120.311279296875,\n 38.66192241975437\n ],\n [\n -121.83288574218749,\n 38.66192241975437\n ],\n [\n -121.83288574218749,\n 37.67512527892127\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","noUsgsAuthors":false,"publicationDate":"2021-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":819563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster-Martinez, Madeline R.","contributorId":201705,"corporation":false,"usgs":false,"family":"Foster-Martinez","given":"Madeline","email":"","middleInitial":"R.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":819564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Rachel M. 0000-0002-0287-6466","orcid":"https://orcid.org/0000-0002-0287-6466","contributorId":261242,"corporation":false,"usgs":false,"family":"Allen","given":"Rachel","email":"","middleInitial":"M.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":819565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819566,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70226696,"text":"70226696 - 2021 - Seismic monitoring during crises at the NEIC in support of the ANSS","interactions":[],"lastModifiedDate":"2021-12-06T12:18:06.643593","indexId":"70226696","displayToPublicDate":"2021-07-14T06:10:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Seismic monitoring during crises at the NEIC in support of the ANSS","docAbstract":"

Over the past two decades, the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) has overcome many operational challenges. These range from minor disruptions, such as power outages, to significant operational changes, including system reconfiguration to handle unique earthquake sequences and the need to handle distributed work during a pandemic. Our ability to overcome crises is built on the development and implementation of a continuity of operations plan, well‐designed infrastructure, adaptive software systems, experienced staff, and extensive collaboration. The NEIC does not operate in a vacuum but benefits from contributions of United States and international seismic networks. Similarly, the overall resilience of earthquake monitoring in the United States and around the globe benefits from the NEIC’s role as the national center for the Advanced National Seismic System (ANSS). Here, we highlight significant adaptations the NEIC has made in the face of crises. We discuss the COVID‐19 pandemic, which represents the most significant operational crisis to impact the NEIC. The NEIC has maintained continuous operations during the ongoing COVID‐19 pandemic by shifting from a fully onsite operations center to a distributed hybrid of onsite and telework staffing. We then discuss cases in which the NEIC has supported regional monitoring in the face of significant crises. In 2018, the NEIC assisted the Hawaiian Volcano Observatory with the Kīlauea volcano eruption by responding to large events, implementing contingency monitoring procedures, and calculating moment magnitudes for the low‐frequency caldera collapses. Impacts of a crisis extend beyond the immediate response and often require a significant postevent assessment and a rebuilding phase. After the 2017 Hurricane Maria, the NEIC, the USGS National Strong‐Motion Program, and the USGS Albuquerque Seismological Laboratory worked with the Puerto Rico Seismic Network and the Puerto Rico Strong‐Motion program to assess, plan, and implement upgrades at sites that experienced storm damage.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220200289","usgsCitation":"Earle, P.S., Benz, H.M., Yeck, W.L., Hayes, G., Guy, M.M., Patton, J., Kragness, D., Mason, D.B., Shiro, B., Wolin, E., Bellini, J., Pursley, J., and Sanders, R.L., 2021, Seismic monitoring during crises at the NEIC in support of the ANSS: Seismological Research Letters, v. 5, no. 92, p. 2905-2914, https://doi.org/10.1785/0220200289.","productDescription":"10 p.","startPage":"2905","endPage":"2914","ipdsId":"IP-126084","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":392495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": 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2015–17","interactions":[],"lastModifiedDate":"2021-07-14T18:43:40.52114","indexId":"ofr20211061","displayToPublicDate":"2021-07-13T13:15:14","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":"2021-1061","displayTitle":"Spatial and Temporal Distribution of Radio-Tagged Lost River (Deltistes luxatus) and Shortnose (Chasmistes brevirostris) Suckers in Clear Lake Reservoir and Associated Spawning Tributaries, Northern California, 2015–17","title":"Spatial and temporal distribution of radio-tagged Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) suckers in Clear Lake Reservoir and associated spawning tributaries, Northern California, 2015–17","docAbstract":"

Executive Summary

Data from a multi-year radio telemetry study were used to assess seasonal distribution patterns for two long-lived, federally endangered catostomids across substantially different water conditions in Clear Lake Reservoir, northern California. Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) suckers, two species endemic to the Klamath Basin, were implanted with radio transmitters in each of 3 years in an effort to expand our understanding of seasonal sucker movements within the reservoir and their migrations in spawning tributaries. Clear Lake Reservoir and its tributaries are part of a critical management unit within the Lost River Basin Recovery Unit for populations of Lost River and shortnose suckers. We documented residency and migratory behaviors and how behaviors were affected by lake surface elevations and water management practices.

Adult suckers were captured during autumn trammel net sampling in the west lobe of the reservoir and implanted with internal radio transmitters. A total of 163 suckers were radio-tagged (75 in 2014, 64 in 2015, and 24 in 2016); 27 more shortnose suckers were tagged than Lost River suckers to reflect the larger population of shortnose suckers in the reservoir. Sex ratios were approximately equal for each species. Aerial telemetry surveys were used to monitor radio-tagged fish from January 20 to December 2 each year and to document the upstream extent of spawning migrations in the tributaries. Surveys were scheduled more frequently during the spawning season (February–June) when suckers are known to move out of the reservoir and into spawning tributaries.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211061","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Banet, N.V., Hewitt, D.A., Dolan-Caret, A., and Harris, A.C., 2021, Spatial and temporal distribution of radio-tagged Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) suckers in Clear Lake Reservoir and associated spawning tributaries, Northern California, 2015–17: U.S. Geological Survey Open-File Report 2021–1061, 37 p., https://doi.org/10.3133/ofr20211061.","productDescription":"vi, 37 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-120279","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":387167,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2021/1061/ofr20211061_landing.html","text":"Animated movements and migrations","description":"OFR 2021-1061 Animated movements and migrations."},{"id":387166,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1061/ofr20211061.pdf","text":"Report","size":"12.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1061"},{"id":387165,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1061/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Clear Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.25610351562499,\n 41.78616105896385\n ],\n [\n -121.03637695312499,\n 41.78616105896385\n ],\n [\n -121.03637695312499,\n 41.93548729665268\n ],\n [\n -121.25610351562499,\n 41.93548729665268\n ],\n [\n -121.25610351562499,\n 41.78616105896385\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016

","tableOfContents":"","publishedDate":"2021-07-13","noUsgsAuthors":false,"publicationDate":"2021-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Banet, Nathan 0000-0002-8537-1702","orcid":"https://orcid.org/0000-0002-8537-1702","contributorId":217751,"corporation":false,"usgs":true,"family":"Banet","given":"Nathan","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dolan-Caret, Amari 0000-0001-9155-6116 amaridc@usgs.gov","orcid":"https://orcid.org/0000-0001-9155-6116","contributorId":149805,"corporation":false,"usgs":true,"family":"Dolan-Caret","given":"Amari","email":"amaridc@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819253,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, Alta C. 0000-0002-2123-3028 aharris@usgs.gov","orcid":"https://orcid.org/0000-0002-2123-3028","contributorId":3490,"corporation":false,"usgs":true,"family":"Harris","given":"Alta C.","email":"aharris@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819254,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221881,"text":"fs20213039 - 2021 - Arizona and Landsat","interactions":[],"lastModifiedDate":"2023-01-24T11:49:54.477263","indexId":"fs20213039","displayToPublicDate":"2021-07-13T11:47:03","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-3039","displayTitle":"Arizona and Landsat","title":"Arizona and Landsat","docAbstract":"

Arizona is a land of massive grandeur, deep gorges, lofty mountains, immense plains, and elevated mesas—and, without question, its crown jewel is the Grand Canyon. The spectacular canyon, one of the seven natural wonders of the world, was created when the Colorado River carved a channel through northern Arizona, revealing nearly two billion years of the Earth's history.

Yet, for all its ancient beauty, Arizona and its landscapes are experiencing a transformation.

Arizonans face more extreme temperatures and drought because of climate change. Amid a drought in the western United States, Lake Mead, one of Arizona's main water resources, dropped to a record low level in June 2021. Climate change is making extreme weather events such as dust storms and heat waves more common, posing higher risks to human health, according to the Centers for Disease Control and Prevention.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213039","usgsCitation":"U.S. Geological Survey, 2021, Arizona and Landsat (ver. 1.1, January 2023): U.S. Geological Survey Fact Sheet 2021–3039, 2 p., https://doi.org/10.3133/fs20213039.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-130596","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":412226,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20213039/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":412182,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2021/3039/images"},{"id":412181,"rank":4,"type":{"id":31,"text":"Publication 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\"}}]}","edition":"Version 1.0: July 13, 2021; Version 1.1: January 23, 2023","contact":"

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","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-07-13","revisedDate":"2023-01-23","noUsgsAuthors":false,"publicationDate":"2021-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":819201,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70251840,"text":"70251840 - 2021 - Seismic and geodetic analysis of rupture characteristics of the 2020 Mw 6.5 Monte Cristo Range, Nevada, earthquake","interactions":[],"lastModifiedDate":"2024-03-04T16:54:56.411506","indexId":"70251840","displayToPublicDate":"2021-07-13T10:48:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Seismic and geodetic analysis of rupture characteristics of the 2020 Mw 6.5 Monte Cristo Range, Nevada, earthquake","docAbstract":"

The largest earthquake since 1954 to strike the state of Nevada, United States, ruptured on 15 May 2020 along the Monte Cristo range of west‐central Nevada. The Mw 6.5 event involved predominantly left‐lateral strike‐slip faulting with minor normal components on three aligned east–west‐trending faults that vary in strike by 23°. The kinematic rupture process is determined by joint inversion of Global Navigation Satellite Systems displacements, Interferometric Synthetic Aperture Radar (InSAR) data, regional strong motions, and teleseismic P and SH waves, with the three‐fault geometry being constrained by InSAR surface deformation observations, surface ruptures, and relocated aftershock distributions. The average rupture velocity is 1.5  km/s⁠, with a peak slip of ∼1.6  m and a ∼20  s rupture duration. The seismic moment is 6.9×1018  N·m⁠. Complex surface deformation is observed near the fault junction, with a deep near‐vertical fault and a southeast‐dipping fault at shallow depth on the western segment, along which normal‐faulting aftershocks are observed. There is a shallow slip deficit in the Nevada ruptures, probably due to the immature fault system. The causative faults had not been previously identified and are located near the transition from the Walker Lane belt to the Basin and Range province. The east–west geometry of the system is consistent with the eastward extension of the Mina Deflection of the Walker Lane north of the White Mountains.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120200327","usgsCitation":"Liu, C., Lay, T., Pollitz, F., Xu, J., and Xiong, X., 2021, Seismic and geodetic analysis of rupture characteristics of the 2020 Mw 6.5 Monte Cristo Range, Nevada, earthquake: Bulletin of the Seismological Society of America, v. 111, no. 6, p. 3226-3236, https://doi.org/10.1785/0120200327.","productDescription":"11 p.","startPage":"3226","endPage":"3236","ipdsId":"IP-124244","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":426236,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116,\n 39.5\n ],\n [\n -119.75,\n 39.5\n ],\n [\n -119.75,\n 36.75\n ],\n [\n -116,\n 36.75\n ],\n [\n -116,\n 39.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"111","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Chengli","contributorId":334476,"corporation":false,"usgs":false,"family":"Liu","given":"Chengli","email":"","affiliations":[{"id":12433,"text":"China University of Geosciences","active":true,"usgs":false}],"preferred":false,"id":895789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lay, Thorne","contributorId":334478,"corporation":false,"usgs":false,"family":"Lay","given":"Thorne","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":895790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":895791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xu, Jiao","contributorId":334480,"corporation":false,"usgs":false,"family":"Xu","given":"Jiao","email":"","affiliations":[{"id":55508,"text":"Guilin University of Technology","active":true,"usgs":false}],"preferred":false,"id":895792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xiong, Xiong","contributorId":334482,"corporation":false,"usgs":false,"family":"Xiong","given":"Xiong","email":"","affiliations":[{"id":12433,"text":"China University of Geosciences","active":true,"usgs":false}],"preferred":false,"id":895793,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254672,"text":"70254672 - 2021 - Evaluation of camera trap-based abundance estimators for unmarked populations","interactions":[],"lastModifiedDate":"2024-06-06T14:32:31.086132","indexId":"70254672","displayToPublicDate":"2021-07-13T09:21:25","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of camera trap-based abundance estimators for unmarked populations","docAbstract":"

Estimates of species abundance are critical to understand population processes and to assess and select management actions. However, capturing and marking individuals for abundance estimation, while providing robust information, can be economically and logistically prohibitive, particularly for species with cryptic behavior. Camera traps can be used to collect data at temporal and spatial scales necessary for estimating abundance, but the use of camera traps comes with limitations when target species are not uniquely identifiable (i.e., “unmarked”). Abundance estimation is particularly useful in the management of invasive species, with herpetofauna being recognized as some of the most pervasive and detrimental invasive vertebrate species. However, the use of camera traps for these taxa presents additional challenges with relevancy across multiple taxa. It is often necessary to use lures to attract animals in order to obtain sufficient observations, yet lure attraction can influence species’ landscape use and potentially induce bias in abundance estimators. We investigated these challenges and assessed the feasibility of obtaining reliable abundance estimates using camera-trapping data on a population of invasive brown treesnakes (Boiga irregularis) in Guam. Data were collected using camera traps in an enclosed area where snakes were subject to high-intensity capture–recapture effort, resulting in presumed abundance of 116 snakes (density = 23/ha). We then applied spatial count, random encounter and staying time, space to event, and instantaneous sampling estimators to photo-capture data to estimate abundance and compared estimates to our presumed abundance. We found that all estimators for unmarked populations performed poorly, with inaccurate or imprecise abundance estimates that limit their usefulness for management in this system. We further investigated the sensitivity of these estimators to the use of lures (i.e., violating the assumption that animal behavior is unchanged by sampling) and camera density in a simulation study. Increasing the effective distances of a lure (i.e., lure attraction) and camera density both resulted in biased abundance estimates. Each estimator rarely recovered truth or suffered from convergence issues. Our results indicate that, when limited to unmarked estimators and the use of lures, camera traps alone are unlikely to produce abundance estimates with utility for brown treesnake management.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2410","usgsCitation":"Amburgey, S.M., Yackel Adams, A.A., Gardner, B., Hostetter, N., Siers, S., McClintock, B., and Converse, S.J., 2021, Evaluation of camera trap-based abundance estimators for unmarked populations: Ecological Applications, v. 31, no. 7, e02410, 19 p.; Data Release, https://doi.org/10.1002/eap.2410.","productDescription":"e02410, 19 p.; Data Release","ipdsId":"IP-126135","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":451529,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/eap.2410","text":"External Repository"},{"id":436279,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JV1QU5","text":"USGS data release","linkHelpText":"Camera trap data of Brown Treesnakes at mouse-lure 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13.245019438123833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Amburgey, S M 0000-0002-7100-7811","orcid":"https://orcid.org/0000-0002-7100-7811","contributorId":245926,"corporation":false,"usgs":false,"family":"Amburgey","given":"S","email":"","middleInitial":"M","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":902201,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":902202,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gardner, B.","contributorId":26793,"corporation":false,"usgs":true,"family":"Gardner","given":"B.","email":"","affiliations":[],"preferred":false,"id":902280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hostetter, N.J.","contributorId":46347,"corporation":false,"usgs":true,"family":"Hostetter","given":"N.J.","affiliations":[],"preferred":false,"id":902203,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Siers, S.R.","contributorId":337213,"corporation":false,"usgs":false,"family":"Siers","given":"S.R.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":902204,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McClintock, B.T.","contributorId":29108,"corporation":false,"usgs":true,"family":"McClintock","given":"B.T.","email":"","affiliations":[],"preferred":false,"id":902205,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902200,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"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":"

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.

","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":"

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 activities1. 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 journal2 — 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 meetings3.

","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":"

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.

","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":70248348,"text":"70248348 - 2021 - Southwestern bats and their external bacteria","interactions":[],"lastModifiedDate":"2023-09-08T12:24:53.620346","indexId":"70248348","displayToPublicDate":"2021-07-13T07:23:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Southwestern bats and their external bacteria","docAbstract":"

Bat species diversity within the United States is greatest in the Southwest, with approximately 30 species present. At least 16 of these bat species hibernate and are susceptible to white-nose syndrome (WNS), which is caused by the fungus Pseudogymnoascus destructans. Since 2006, millions of bats from 35 U.S. states and 7 Canadian provinces have died from WNS. In previous studies of external surfaces of bats sampled from southwestern states, Actinobacteria were detected that were shown to have antifungal properties against P. destructans in laboratory testing. These studies motivated us to expand our research to sites that represent possible gateways for P. destructans to enter the Southwest so that we could establish a baseline of bat microbiota before the arrival of WNS. We surveyed for the presence of bats and their external microbiota at 3 national parks and monuments located in southeastern Colorado and northeastern New Mexico. Our results document new occurrence records of bat species and their external bacteria at each sampling location. Additionally, we provide insight on the composition of bat external microbiota in the absence of P. destructans, while revealing information about the Streptomyces and other possible native defenses of bats against P. destructans at a gateway into the Southwest.

","language":"English","publisher":"BioOne","doi":"10.3398/064.081.0206","usgsCitation":"Valdez, E.W., Johnson, E.M., Strach, E.W., Lewis, P.A., Briggs, W., Caimi, N.A., Winter, A.S., Northup, D.E., and Hathaway, J.J., 2021, Southwestern bats and their external bacteria: Western North American Naturalist, v. 81, no. 2, p. 207-224, https://doi.org/10.3398/064.081.0206.","productDescription":"18 p.","startPage":"207","endPage":"224","ipdsId":"IP-099392","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":420658,"type":{"id":24,"text":"Thumbnail"},"url":"http://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"81","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Valdez, Ernest W. 0000-0002-7262-3069 ernie@usgs.gov","orcid":"https://orcid.org/0000-0002-7262-3069","contributorId":3600,"corporation":false,"usgs":true,"family":"Valdez","given":"Ernest","email":"ernie@usgs.gov","middleInitial":"W.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":882642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Emily M.","contributorId":329576,"corporation":false,"usgs":false,"family":"Johnson","given":"Emily","email":"","middleInitial":"M.","affiliations":[{"id":33800,"text":"University of New Mexico (UNM)","active":true,"usgs":false}],"preferred":false,"id":882643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Strach, Edward W.","contributorId":329578,"corporation":false,"usgs":false,"family":"Strach","given":"Edward","email":"","middleInitial":"W.","affiliations":[{"id":16658,"text":"UNM","active":true,"usgs":false}],"preferred":false,"id":882644,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewis, Patrick A.","contributorId":329580,"corporation":false,"usgs":false,"family":"Lewis","given":"Patrick","email":"","middleInitial":"A.","affiliations":[{"id":16658,"text":"UNM","active":true,"usgs":false}],"preferred":false,"id":882645,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, William C","contributorId":329582,"corporation":false,"usgs":false,"family":"Briggs","given":"William C","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":882646,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caimi, Nicole A.","contributorId":193655,"corporation":false,"usgs":false,"family":"Caimi","given":"Nicole","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":882647,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Winter, Ara S.","contributorId":199826,"corporation":false,"usgs":false,"family":"Winter","given":"Ara","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":882648,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Northup, Diana E.","contributorId":193656,"corporation":false,"usgs":false,"family":"Northup","given":"Diana","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":882649,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hathaway, Jennifer J.M.","contributorId":329573,"corporation":false,"usgs":false,"family":"Hathaway","given":"Jennifer","email":"","middleInitial":"J.M.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":882650,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"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":"

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 (zeroth moment, m0; bandwidth parameter, δ; frequency of zero crossings, fz; and frequency of extrema, fe). 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.

","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 (Centrococercus urophasianus)","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":70229379,"text":"70229379 - 2021 - A case for multiscale habitat selection studies of small mammals","interactions":[],"lastModifiedDate":"2022-03-04T15:29:53.836594","indexId":"70229379","displayToPublicDate":"2021-07-12T09:18:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"A case for multiscale habitat selection studies of small mammals","docAbstract":"

Habitat information for small mammals typically consists of anecdotal descriptions or infrequent analyses of habitat use, which often are reported erroneously as signifying habitat preference, requirements, or quality. Habitat preferences can be determined only by analysis of habitat selection, a behavioral process that results in the disproportionate use of one resource over other available resources and occurs in a hierarchical manner across different environmental scales. North American chipmunks (Neotamias and Tamias) are a prime example of the lack of studies on habitat selection for small mammal species. We used the Organ Mountains Colorado chipmunk (N. quadrivittatus australis) as a case study to determine whether previous descriptions of habitat in the literature were upheld in a multiscale habitat selection context. We tracked VHF radiocollared chipmunks and collected habitat information at used and available locations to analyze habitat selection at three scales: second order (i.e., home range), third order (i.e., within home range), and microhabitat scales. Mean home range was 2.55 ha ± 1.55 SD and did not differ between sexes. At the second and third order, N. q. australis avoided a coniferous forest land cover type and favored particular areas of arroyos (gullies) that were relatively steep-sided and greener and contained montane scrub land cover type. At the microhabitat scale, chipmunks selected areas that had greater woody plant diversity, rock ground cover, and ground cover of coarse woody debris. We concluded that habitat selection by N. q. australis fundamentally was different from descriptions of habitat in the literature that described N. quadrivittatus as primarily associated with coniferous forests. We suggest that arroyos, which are unique and rare on the landscape, function as climate refugia for these chipmunks because they create a cool, wet microclimate. Our findings demonstrate the importance of conducting multiscale habitat selection studies for small mammals to ensure that defensible and enduring habitat information is available to support appropriate conservation and management actions.

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