{"pageNumber":"52","pageRowStart":"1275","pageSize":"25","recordCount":11004,"records":[{"id":70221729,"text":"70221729 - 2021 - Recent carbon storage and burial exceed historic rates in the San Juan Bay estuary peri-urban mangrove forests (Puerto Rico, United States)","interactions":[],"lastModifiedDate":"2021-06-30T13:02:41.288765","indexId":"70221729","displayToPublicDate":"2021-06-07T07:56:06","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5860,"text":"Frontiers in Forests and Global Change","active":true,"publicationSubtype":{"id":10}},"title":"Recent carbon storage and burial exceed historic rates in the San Juan Bay estuary peri-urban mangrove forests (Puerto Rico, United States)","docAbstract":"

Mangroves sequester significant quantities of organic carbon (C) because of high rates of burial in the soil and storage in biomass. We estimated mangrove forest C storage and accumulation rates in aboveground and belowground components among five sites along an urbanization gradient in the San Juan Bay Estuary, Puerto Rico. Sites included the highly urbanized and clogged Caño Martin Peña in the western half of the estuary, a series of lagoons in the center of the estuary, and a tropical forest reserve (Piñones) in the easternmost part. Radiometrically dated cores were used to determine sediment accretion and soil C storage and burial rates. Measurements of tree dendrometers coupled with allometric equations were used to estimate aboveground biomass. Estuary-wide mangrove forest C storage and accumulation rates were estimated using interpolation methods and coastal vegetation cover data. In recent decades (1970–2016), the highly urbanized Martin Peña East (MPE) site with low flushing had the highest C storage and burial rates among sites. The MPE soil carbon burial rate was over twice as great as global estimates. Mangrove forest C burial rates in recent decades were significantly greater than historic decades (1930–1970) at Caño Martin Peña and Piñones. Although MPE and Piñones had similarly low flushing, the landscape settings (clogged canal vs forest reserve) and urbanization (high vs low) were different. Apparently, not only urbanization, but site-specific flushing patterns, landscape setting, and soil fertility affected soil C storage and burial rates. There was no difference in C burial rates between historic and recent decades at the San José and La Torrecilla lagoons. Mangrove forests had soil C burial rates ranging from 88 g m–2 y–1 at the San José lagoon to 469 g m–2 y–1 at the MPE in recent decades. Watershed anthropogenic CO2 emissions (1.56 million Mg C y–1) far exceeded the annual mangrove forest C storage rates (aboveground biomass plus soils: 17,713 Mg C y–1). A combination of maintaining healthy mangrove forests and reducing anthropogenic emissions might be necessary to mitigate greenhouse gas emissions in urban, tropical areas.

","language":"English","publisher":"Frontiers","doi":"10.3389/ffgc.2021.676691","usgsCitation":"Wigand, C., Eagle, M.J., Branoff, B., Balogh, S., Miller, K., Martin, R.M., Hanson, A., Oczkowski, A., Huertas, E., Loffredo, J., and Watson, E., 2021, Recent carbon storage and burial exceed historic rates in the San Juan Bay estuary peri-urban mangrove forests (Puerto Rico, United States): Frontiers in Forests and Global Change, v. 4, 14 p., https://doi.org/10.3389/ffgc.2021.676691.","productDescription":"14 p.","ipdsId":"IP-127865","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451994,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2021.676691","text":"Publisher Index Page"},{"id":436326,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97CAF30","text":"USGS data release","linkHelpText":"Collection, analysis, and age-dating of sediment cores from mangrove wetlands in San Juan Bay Estuary, Puerto Rico, 2016"},{"id":386891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.357177734375,\n 17.756534036838417\n ],\n [\n -65.58013916015625,\n 17.756534036838417\n ],\n [\n -65.58013916015625,\n 18.599395202198725\n ],\n [\n -67.357177734375,\n 18.599395202198725\n ],\n [\n -67.357177734375,\n 17.756534036838417\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","noUsgsAuthors":false,"publicationDate":"2021-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Wigand, Cathleen","contributorId":260715,"corporation":false,"usgs":false,"family":"Wigand","given":"Cathleen","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":818541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eagle, Meagan J. 0000-0001-5072-2755 meagle@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":242890,"corporation":false,"usgs":true,"family":"Eagle","given":"Meagan","email":"meagle@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Branoff, Benjamin","contributorId":216871,"corporation":false,"usgs":false,"family":"Branoff","given":"Benjamin","affiliations":[{"id":39539,"text":"University of Puerto Rico, San Juan, PR","active":true,"usgs":false}],"preferred":false,"id":818543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Balogh, Stephen","contributorId":260716,"corporation":false,"usgs":false,"family":"Balogh","given":"Stephen","email":"","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":818544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Kenneth","contributorId":260717,"corporation":false,"usgs":false,"family":"Miller","given":"Kenneth","affiliations":[{"id":52655,"text":"General Dynamics Information Technology, 6361 Walker Lane, Suite 300 Alexandria, VA","active":true,"usgs":false}],"preferred":false,"id":818545,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Martin, Rose M.","contributorId":211671,"corporation":false,"usgs":false,"family":"Martin","given":"Rose","email":"","middleInitial":"M.","affiliations":[{"id":38313,"text":"Atlantic Ecology Division, Environmental Protection Agency, 27 Tarzwell Dr. Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":818546,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hanson, Alana","contributorId":260718,"corporation":false,"usgs":false,"family":"Hanson","given":"Alana","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":818547,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oczkowski, Autumn","contributorId":260719,"corporation":false,"usgs":false,"family":"Oczkowski","given":"Autumn","email":"","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":818548,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Huertas, Evelyn","contributorId":260720,"corporation":false,"usgs":false,"family":"Huertas","given":"Evelyn","email":"","affiliations":[{"id":52656,"text":"US EPA, Caribbean Environmental Protection Division, Guaynabo, PR","active":true,"usgs":false}],"preferred":false,"id":818549,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Loffredo, Joseph","contributorId":260721,"corporation":false,"usgs":false,"family":"Loffredo","given":"Joseph","email":"","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":818550,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Watson, Elizabeth","contributorId":260722,"corporation":false,"usgs":false,"family":"Watson","given":"Elizabeth","affiliations":[{"id":52657,"text":"Department of Biodiversity, Earth & Environmental Sciences and The Academy of Natural Sciences, Drexel University, 1900 Benjamin Franklin Pkwy, Philadelphia, PA,","active":true,"usgs":false}],"preferred":false,"id":818551,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70221293,"text":"70221293 - 2021 - Direct and size-mediated effects of temperature and ration-dependent growth rates on energy reserves in juvenile anadromous alewives (Alosa pseudoharengus)","interactions":[],"lastModifiedDate":"2021-10-18T14:04:00.020978","indexId":"70221293","displayToPublicDate":"2021-06-07T07:27:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Direct and size-mediated effects of temperature and ration-dependent growth rates on energy reserves in juvenile anadromous alewives (Alosa pseudoharengus)","title":"Direct and size-mediated effects of temperature and ration-dependent growth rates on energy reserves in juvenile anadromous alewives (Alosa pseudoharengus)","docAbstract":"

Growth rate and energy reserves are important determinants of fitness and are governed by endogenous and exogenous factors. Thus, examining the influence of individual and multiple stressors on growth and energy reserves can help estimate population health under current and future conditions. In young anadromous fishes, freshwater habitat quality determines physiological state and fitness of juveniles emigrating to marine habitats. We tested how temperature and food availability affect survival, growth, and energy reserves in juvenile anadromous alewives (Alosa pseudoharengus), a forage fish distributed along the eastern North American continent. Field-collected juvenile anadromous A. pseudoharengus were exposed for 21 days to one of two temperatures (21°C and 25°C) and one of two levels of food rations (1% or 2% tank biomass daily) and compared for differences in final size, fat mass-at-length, lean mass-at-length, and energy density. Increased temperature and reduced ration both led to lower growth rates and the effect of reduced ration was greater at higher temperature. Fat mass-at-length decreased with dry mass and energy density increased with total length, suggesting size-based endogenous influences on energy reserves. Lower ration also directly decreased fat mass-at-length, lean mass-at-length and energy density. Given the fitness implications of size and energy reserves, temperature and food availability should be considered important indicators of nursery habitat quality and incorporated in A. pseudoharengus life history models to improve forecasting of population health under climate change.

","language":"English","publisher":"Wiley","doi":"10.1111/jfb.14824","usgsCitation":"Guo, L., McCormick, S.D., Schultz, E., and Jordaan, A., 2021, Direct and size-mediated effects of temperature and ration-dependent growth rates on energy reserves in juvenile anadromous alewives (Alosa pseudoharengus): Journal of Fish Biology, v. 99, no. 4, p. 1236-1246, https://doi.org/10.1111/jfb.14824.","productDescription":"11 p.","startPage":"1236","endPage":"1246","ipdsId":"IP-125451","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":386341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Guo, Liang 0000-0001-5454-6330","orcid":"https://orcid.org/0000-0001-5454-6330","contributorId":210404,"corporation":false,"usgs":false,"family":"Guo","given":"Liang","email":"","affiliations":[],"preferred":false,"id":817253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":817254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schultz, Eric T.","contributorId":260102,"corporation":false,"usgs":false,"family":"Schultz","given":"Eric T.","affiliations":[],"preferred":false,"id":817255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jordaan, Adrian","contributorId":257709,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":817256,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222615,"text":"70222615 - 2021 - NGA-East ground-motion characterization model Part II: Implementation and hazard implications","interactions":[],"lastModifiedDate":"2021-08-09T13:14:26.676694","indexId":"70222615","displayToPublicDate":"2021-06-06T08:11:42","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 II: Implementation and hazard implications","docAbstract":"

As a companion article to Goulet et al., we describe implementation of the NGA-East ground motion characterization (GMC) model in probabilistic seismic hazard analysis (PSHA) for sites in the Central and Eastern United States (CEUS). We present extensions to the EPRI/DOE/NRC seismic source characterization (SSC) model for the CEUS needed for full implementation of NGA-East. Comparisons are presented to the EPRI GMC, the currently accepted model by the U.S. Nuclear Regulatory Commission for hazard assessment at nuclear facilities. Comparisons are presented both in terms of GMC model components and in the resulting seismic hazard assessments for a range of site locations in the CEUS. Illustrations of the effect of various components of the NGA-East GMC on seismic hazard results are also presented. Finally, we present recommendations for application of the NGA-East GMC in PSHA.

","language":"English","publisher":"Earthquake Engineering Research Institute (EERI)","doi":"10.1177/87552930211007503","usgsCitation":"Youngs, R., Goulet, C.A., Bozorgnia, Y., Kuehn, N., Al Atik, L., Graves, R., and Atkinson, G.M., 2021, NGA-East ground-motion characterization model Part II: Implementation and hazard implications: Earthquake Spectra, v. 37, no. 1, p. 1283-1330, https://doi.org/10.1177/87552930211007503.","productDescription":"48 p.","startPage":"1283","endPage":"1330","ipdsId":"IP-124999","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":387773,"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 -108.6328125,\n 31.57853542647338\n ],\n [\n -105.205078125,\n 29.458731185355344\n ],\n [\n -102.919921875,\n 29.152161283318915\n ],\n [\n -97.646484375,\n 25.48295117535531\n ],\n [\n -93.779296875,\n 26.27371402440643\n ],\n [\n -81.298828125,\n 24.367113562651262\n ],\n [\n -77.34374999999999,\n 27.371767300523047\n ],\n [\n -72.24609375,\n 33.94335994657882\n ],\n [\n -57.65624999999999,\n 45.089035564831036\n ],\n [\n -61.787109375,\n 51.23440735163459\n ],\n [\n -71.630859375,\n 50.401515322782366\n ],\n [\n -75.9375,\n 47.635783590864854\n ],\n [\n -86.1328125,\n 50.28933925329178\n ],\n [\n -100.283203125,\n 52.696361078274485\n ],\n [\n -108.896484375,\n 51.83577752045248\n ],\n [\n -108.720703125,\n 48.86471476180277\n ],\n [\n -109.3359375,\n 40.44694705960048\n ],\n [\n -108.6328125,\n 31.57853542647338\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Youngs, Robert","contributorId":140544,"corporation":false,"usgs":false,"family":"Youngs","given":"Robert","affiliations":[],"preferred":false,"id":820761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":820762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":820763,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":820764,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Al Atik, Linda","contributorId":140526,"corporation":false,"usgs":false,"family":"Al Atik","given":"Linda","email":"","affiliations":[],"preferred":false,"id":820765,"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":820766,"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":820767,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70221475,"text":"70221475 - 2021 - Relative risk of groundwater-quality degradation near California (USA) oil fields estimated from 3H, 14C, and 4He","interactions":[],"lastModifiedDate":"2021-06-17T11:56:09.830879","indexId":"70221475","displayToPublicDate":"2021-06-05T06:52:07","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Relative risk of groundwater-quality degradation near California (USA) oil fields estimated from 3H, 14C, and 4He","docAbstract":"

Relative risks of groundwater-quality degradation near selected California oil fields are estimated by examining spatial and temporal patterns in chemical and isotopic data in the context of groundwater-age categories defined by tritium and carbon-14. In the Coastal basins, western San Joaquin Valley (SJV), and eastern SJV; 82, 76, and 0% of samples are premodern (pre-1953 recharge), respectively; and 3, 0, and 31% are modern (recharged during or after 1953), respectively. Carbon-14 and helium-4 data indicate most premodern samples are 1000 to 10,000 (33%) or >10,000 (50%) years old. Organic chemicals that could be associated with deeper hydrocarbon reservoirs (e.g. thermogenic gases and benzene) occur most frequently in premodern groundwater, suggesting premodern groundwater has a higher risk of degradation from upward migration of hydrocarbons than modern and mixed-age groundwater. Low sulfate concentrations in some premodern groundwater containing high thermogenic-methane concentrations (>28 mg/L) indicate methane attenuation associated with sulfate reduction can be limited in premodern groundwater. The more common occurrence of manufactured compounds, like tetrachloroethene, in modern and mixed-age groundwater than in premodern groundwater indicates modern and mixed-age groundwater has a higher risk of degradation from land-surface sources than premodern groundwater. Time-series data for chloride in groundwater affected by disposal of oil-field water in unlined ponds indicate some modern and mixed-age groundwater are susceptible to chemical migration within 2–3 km of surface sources. Timescales for diluting chloride concentrations in groundwater with fresh recharge once disposal ponds are decommissioned are shorter in mixed-age groundwater with large fractions of modern water (9–14 years in one example) than in mixed-age groundwater with large fractions of premodern water (no evidence of dilution after 12 years of monitoring in one example). The presence of predominantly premodern groundwater in the Coastal basins and western SJV indicates these areas have relatively high risk from upward migration of hydrocarbons, reduced methane attenuation capacity, and long dilution times, whereas predominantly modern- and mixed-age groundwater in the eastern SJV indicates this area has relatively high risk from chemical migration from land-surface sources and subsequent extensive spreading. Age-based characterizations of relative risk could inform the design of groundwater-monitoring programs near oil fields in terms of the spatial distribution of monitoring points relative to source areas and monitoring frequency and duration.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2021.105024","usgsCitation":"McMahon, P.B., Landon, M.K., Davis, T., Wright, M., Rosecrans, C.Z., Anders, R., Land, M., Kulongoski, J.T., and Hunt, A., 2021, Relative risk of groundwater-quality degradation near California (USA) oil fields estimated from 3H, 14C, and 4He: Applied Geochemistry, v. 131, 105024, 15 p., https://doi.org/10.1016/j.apgeochem.2021.105024.","productDescription":"105024, 15 p.","ipdsId":"IP-120473","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":452009,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2021.105024","text":"Publisher Index Page"},{"id":386566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.95947265624999,\n 33.96158628979907\n ],\n [\n -117.99316406249999,\n 33.96158628979907\n ],\n [\n -117.99316406249999,\n 35.30840140169162\n ],\n [\n -120.95947265624999,\n 35.30840140169162\n ],\n [\n -120.95947265624999,\n 33.96158628979907\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"131","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Tracy 0000-0003-0253-6661 tadavis@usgs.gov","orcid":"https://orcid.org/0000-0003-0253-6661","contributorId":176921,"corporation":false,"usgs":true,"family":"Davis","given":"Tracy","email":"tadavis@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817787,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, Michael 0000-0003-0653-6466 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aquifers","interactions":[],"lastModifiedDate":"2024-06-03T11:50:37.905478","indexId":"70254573","displayToPublicDate":"2021-06-03T06:45:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Effects of climate and irrigation on GRACE-based estimates of water storage changes in major US aquifers","docAbstract":"

Understanding climate and human impacts on water storage is critical for sustainable water-resources management. Here we assessed climate and human drivers of total water storage (TWS) variability from Gravity Recovery and Climate Experiment (GRACE) satellites compared with drought severity and irrigation water use in 14 major aquifers in the United States. Results show that long-term variability in TWS tracked by GRACE satellites is dominated by interannual variability in most of the 14 major US aquifers. Low TWS trends in the humid eastern U.S. are linked to low drought intensity. Although irrigation pumpage in the humid Mississippi Embayment aquifer exceeded that in the semi-arid California Central Valley, a surprising lack of TWS depletion in the Mississippi Embayment aquifer is attributed to extensive streamflow capture. Marked storage depletion in the semi-arid southwestern Central Valley and south-central High Plains totaled ∼90 km3, about three times greater than the capacity of Lake Mead, the largest U.S. reservoir. Depletion in the Central Valley was driven by long-term droughts (⩽5 yr) amplified by switching from mostly surface water to groundwater irrigation. Low or slightly rising TWS trends in the northwestern (Columbia and Snake Basins) US are attributed to dampening drought impacts by mostly surface water irrigation. GRACE satellite data highlight synergies between climate and irrigation, resulting in little impact on TWS in the humid east, amplified TWS depletion in the semi-arid southwest and southcentral US, and dampened TWS deletion in the northwest and north central US Sustainable groundwater management benefits from conjunctive use of surface water and groundwater, inefficient surface water irrigation promoting groundwater recharge, efficient groundwater irrigation minimizing depletion, and increasing managed aquifer recharge. This study has important implications for sustainable water development in many regions globally.

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Pickle Research Campus, Bldg. 130, 10100 Burnet Rd., Austin, TX 78758-4445","active":true,"usgs":false}],"preferred":false,"id":901930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rateb, Ahsraf 0000-0002-8875-1508","orcid":"https://orcid.org/0000-0002-8875-1508","contributorId":337082,"corporation":false,"usgs":false,"family":"Rateb","given":"Ahsraf","affiliations":[{"id":80965,"text":"Bureau of Economic Geology, University of Texas","active":true,"usgs":false}],"preferred":false,"id":901931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pool, Donald R. 0001-1234-4321-0505","orcid":"https://orcid.org/0001-1234-4321-0505","contributorId":337083,"corporation":false,"usgs":false,"family":"Pool","given":"Donald R.","affiliations":[{"id":80967,"text":"Retired USGS, Arizona Water Science Center","active":true,"usgs":false}],"preferred":false,"id":901932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":337084,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":901933,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Save, Himanshu","contributorId":187510,"corporation":false,"usgs":false,"family":"Save","given":"Himanshu","email":"","affiliations":[],"preferred":false,"id":902001,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sun, Alexander Y. 0000-0002-6365-8526","orcid":"https://orcid.org/0000-0002-6365-8526","contributorId":302987,"corporation":false,"usgs":false,"family":"Sun","given":"Alexander","email":"","middleInitial":"Y.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":902002,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Long, Di","contributorId":187511,"corporation":false,"usgs":false,"family":"Long","given":"Di","email":"","affiliations":[],"preferred":false,"id":902003,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fuchs, Brian","contributorId":192359,"corporation":false,"usgs":false,"family":"Fuchs","given":"Brian","email":"","affiliations":[],"preferred":false,"id":902004,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70224608,"text":"70224608 - 2021 - The liquefaction record of past earthquakes in the Central Virginia Seismic Zone, Eastern United States","interactions":[],"lastModifiedDate":"2021-09-30T11:36:07.957997","indexId":"70224608","displayToPublicDate":"2021-06-02T06:33:43","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":"The liquefaction record of past earthquakes in the Central Virginia Seismic Zone, Eastern United States","docAbstract":"

Following the 2011 moment magnitude, M\">MM 5.7 Mineral, Virginia, earthquake, we conducted a search for paleoliquefaction features and found 41 sand dikes, sand sills, and soft‐sediment deformation features at 24 sites exposed in cutbanks along several rivers: (1) the South Anna River, where paleoliquefaction features were found in the epicentral area of the Mineral earthquake and farther downstream to the southeast; (2) the Mattaponi and Pamunkey Rivers east of the Fall Line, where liquefiable sediments are more common than in the epicentral area; and (3) the James River and Rivanna River–Stigger Creek, where a few sand dikes were found in the 1990s. Liquefaction features are grouped into two age categories based on dating of host sediment in which they occur and weathering characteristics of the features. A younger generation of features that formed during the past 350 yr are small, few in number, and appear to be limited to the James and Pamunkey Rivers. Though there are large uncertainties in their locations and magnitudes, one or more preinstrumental earthquakes, including the 1758, 1774, and 1875 events, likely caused these features. An older generation of liquefaction features that formed between 350 and 2800 yr ago are larger, more numerous, and more broadly distributed than the younger generation of features. Several earthquakes could account for the regional distribution of paleoliquefaction features, including one event of M\">MM 6.25–6.5 near Holly Grove, or two events of M\">MM 6.0 near Mineral and M\">MM 6.25 near Ashland. Amplification of ground motions in Coastal Plain sediment might have contributed to liquefaction along the Mattaponi and Pamunkey Rivers.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220200456","usgsCitation":"Tuttle, M.P., Dyer-Williams, K., Carter, M.W., Forman, S.L., Tucker, K., Fuentes, Z., Velez, C., and Bauer, L., 2021, The liquefaction record of past earthquakes in the Central Virginia Seismic Zone, Eastern United States: Seismological Research Letters, v. 92, no. 5, p. 3126-3144, https://doi.org/10.1785/0220200456.","productDescription":"19 p.","startPage":"3126","endPage":"3144","ipdsId":"IP-123694","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":390021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"92","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Tuttle, Martitia P.","contributorId":139388,"corporation":false,"usgs":false,"family":"Tuttle","given":"Martitia","email":"","middleInitial":"P.","affiliations":[{"id":12760,"text":"Tuttle and Associates","active":true,"usgs":false}],"preferred":false,"id":824251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dyer-Williams, Kathleen","contributorId":266054,"corporation":false,"usgs":false,"family":"Dyer-Williams","given":"Kathleen","email":"","affiliations":[{"id":54871,"text":"VanLeen and Associates","active":true,"usgs":false}],"preferred":false,"id":824252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, Mark W. 0000-0003-0460-7638 mcarter@usgs.gov","orcid":"https://orcid.org/0000-0003-0460-7638","contributorId":4808,"corporation":false,"usgs":true,"family":"Carter","given":"Mark","email":"mcarter@usgs.gov","middleInitial":"W.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":824253,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forman, Steven L. 0000-0002-1385-9194","orcid":"https://orcid.org/0000-0002-1385-9194","contributorId":197758,"corporation":false,"usgs":false,"family":"Forman","given":"Steven","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":824254,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tucker, Kathleen","contributorId":194863,"corporation":false,"usgs":false,"family":"Tucker","given":"Kathleen","email":"","affiliations":[],"preferred":false,"id":824255,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fuentes, Zamara","contributorId":195074,"corporation":false,"usgs":false,"family":"Fuentes","given":"Zamara","email":"","affiliations":[],"preferred":false,"id":824256,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Velez, Carlos","contributorId":266055,"corporation":false,"usgs":false,"family":"Velez","given":"Carlos","email":"","affiliations":[{"id":13136,"text":"M. Tuttle & Associates","active":true,"usgs":false}],"preferred":false,"id":824257,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bauer, Laurel","contributorId":266056,"corporation":false,"usgs":false,"family":"Bauer","given":"Laurel","email":"","affiliations":[{"id":54872,"text":"Office of Nuclear Reactor Regulation, U.S. Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":824258,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70221082,"text":"sir20215037 - 2021 - Sediment concentrations and loads upstream from and through John Redmond Reservoir, east-central Kansas, 2010–19","interactions":[],"lastModifiedDate":"2021-06-02T13:05:23.095316","indexId":"sir20215037","displayToPublicDate":"2021-06-02T06:12:32","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":"2021-5037","displayTitle":"Sediment Concentrations and Loads Upstream from and through John Redmond Reservoir, East-Central Kansas, 2010–19","title":"Sediment concentrations and loads upstream from and through John Redmond Reservoir, east-central Kansas, 2010–19","docAbstract":"

Streambank erosion and reservoir sedimentation are primary concerns of resource managers in Kansas and throughout many regions of the United States and negatively affect flood control, water supply, and recreation. The Cottonwood and upper Neosho Rivers drain into John Redmond Reservoir, and since reservoir completion in 1964, there has been substantial conservation-pool sedimentation and storage loss in John Redmond Reservoir, causing storage capacity losses more rapidly than most other Federal reservoirs in Kansas. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office, has monitored water quality (temperature, specific conductance, and turbidity) on the Cottonwood River (upstream from the reservoir) and Neosho River (upstream and downstream from the reservoir) since 2007 with additional sites added in 2009. The purpose of this report is to quantify suspended-sediment concentrations, loads, and yields entering and exiting John Redmond Reservoir during January 1, 2010, through December 31, 2019.

Three water-quality monitoring sites were upstream from the reservoir (Cottonwood River near Plymouth, Kansas [USGS site 07182250; hereinafter referred to as “Cottonwood”]; Neosho River at Burlingame Road near Emporia, Kans. [USGS site 07179750; hereinafter referred to as “Burlingame”]; and Neosho River at Neosho Rapids, Kans. [USGS site 07182390; hereinafter referred to as “Neosho Rapids”]), and one water-quality monitoring site was downstream from the reservoir (Neosho River at Burlington, Kans. [USGS site 07182510; hereinafter referred to as “Burlington”]). The Neosho Rapids streamgage is downstream from the confluence of the Cottonwood and upper Neosho Rivers and has a contributing drainage area accounting for 91 percent of the total contributing drainage area to John Redmond Reservoir.

Continuously measured streamflow, water quality, and discrete water-quality data were used to develop updated regression models to compute suspended-sediment concentrations, loads, and yields upstream and downstream from John Redmond Reservoir in east-central Kansas. Several turbidity sensors were deployed during the analysis period, and there are no established relations between the sensors; therefore, individual models for each sensor were developed. Model statistics for the turbidity and suspended-sediment concentration linear regression models were better (based on the coefficient of determination, root mean square error, and model standard percentage error) than the streamflow and suspended-sediment concentration linear regression models, indicating better model performance. Computed concentrations, loads, and yields do not account for the ungaged 9 percent of the drainage basin downstream from the Neosho Rapids streamgage.

Mean daily suspended-sediment loads upstream from the reservoir were largest at Neosho Rapids (2,250 tons), second largest at Cottonwood (2,180 tons), and smallest at Burlingame (624 tons). Streamflow at Burlington was predominately regulated by reservoir releases, and mean daily suspended-sediment loads were smaller (286 tons) than at upstream sites. Among the upstream sites, Cottonwood had the largest mean daily suspended-sediment concentration (179 milligrams per liter [mg/L]), followed by Neosho Rapids (162 mg/L), and Burlingame (108 mg/L). Burlington had the smallest mean daily suspended-sediment concentration of all sites (46 mg/L).

Annual reservoir trapping efficiency ranged from 82 to 94 percent, and the largest sediment mass trapped was during 2019 (2,230,000 tons). Reservoir storage decreased an estimated 7,750 acre-feet during 2010 and 2014–19. Using the mean trapping efficiency to estimate suspended-sediment loads during years with missing data (2011–13), the total estimated reservoir storage lost to sedimentation for the analysis period (2010–19) was 8,690 acre-feet, about 17 percent of the remaining storage space reported in 2007. The mean annual sedimentation rate during the analysis period (747 acre-feet per year) was about 85 percent larger than the design sedimentation rate (404 acre-feet per year) originally projected during construction. Different reservoir outflow management strategies, including operating near normal capacity as opposed to higher flood pool levels, could reduce the total reservoir storage lost by 3 percent (about 261 acre-feet), which is equal to 14 percent of the total sediment removed during the dredging operation in 2016.

During the study period, about 56 percent of the total suspended-sediment load was transported during streamflows greater than the National Weather Service flood action stage at the upstream sites (0.1–5 percent of the record; Cottonwood mean: 48 percent; Burlingame mean: 40 percent; Neosho Rapids mean: 78 percent). Disproportionately large sediment loads were delivered during short periods of time, and localized efforts of stream erosion protection (streambank stabilization, riparian buffers) were likely to be overwhelmed. Precipitation frequency and intensity are projected to continue to increase in this region; therefore, future sediment reduction strategies that account for extreme episodic events may be beneficial. Changes to reservoir outflow management could also minimize sediment accumulation while still preserving flood control. Continued investigation of sediment reduction measures is necessary for future mitigation with the understanding that sedimentation rate is largely driven by high flows. Results from this study can be used to calibrate sediment models, explore sediment reduction strategies, highlight the importance of continued water-quality monitoring to determine effectiveness and changes in sediment transport, and assess the ability of John Redmond Reservoir to support designated uses into the future.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215037","collaboration":"Prepared in cooperation with the Kansas Water Office","usgsCitation":"Kramer, A.R., Peterman-Phipps, C.L., Mahoney, M.D., and Lukasz, B.S., 2021, Sediment concentrations and loads upstream from and through John Redmond Reservoir, east-central Kansas, 2010–19: U.S. Geological Survey Scientific Investigations Report 2021–5037, 49 p., https://doi.org/10.3133/sir20215037.","productDescription":"Report: ix, 50 p; Appendixes: 12; Dataset","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-119997","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":386084,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix09.pdf","text":"Appendix 9","size":"457 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 9","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182250, Cottonwood River near Plymouth, Kansas, during January 1, 2010, through December 31, 2019"},{"id":386074,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5037/coverthb.jpg"},{"id":386075,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037.pdf","text":"Report","size":"3.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037"},{"id":386076,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix01.pdf","text":"Appendix 1","size":"408 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 1","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182250, Cottonwood River near Plymouth, Kansas, during January 1, 2010, through April 22, 2015"},{"id":386078,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix03.pdf","text":"Appendix 3","size":"432 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 3","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182390, Neosho River at Neosho Rapids, Kansas, during January 1, 2010, through September 24, 2015"},{"id":386079,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix04.pdf","text":"Appendix 4","size":"455 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 4","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182510, Neosho River at Burlington, Kansas, during January 1, 2010, through October 16, 2015"},{"id":386088,"rank":15,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":386087,"rank":14,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix12.pdf","text":"Appendix 12","size":"451 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 12","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182510, Neosho River at Burlington, Kansas, during January 1, 2010, through December 31, 2019"},{"id":386086,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix11.pdf","text":"Appendix 11","size":"449 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 11","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182390, Neosho River at Neosho Rapids, Kansas, during January 1, 2010, through December 31, 2019"},{"id":386083,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix08.pdf","text":"Appendix 8","size":"427 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 8","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182510, Neosho River at Burlington, Kansas, during October 23, 2015, through December 31, 2019"},{"id":386082,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix07.pdf","text":"Appendix 7","size":"391 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 7","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182390, Neosho River at Neosho Rapids, Kansas, during November 13, 2015, through December 31, 2019"},{"id":386085,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix10.pdf","text":"Appendix 10","size":"418 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 10","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07179750, Neosho River at Burlingame Road near Emporia, Kansas, during January 1, 2010, through December 31, 2019"},{"id":386080,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix05.pdf","text":"Appendix 5","size":"376 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 5","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182250, Cottonwood River near Plymouth, Kansas, during April 22, 2015, through December 31, 2019"},{"id":386081,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix06.pdf","text":"Appendix 6","size":"399 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 6","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07179750, Neosho River at Burlingame Road near Emporia, Kansas, during May 2, 2015, through December 31, 2019"},{"id":386077,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5037/sir20215037_appendix02.pdf","text":"Appendix 2","size":"414 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5037 Appendix 2","linkHelpText":"— Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07179750, Neosho River at Burlingame Road near Emporia, Kansas, during January 1, 2010, through December 16, 2012"}],"country":"United States","state":"Kansas","otherGeospatial":"John Redmond Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.52838134765624,\n 38.01131226070673\n ],\n [\n -95.49041748046875,\n 38.01131226070673\n ],\n [\n -95.49041748046875,\n 39.27266344858914\n ],\n [\n -97.52838134765624,\n 39.27266344858914\n ],\n [\n -97.52838134765624,\n 38.01131226070673\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-06-02","noUsgsAuthors":false,"publicationDate":"2021-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Kramer, Ariele R. 0000-0002-7075-3310 akramer@usgs.gov","orcid":"https://orcid.org/0000-0002-7075-3310","contributorId":185245,"corporation":false,"usgs":true,"family":"Kramer","given":"Ariele","email":"akramer@usgs.gov","middleInitial":"R.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":816715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterman-Phipps, Cara L. 0000-0003-1822-2552","orcid":"https://orcid.org/0000-0003-1822-2552","contributorId":259166,"corporation":false,"usgs":true,"family":"Peterman-Phipps","given":"Cara","email":"","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":816716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mahoney, Matthew D. 0000-0002-9008-7132","orcid":"https://orcid.org/0000-0002-9008-7132","contributorId":206054,"corporation":false,"usgs":true,"family":"Mahoney","given":"Matthew","email":"","middleInitial":"D.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":816717,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lukasz, Bradley S. 0000-0001-5438-5901","orcid":"https://orcid.org/0000-0001-5438-5901","contributorId":225021,"corporation":false,"usgs":true,"family":"Lukasz","given":"Bradley","email":"","middleInitial":"S.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":816718,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221885,"text":"70221885 - 2021 - Multivariate classification of the crude oil petroleum systems in southeast Texas, USA, using conventional and compositional data analysis of biomarkers","interactions":[],"lastModifiedDate":"2021-07-13T18:57:42.166406","indexId":"70221885","displayToPublicDate":"2021-06-01T13:53:23","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Multivariate classification of the crude oil petroleum systems in southeast Texas, USA, using conventional and compositional data analysis of biomarkers","docAbstract":"

Chemically, petroleum is an extraordinarily complex mixture of different types of hydrocarbons that are now possible to isolate and identify because of advances in geochemistry. Here, we use biomarkers and carbon isotopes to establish genetic differences and similarities among oil samples. Conventional approaches for evaluating biomarker and carbon isotope relative abundances include statistical techniques such as principal component and cluster analysis. Considering that proportions of the different hydrocarbon molecules are relative parts of a laboratory sample, the data are compositional in nature, thus requiring the use of log-ratio approaches for adequate mathematical modeling. We apply both traditional and compositional modeling approaches to crude oil samples from an onshore area of about 50,000 square miles in southeast Texas. The data comprise 177 crude oil samples from producing oil fields that include key biomarkers, elemental, and isotopic values commonly used in source rock correlation studies. Our results indicate that compositional modeling has higher discriminating power and lower uncertainty than the traditional approach, allowing the identification of up to 16 clusters. Each cluster represents one oil family from a source rock organofacies ranging from Carboniferous to Paleogene. The families provide new insights into important petroleum systems in the Texas onshore region of the Gulf of Mexico sedimentary basin.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Advances in compositional data analysis—Festschrift in honor of Vera-Pawlowsky-Glahn","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-71175-7_16","usgsCitation":"Olea, R., Martin-Fernandez, J.A., and Craddock, W.H., 2021, Multivariate classification of the crude oil petroleum systems in southeast Texas, USA, using conventional and compositional data analysis of biomarkers, chap. of Advances in compositional data analysis—Festschrift in honor of Vera-Pawlowsky-Glahn, p. 303-307, https://doi.org/10.1007/978-3-030-71175-7_16.","productDescription":"5 p.","startPage":"303","endPage":"307","ipdsId":"IP-112995","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":387163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.119140625,\n 25.97779895546436\n ],\n [\n -96.767578125,\n 27.68352808378776\n ],\n [\n -95.11962890625,\n 28.497660832963472\n ],\n [\n -93.8232421875,\n 29.49698759653577\n ],\n [\n -93.97705078125,\n 30.20211367909724\n ],\n [\n -95.55908203125,\n 30.240086360983426\n ],\n [\n -97.3388671875,\n 28.9600886880068\n ],\n [\n -98.23974609375,\n 27.586197857692664\n ],\n [\n -97.91015624999999,\n 26.13571361317392\n ],\n [\n -97.119140625,\n 25.97779895546436\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-06-02","publicationStatus":"PW","contributors":{"editors":[{"text":"Fitzmoser, Peter","contributorId":261055,"corporation":false,"usgs":false,"family":"Fitzmoser","given":"Peter","email":"","affiliations":[],"preferred":false,"id":819247,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Hron, Karel","contributorId":261056,"corporation":false,"usgs":false,"family":"Hron","given":"Karel","email":"","affiliations":[],"preferred":false,"id":819248,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Martin-Fernandez, Josep Antoni","contributorId":208528,"corporation":false,"usgs":false,"family":"Martin-Fernandez","given":" Josep Antoni","affiliations":[],"preferred":false,"id":819249,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Palarea-Albaladejo, Javier","contributorId":120518,"corporation":false,"usgs":true,"family":"Palarea-Albaladejo","given":"Javier","email":"","affiliations":[],"preferred":false,"id":819250,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":224285,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":819213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin-Fernandez, J. A 0000-0003-2366-1592","orcid":"https://orcid.org/0000-0003-2366-1592","contributorId":260957,"corporation":false,"usgs":false,"family":"Martin-Fernandez","given":"J.","email":"","middleInitial":"A","affiliations":[{"id":28183,"text":"University of Girona","active":true,"usgs":false}],"preferred":false,"id":819214,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Craddock, William H. 0000-0002-4181-4735 wcraddock@usgs.gov","orcid":"https://orcid.org/0000-0002-4181-4735","contributorId":3411,"corporation":false,"usgs":true,"family":"Craddock","given":"William","email":"wcraddock@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":819215,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229659,"text":"70229659 - 2021 - Greater Yellowstone climate assessment: Past, present, and future climate change in the greater Yellowstone watersheds","interactions":[],"lastModifiedDate":"2022-03-15T15:41:13.424217","indexId":"70229659","displayToPublicDate":"2021-06-01T11:57:17","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":10388,"text":"Greater Yellowstone Climate Assessment","active":true,"publicationSubtype":{"id":3}},"title":"Greater Yellowstone climate assessment: Past, present, and future climate change in the greater Yellowstone watersheds","docAbstract":"

The Greater Yellowstone Area (GYA) is one of the last remaining large and nearly intact temperate ecosystems on Earth. GYA was originally defined in the 1970s as the Greater Yellowstone Ecosystem, which encompassed the minimum range of the grizzly bear. The boundary now includes about 22 million acres (8.9 million ha) in northwestern Wyoming, south central Montana, and eastern Idaho (Figure ES-1). Two national parks, five national forests, three wildlife refuges, 20 counties, and state and private lands lie within the GYA boundary (Figure ES-1). The Tribal Nations of the Eastern Shoshone, Northern Arapaho, Apsa´alooke/Crow, Northern Cheyenne, Shoshone, and Bannock have reservations in and near the Greater Yellowstone Area, and 27 Tribes are formally recognized to have historical connections to the lands and resources of the region. Natural resources sensitive to climate change connect many of the major economic activities of the GYA, including tourism and recreation, agriculture, and energy development.

","language":"English","publisher":"Montana State University","doi":"10.15788/GYCA2021","usgsCitation":"Hostetler, S.W., Whitlock, C., Shuman, B., Liefert, D., Wolf Drimal, C., and Bischke, S., 2021, Greater Yellowstone climate assessment: Past, present, and future climate change in the greater Yellowstone watersheds: Greater Yellowstone Climate Assessment, 218 p., https://doi.org/10.15788/GYCA2021.","productDescription":"218 p.","ipdsId":"IP-127170","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":452032,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15788/gyca2021","text":"Publisher Index Page"},{"id":436330,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P972JAUC","text":"USGS data release","linkHelpText":"Data release for Greater Yellowstone Climate Assessment (vol 1), Chapter 7. Future Water Projections for the GYA"},{"id":397116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone watersheds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.54394531249999,\n 42.09822241118974\n ],\n [\n -108.2373046875,\n 42.09822241118974\n ],\n [\n -108.2373046875,\n 45.9511496866914\n ],\n [\n -112.54394531249999,\n 45.9511496866914\n ],\n [\n -112.54394531249999,\n 42.09822241118974\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-06-23","publicationStatus":"PW","contributors":{"editors":[{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":837847,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":837848,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":837841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whitlock, Cathy","contributorId":79745,"corporation":false,"usgs":false,"family":"Whitlock","given":"Cathy","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":837842,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shuman, Bryan","contributorId":205232,"corporation":false,"usgs":false,"family":"Shuman","given":"Bryan","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":837843,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liefert, David 0000-0001-7682-6835","orcid":"https://orcid.org/0000-0001-7682-6835","contributorId":288395,"corporation":false,"usgs":false,"family":"Liefert","given":"David","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":837844,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolf Drimal, Charles","contributorId":288398,"corporation":false,"usgs":false,"family":"Wolf Drimal","given":"Charles","email":"","affiliations":[{"id":61749,"text":"Greater Yellowstone Coalition","active":true,"usgs":false}],"preferred":false,"id":837845,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bischke, Scott","contributorId":288399,"corporation":false,"usgs":false,"family":"Bischke","given":"Scott","email":"","affiliations":[{"id":61752,"text":"Mountain Works","active":true,"usgs":false}],"preferred":false,"id":837846,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229042,"text":"70229042 - 2021 - Diel patterns of predation and fledging at nests of four species of grassland songbirds","interactions":[],"lastModifiedDate":"2022-02-28T17:09:30.743422","indexId":"70229042","displayToPublicDate":"2021-06-01T10:56:56","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":"Diel patterns of predation and fledging at nests of four species of grassland songbirds","docAbstract":"

Although it is common for nestlings to exhibit a strong bias for fledging in the morning, the mechanisms underlying this behavior are not well understood. Avoiding predation risk has been proposed as a likely mechanism by a number of researchers. We used video surveillance records from studies of grassland birds nesting in North Dakota, Minnesota, and Wisconsin to determine the diel pattern of nest predation and fledging patterns of four ground-nesting obligate grassland passerines (Grasshopper Sparrow (Ammodramus savannarum), Savannah Sparrow (Passerculus sandwichensis), Bobolink (Dolichonyx oryzivorus), and Eastern Meadowlark (Sturnella magna)). We used the nest predation pattern as a surrogate for predation activity to test whether nestlings minimized predation risk by avoiding fledging when predation activity was high and preferentially fledging when predation risk was low. Predation activity was significantly lower starting 3 hr before sunrise and ending 3 hr after sunrise, followed by a transition to a period of significantly higher activity lasting for 4 hr, before declining to an average activity level for the rest of the diel period. There was little evidence that the four grassland bird species avoided fledging during the high-risk period and Savannah Sparrow fledged at higher rates during that period. All four species had hours during the low-risk period where they fledged at higher rates, but only Grasshopper Sparrow fledged preferentially during that period. Bobolink and Eastern Meadowlark had multiple hours with high fledging rates throughout the daytime period, resulting in no relationship between probability of fledging and predation risk. Given the species variability in fledging pattern seen in our study, it is unlikely that there is a universal response to any driver that affects time of fledging. Further study is needed to understand the complex interplay between species ecology and drivers such as physiology, energetics, and predation in affecting grassland bird fledging behavior.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7541","usgsCitation":"Ribic, C., Rugg, D.J., Ellison, K., Koper, N., and Pietz, P.J., 2021, Diel patterns of predation and fledging at nests of four species of grassland songbirds: Ecology and Evolution, v. 11, no. 11, p. 6913-6926, https://doi.org/10.1002/ece3.7541.","productDescription":"14 p.","startPage":"6913","endPage":"6926","ipdsId":"IP-120613","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":452037,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.7541","text":"Publisher Index Page"},{"id":396566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, North Dakota, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.085693359375,\n 46.707852594536355\n ],\n [\n -98.31390380859375,\n 46.707852594536355\n ],\n [\n -98.31390380859375,\n 47.04766864046083\n ],\n [\n -99.085693359375,\n 47.04766864046083\n ],\n [\n -99.085693359375,\n 46.707852594536355\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.49630737304688,\n 47.05983195515023\n ],\n [\n -99.08843994140625,\n 47.05983195515023\n ],\n [\n -99.08843994140625,\n 47.24381345414034\n ],\n [\n -99.49630737304688,\n 47.24381345414034\n ],\n [\n -99.49630737304688,\n 47.05983195515023\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.00830078125,\n 48.50295743049266\n ],\n [\n -100.43289184570312,\n 48.50295743049266\n ],\n [\n -100.43289184570312,\n 48.672826384100354\n ],\n [\n -101.00830078125,\n 48.672826384100354\n ],\n [\n -101.00830078125,\n 48.50295743049266\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.7730712890625,\n 47.711609647845975\n ],\n [\n -96.4874267578125,\n 47.711609647845975\n ],\n [\n -96.4874267578125,\n 47.830674012109434\n ],\n [\n -96.7730712890625,\n 47.830674012109434\n ],\n [\n -96.7730712890625,\n 47.711609647845975\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.80361938476562,\n 42.96245265666877\n ],\n [\n -89.68276977539062,\n 42.96245265666877\n ],\n [\n -89.68276977539062,\n 43.04881979669318\n ],\n [\n -89.80361938476562,\n 43.04881979669318\n ],\n [\n -89.80361938476562,\n 42.96245265666877\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":836346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rugg, David J.","contributorId":171931,"corporation":false,"usgs":false,"family":"Rugg","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":836347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellison, Kevin","contributorId":274390,"corporation":false,"usgs":false,"family":"Ellison","given":"Kevin","affiliations":[{"id":37767,"text":"World Wildlife Fund","active":true,"usgs":false}],"preferred":false,"id":836348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koper, Nicola","contributorId":274389,"corporation":false,"usgs":false,"family":"Koper","given":"Nicola","affiliations":[{"id":16603,"text":"University of Manitoba","active":true,"usgs":false}],"preferred":false,"id":836349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pietz, Pamela J. 0000-0003-4606-044X","orcid":"https://orcid.org/0000-0003-4606-044X","contributorId":286892,"corporation":false,"usgs":true,"family":"Pietz","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":836350,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221396,"text":"70221396 - 2021 - A survey of storm-induced seaward-transport features observed during the 2019 and 2020 hurricane seasons","interactions":[],"lastModifiedDate":"2021-06-14T12:56:49.325445","indexId":"70221396","displayToPublicDate":"2021-06-01T07:54:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8932,"text":"Shore and Beach","active":true,"publicationSubtype":{"id":10}},"title":"A survey of storm-induced seaward-transport features observed during the 2019 and 2020 hurricane seasons","docAbstract":"Hurricanes are known to play a critical role in reshaping coastlines, but often only impacts on the open ocean coast are considered, ignoring seaward-directed forces and responses. The identification of subaerial evidence for storm-induced seaward transport is a critical step towards understanding its impact on coastal resiliency. The visual features, found in the National Oceanic and Atmospheric Administration, National Geodetic Survey Emergency Response Imagery (ERI) collected after recent hurricanes on the U.S. East Atlantic and Gulf of Mexico coasts, include scours and channelized erosion, but also deposition on the shoreface or in the nearshore as deltas and fans of various sizes. We catalog all available ERI and describe recently formed features found on the North Core Banks, North Carolina, after Hurricane Dorian (2019); the Carolina coasts after Hurricane Isaias (2020); the Isles Dernieres, Louisiana, after Hurricane Zeta (2020); and the southwest coast of Louisiana, after Hurricanes Laura and Delta (2020). Hundreds of features were identified over nearly 200 km of coastline with the density of features exceeding 20 per km in some areas. Individual features range in size from 5 m to 500 m in the alongshore, with similar dimensions in the cross-shore direction, including the formation or reactivation of outlets. The extensive occurrence of these storm-induced return-flow and seawardflow morphologic features demonstrates that their role in coastal evolution and resilience may be more prominent than previously thought. Based on these observations we propose clarifying terms for return- and seaward-flow features to distinguish them from more frequently documented landward-flow features and advocate for their inclusion in coastal change hazards classification schemes and coastal evolution morphodynamic models.","language":"English","publisher":"American Shore & Beach Preservation Association","doi":"10.34237/1008924","usgsCitation":"Over, J.R., Brown, J., Sherwood, C.R., Hegermiller, C., Wernette, P., Ritchie, A.C., and Warrick, J.A., 2021, A survey of storm-induced seaward-transport features observed during the 2019 and 2020 hurricane seasons: Shore and Beach, v. 89, no. 2, p. 31-40, https://doi.org/10.34237/1008924.","productDescription":"10 p.","startPage":"31","endPage":"40","ipdsId":"IP-126879","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":452060,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.31223/x5dp69","text":"External Repository"},{"id":386467,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"southeast United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.306640625,\n 25.005972656239187\n ],\n [\n -75.146484375,\n 25.005972656239187\n ],\n [\n -75.146484375,\n 36.59788913307022\n ],\n [\n -94.306640625,\n 36.59788913307022\n ],\n [\n -94.306640625,\n 25.005972656239187\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"89","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Over, Jin-Si R. 0000-0001-6753-7185 jover@usgs.gov","orcid":"https://orcid.org/0000-0001-6753-7185","contributorId":260178,"corporation":false,"usgs":true,"family":"Over","given":"Jin-Si","email":"jover@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Jenna A. 0000-0003-3137-7073","orcid":"https://orcid.org/0000-0003-3137-7073","contributorId":208564,"corporation":false,"usgs":true,"family":"Brown","given":"Jenna A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hegermiller, Christie 0000-0002-6383-7508 chegermiller@usgs.gov","orcid":"https://orcid.org/0000-0002-6383-7508","contributorId":149010,"corporation":false,"usgs":true,"family":"Hegermiller","given":"Christie","email":"chegermiller@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wernette, Phillipe Alan 0000-0002-8902-5575","orcid":"https://orcid.org/0000-0002-8902-5575","contributorId":259274,"corporation":false,"usgs":true,"family":"Wernette","given":"Phillipe Alan","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817514,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ritchie, Andrew C. aritchie@usgs.gov","contributorId":4984,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","email":"aritchie@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817515,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817516,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70222051,"text":"70222051 - 2021 - Ecological effects of climate-driven salinity variation in the San Francisco Estuary: Can we anticipate and manage the coming changes?","interactions":[],"lastModifiedDate":"2021-07-15T20:45:26.524443","indexId":"70222051","displayToPublicDate":"2021-05-31T15:39:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Ecological effects of climate-driven salinity variation in the San Francisco Estuary: Can we anticipate and manage the coming changes?","docAbstract":"

Climate change-driven sea level rise and altered precipitation regimes are predicted to alter patterns of salt intrusion within the San Francisco Estuary. A central question is: Can we use existing knowledge and future projections to predict and manage the anticipated ecological impacts? This was the subject of a 2018 symposium entitled “Ecological and Physiological Impacts of Salinization of Aquatic Systems from Human Activities.” The symposium brought together an inter-disciplinary group of scientists and researchers, resource managers, and policy-makers. Here, we summarize and review the presentations and discussions that arose during the symposium. From a historical perspective, salt intrusion has changed substantially over the past 10,000 years as a result of changing climate patterns, with additional shifts from recent anthropogenic effects. Current salinity patterns in the San Francisco Estuary are driven by a suite of hydrodynamic processes within the given contexts of water management and geography. Based on climate projections for the coming century, significant changes are expected in the processes that determine the spatial and temporal patterns of salinity. Given that native species—including fishes such as the Delta Smelt and Sacramento Splittail—track favorable habitats, exhibit physiological acclimation, and can adaptively evolve, we present a framework for assessing their vulnerability to altered salinity in the San Francisco Estuary. We then present a range of regulatory and structural management tools that are available to control patterns of salinity within the San Francisco Estuary. Finally, we identify major research priorities that can help fill critical gaps in our knowledge about future salinity patterns and the consequences of climate change and sea level rise. These research projects will be most effective with strong linkages and communication between scientists and researchers, resource managers, and policy-makers.

","language":"English","publisher":"John Muir Institute of the Environment","doi":"10.15447/sfews.2021v19iss2art3","usgsCitation":"Chalambor, C.K., Gross, E.S., Grosholz, E., Jeffries, K.M., Largier, J.L., McCormick, S.D., Sommer, T., Velotta, J., and Whitehead, A., 2021, Ecological effects of climate-driven salinity variation in the San Francisco Estuary: Can we anticipate and manage the coming changes?: San Francisco Estuary and Watershed Science, v. 19, no. 2, https://doi.org/10.15447/sfews.2021v19iss2art3.","productDescription":"3, 30 p.","startPage":"article 3","ipdsId":"IP-120646","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":452067,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2021v19iss2art3","text":"Publisher Index Page"},{"id":387198,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.56347656249999,\n 37.208456662000195\n ],\n [\n -120.904541015625,\n 37.208456662000195\n ],\n [\n -120.904541015625,\n 38.749799358878526\n ],\n [\n -122.56347656249999,\n 38.749799358878526\n ],\n [\n -122.56347656249999,\n 37.208456662000195\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Chalambor, Cameron K","contributorId":261131,"corporation":false,"usgs":false,"family":"Chalambor","given":"Cameron","email":"","middleInitial":"K","affiliations":[{"id":52741,"text":"Colorado State Univ","active":true,"usgs":false}],"preferred":false,"id":819305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gross, Edward S.","contributorId":173128,"corporation":false,"usgs":false,"family":"Gross","given":"Edward","email":"","middleInitial":"S.","affiliations":[{"id":16871,"text":"Resource Management Associates","active":true,"usgs":false}],"preferred":false,"id":819307,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grosholz, Edwin D.","contributorId":171563,"corporation":false,"usgs":false,"family":"Grosholz","given":"Edwin D.","affiliations":[],"preferred":false,"id":819306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jeffries, Ken M","contributorId":261132,"corporation":false,"usgs":false,"family":"Jeffries","given":"Ken","email":"","middleInitial":"M","affiliations":[{"id":52742,"text":"Univ Manitoba","active":true,"usgs":false}],"preferred":false,"id":819308,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Largier, John L.","contributorId":175121,"corporation":false,"usgs":false,"family":"Largier","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":819309,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":819310,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sommer, Ted","contributorId":256830,"corporation":false,"usgs":false,"family":"Sommer","given":"Ted","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":819311,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Velotta, Jonathan P","contributorId":192317,"corporation":false,"usgs":false,"family":"Velotta","given":"Jonathan P","affiliations":[],"preferred":false,"id":819312,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Whitehead, Andrew","contributorId":221105,"corporation":false,"usgs":false,"family":"Whitehead","given":"Andrew","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":819313,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70221053,"text":"70221053 - 2021 - Perfluoroalkyl substances in plasma of smallmouth bass from the Chesapeake Bay Watershed","interactions":[],"lastModifiedDate":"2021-07-02T13:32:14.906126","indexId":"70221053","displayToPublicDate":"2021-05-30T06:57:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2041,"text":"International Journal of Environmental Research and Public Health","active":true,"publicationSubtype":{"id":10}},"title":"Perfluoroalkyl substances in plasma of smallmouth bass from the Chesapeake Bay Watershed","docAbstract":"

Smallmouth bass Micropterus dolomieu is an economically important sportfish and within the Chesapeake Bay watershed has experienced a high prevalence of external lesions, infectious disease, mortality events, reproductive endocrine disruption and population declines. To date, no clear or consistent associations with contaminants measured in fish tissue or surface water have been found. Therefore, plasma samples from two sites in the Potomac River and two in the Susquehanna River drainage basins, differing in land-use characteristics, were utilized to determine if perfluoroalkyl substances were present. Four compounds, perfluorooctane sulphonic acid (PFOS), perfluoroundecanoic acid (PFUnA), perfluorodecanoic acid (PFDA) and perfluorododecanoic acid (PFDoA), were detected in every fish. Two additional compounds, perfluorooctane sulphonamide (PFOSA) and perfluorononanoic acid (PFNA), were less commonly detected at lower concentrations, depending on the site. Concentrations of PFOS (up to 574 ng/mL) were the highest detected and varied significantly among sites. No seasonal differences (spring versus fall) in plasma concentrations were observed. Concentrations of PFOS were not significantly different between the sexes. However, PFUnA and PFDoA concentrations were higher in males than females. Both agricultural and developed land-use appeared to be associated with exposure. Further research is needed to determine if these compounds could be affecting the health of smallmouth bass and identify sources.

","language":"English","publisher":"MDPI","doi":"10.3390/ijerph18115881","usgsCitation":"Blazer, V., Gordon, S.E., Walsh, H.L., and Smith, C.R., 2021, Perfluoroalkyl substances in plasma of smallmouth bass from the Chesapeake Bay Watershed: International Journal of Environmental Research and Public Health, v. 11, no. 18, 5881, 13 p., https://doi.org/10.3390/ijerph18115881.","productDescription":"5881, 13 p.","ipdsId":"IP-126689","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":452074,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ijerph18115881","text":"Publisher Index Page"},{"id":436331,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H8DW78","text":"USGS data release","linkHelpText":"Morphometric, Age and Concentrations of Perfluoroalkyl Substances in Smallmouth Bass Plasma from Four Sites in the Chesapeake Bay 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],\n [\n -76.190185546875,\n 36.66841891894786\n ],\n [\n -76.0693359375,\n 36.65079252503471\n ],\n [\n -75.9375,\n 36.66841891894786\n ],\n [\n -75.948486328125,\n 36.76529191711624\n ],\n [\n -75.904541015625,\n 37.01132594307015\n ],\n [\n -75.926513671875,\n 37.17782559332976\n ],\n [\n -75.882568359375,\n 37.42252593456307\n ],\n [\n -75.618896484375,\n 37.640334898059486\n ],\n [\n -75.509033203125,\n 37.82280243352756\n ],\n [\n -75.38818359375,\n 38.013476231041935\n ],\n [\n -75.16845703124999,\n 38.272688535980976\n ],\n [\n -75.1904296875,\n 38.41916639395372\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"18","noUsgsAuthors":false,"publicationDate":"2021-05-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":816653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gordon, Stephanie E. 0000-0002-6292-2612 sgordon@usgs.gov","orcid":"https://orcid.org/0000-0002-6292-2612","contributorId":200931,"corporation":false,"usgs":true,"family":"Gordon","given":"Stephanie","email":"sgordon@usgs.gov","middleInitial":"E.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":816654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":816655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Cheyenne R. 0000-0002-7226-1774","orcid":"https://orcid.org/0000-0002-7226-1774","contributorId":219236,"corporation":false,"usgs":true,"family":"Smith","given":"Cheyenne","email":"","middleInitial":"R.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":816656,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220727,"text":"sir20215028 - 2021 - Flow characteristics and salinity patterns in tidal rivers within the northern Ten Thousand Islands, southwest Florida, water years 2007–19","interactions":[],"lastModifiedDate":"2021-05-27T11:52:45.64841","indexId":"sir20215028","displayToPublicDate":"2021-05-26T13:37:00","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":"2021-5028","displayTitle":"Flow Characteristics and Salinity Patterns in Tidal Rivers Within the Northern Ten Thousand Islands, Southwest Florida, Water Years 2007–19","title":"Flow characteristics and salinity patterns in tidal rivers within the northern Ten Thousand Islands, southwest Florida, water years 2007–19","docAbstract":"

Freshwater flow to the Ten Thousand Islands (TTI) estuary has been altered by the construction of the Tamiami Trail and construction of features in the now defunct Southern Golden Gate Estates development. This development included four associated canals that combine into the Faka Union Canal, which discharges into the TTI estuary. The Picayune Strand Restoration Project (PSRP) was initiated in 2007 to improve freshwater delivery to the TTI estuary by removing hundreds of miles of roads, emplacing hundreds of canal plugs, removing exotic vegetation, and constructing three pump stations. Quantifying the tributary flows and salinity patterns prior to, during, and after the restoration is essential to assessing the effectiveness of upstream restoration efforts. The U.S. Geological Survey, in cooperation with U.S. Army Corps of Engineers, initiated an ongoing study in 2006 to assess flow and salinity patterns in the TTI estuary. This is the second report by the U.S. Geological Survey describing flow characteristics and salinity patterns in the TTI area as part of the PSRP. This report describes flow characteristics and salinity patterns for the monitoring stations at Faka Union River, Pumpkin River, and East River and includes an assessment of salinity data from the Faka Union Boundary and Blackwater River water-quality stations for water years 2007–19. A water year is defined as the 12-month period from October 1 for any given year to September 30 of the following year.

Annual and monthly variations in flow and salinity are often related to variations in rainfall with high and low annual flows (and below average and above average salinities) typically occurring during years with high and low annual rainfall, respectively. Monthly flows typically begin increasing in June and peak in September. Over the study period, positive trends in rainfall-adjusted monthly flow were detected at Faka Union River and East River, whereas no significant trend in flow was detected at Pumpkin River. Faka Union River is the largest contributor of freshwater to the TTI estuary, providing over 80 percent of the annual freshwater inflow to the estuary. The Faka Union Canal is expected to be the largest contributor of freshwater because until the PSRP is completed, the Faka Union Canal receives substantial drainage from multiple canals, which is not the case for Pumpkin and East Rivers. East River was the second largest contributor, followed by Pumpkin River. East River is downstream of the Fakahatchee Stand, which is a larger contributing area than the current contributing area for Pumpkin River. Monthly mean salinities were lowest at Faka Union River and East River, indicating that they received a greater amount of freshwater than the stations to the west. Negative trends in rainfall-adjusted salinity monthly means were observed at all monitoring stations during the study period. Increased trends in flow and decreased trends in salinity are attributed to increases in flow from upstream canals.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215028","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Booth, A.C., and Knight, T.M., 2021, Flow characteristics and salinity patterns in tidal rivers within the northern Ten Thousand Islands, southwest Florida, water years 2007–19: U.S. Geological Survey Scientific Investigations Report 2021–5028, 21 p., https://doi.org/10.3133/sir20215028.","productDescription":"vii, 21 p.","numberOfPages":"34","ipdsId":"IP-122818","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":385935,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5028/images"},{"id":385934,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5028/sir20215028.pdf","text":"Report","size":"4.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5028"},{"id":385933,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5028/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Northern Ten Thousand Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.67304992675781,\n 25.852426562716428\n ],\n [\n -81.47941589355469,\n 25.852426562716428\n ],\n [\n -81.47941589355469,\n 25.972243398901558\n ],\n [\n -81.67304992675781,\n 25.972243398901558\n ],\n [\n -81.67304992675781,\n 25.852426562716428\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Caribbean-Florida Water Science Center (CFWSC)
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2021-05-26","noUsgsAuthors":false,"publicationDate":"2021-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Booth, Amanda C. 0000-0002-2666-2366 acbooth@usgs.gov","orcid":"https://orcid.org/0000-0002-2666-2366","contributorId":258448,"corporation":false,"usgs":true,"family":"Booth","given":"Amanda C.","email":"acbooth@usgs.gov","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knight, Travis M. 0000-0002-0472-8141 tknight@usgs.gov","orcid":"https://orcid.org/0000-0002-0472-8141","contributorId":5433,"corporation":false,"usgs":true,"family":"Knight","given":"Travis","email":"tknight@usgs.gov","middleInitial":"M.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":816444,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70230073,"text":"70230073 - 2021 - Onset and evolution of Kilauea’s 2018 flank eruption and summit collapse from continuous gravity","interactions":[],"lastModifiedDate":"2022-03-28T13:19:34.266653","indexId":"70230073","displayToPublicDate":"2021-05-25T08:14:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Onset and evolution of Kīlauea's 2018 flank eruption and summit collapse from continuous gravity","title":"Onset and evolution of Kilauea’s 2018 flank eruption and summit collapse from continuous gravity","docAbstract":"

Prior to the 2018 lower East Rift Zone (ERZ) eruption and summit collapse of Kīlauea Volcano, Hawai‘i, continuous gravimeters operated on the vent rims of ongoing eruptions at both the summit and Pu‘u ‘Ō‘ō. These instruments captured the onset of the 2018 lower ERZ eruption and the effects of lava withdrawal from both locales, providing constraints on the timing and style of activity and the physical properties of the lava lakes at both locations. At the summit, combining gravity, lava level, and a three-dimensional model of the vent indicates that the upper ∼200 m of the lava lake had a density of about 1700 kg m−3, slightly greater than estimates from 2011–2015 and possibly indicating a gradual densification over time. At Pu‘u ‘Ō‘ō, gravity and vent geometry were used to model both the density and the rate of crater collapse, which was unknown owing to a lack of visual observations. Results suggest the withdrawal of at least 11×106 m3 of lava over the course of two hours, and a material density of 1800–1900 kg m−3. In addition, gravity data at Pu‘u ‘Ō‘ō captured a transient decrease and increase about an hour prior to crater collapse and that was probably related to a small, short-lived fissure eruption on the west flank of the cone and possibly to dike intrusion beneath Pu‘u ‘Ō‘ō. The fissure was the first event in the subsequent cascade that ultimately led to the extrusion of over 1 km3 of lava from lower ERZ vents, collapse of the summit caldera floor by more than 500 m, and the destruction of over 700 homes and other structures. These results emphasize the importance of continuous gravity in operational monitoring of active volcanoes.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2021.117003","usgsCitation":"Poland, M., Carbone, D., and Patrick, M.R., 2021, Onset and evolution of Kilauea’s 2018 flank eruption and summit collapse from continuous gravity: Earth and Planetary Science Letters, v. 567, 117003, 12 p., https://doi.org/10.1016/j.epsl.2021.117003.","productDescription":"117003, 12 p.","ipdsId":"IP-123201","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":452142,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2021.117003","text":"Publisher Index Page"},{"id":436343,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99QB29I","text":"USGS data release","linkHelpText":"Crater geometry data for Puʻuʻōʻō, on Kīlauea Volcano’s East Rift Zone, in May 2018"},{"id":436342,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PP5LX1","text":"USGS data release","linkHelpText":"Continuous gravity data from K?lauea Volcano, Hawai?i"},{"id":397686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.40985107421875,\n 19.158141038187704\n ],\n [\n -154.78912353515625,\n 19.158141038187704\n ],\n [\n -154.78912353515625,\n 19.557202031700292\n ],\n [\n -155.40985107421875,\n 19.557202031700292\n ],\n [\n -155.40985107421875,\n 19.158141038187704\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"567","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Poland, Michael 0000-0001-5240-6123","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":49920,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":838947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carbone, Daniele","contributorId":124561,"corporation":false,"usgs":false,"family":"Carbone","given":"Daniele","email":"","affiliations":[{"id":5113,"text":"INGV","active":true,"usgs":false}],"preferred":false,"id":838948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":838949,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221286,"text":"70221286 - 2021 - Do crayfish affect stream ecosystem response to riparian vegetation removal?","interactions":[],"lastModifiedDate":"2021-06-30T19:04:39.950629","indexId":"70221286","displayToPublicDate":"2021-05-25T07:11:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Do crayfish affect stream ecosystem response to riparian vegetation removal?","docAbstract":"1. Riparian vegetation management alters stream basal resources, but stream ecosystem responses partly depend on top-down interactions with in-stream consumers. Large-bodied omnivores can exert particularly strong influences on stream benthic environments through consumption of food resources and physical disturbance of the benthos. Trophic dynamics studies conducted within the context of reach-scale riparian vegetation manipulations can provide insights into the interactions and relative importance of top-down and bottom-up controls that determine ecosystem response to riparian change. \n2. Here, we examine how top-down control by crayfish omnivores (Cambarus spp.) interacts with abiotic conditions created by reach-scale removal of riparian rhododendron (Rhododendron maximum) in the southern Appalachian Mountains. We conducted 32-day trophic experiments by nesting 5 pairs of electrified (crayfish excluded) and non-electrified (crayfish access) plots within each of two 300-m stream reaches (one control and one rhododendron-removed) for one year pre-removal and two years post-removal. \n3. Algal growth only responded positively to the reduced canopy cover (post-rhododendron removal) under low flow conditions and in the absence of top-down control by crayfish during the post-treatment year 2. Leaf decomposition rates were reduced by ~40% in the absence of crayfish, but higher inputs of rhododendron leaf litter during the summer following rhododendron removal reduced the effect of crayfish presence on decomposition. Riparian rhododendron removal also significantly increased benthic sediment and fine benthic organic matter, but macroconsumer exclusion did not affect these stream properties. \n4. Potential long-term reductions in crayfish abundance could reduce the top-down effects of crayfish and ultimately lead to higher algal growth and reduced leaf decomposition rates in streams where rhododendron is managed through removal.","language":"English","publisher":"Wiley","doi":"10.1111/fwb.13728","usgsCitation":"Dudley, M.P., Solomon, K., Wenger, S., Jackson, C.R., Freeman, M., Elliott, K.J., Miniat, C., and Pringle, C.M., 2021, Do crayfish affect stream ecosystem response to riparian vegetation removal?: Freshwater Biology, v. 66, no. 7, p. 1423-1435, https://doi.org/10.1111/fwb.13728.","productDescription":"13 p.","startPage":"1423","endPage":"1435","ipdsId":"IP-120584","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":386339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Southern Appalachian Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.693603515625,\n 34.99850370014629\n ],\n [\n -82.9632568359375,\n 34.99850370014629\n ],\n [\n -82.9632568359375,\n 35.78662688467009\n ],\n [\n -84.693603515625,\n 35.78662688467009\n ],\n [\n -84.693603515625,\n 34.99850370014629\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"66","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-05-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Dudley, Maura P. 0000-0001-9574-8844","orcid":"https://orcid.org/0000-0001-9574-8844","contributorId":236862,"corporation":false,"usgs":false,"family":"Dudley","given":"Maura","email":"","middleInitial":"P.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":817238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Solomon, Kelsey","contributorId":260094,"corporation":false,"usgs":false,"family":"Solomon","given":"Kelsey","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":817239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":817240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, C. Rhett","contributorId":236863,"corporation":false,"usgs":false,"family":"Jackson","given":"C.","email":"","middleInitial":"Rhett","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":817241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":817242,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elliott, Katherine J.","contributorId":260095,"corporation":false,"usgs":false,"family":"Elliott","given":"Katherine","email":"","middleInitial":"J.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":817243,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miniat, Chelcy F.","contributorId":260097,"corporation":false,"usgs":false,"family":"Miniat","given":"Chelcy F.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":817244,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pringle, Catherine M.","contributorId":176292,"corporation":false,"usgs":false,"family":"Pringle","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":817245,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70222344,"text":"70222344 - 2021 - Sin Nombre virus prevalence from 2014–2017 in wild deer mice, Peromyscus maniculatus, on five of the California Channel Islands","interactions":[],"lastModifiedDate":"2021-10-06T15:28:31.314288","indexId":"70222344","displayToPublicDate":"2021-05-24T09:39:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3813,"text":"Zoonoses and Public Health","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Sin Nombre virus prevalence from 2014–2017 in wild deer mice, Peromyscus maniculatus, on five of the California Channel Islands","title":"Sin Nombre virus prevalence from 2014–2017 in wild deer mice, Peromyscus maniculatus, on five of the California Channel Islands","docAbstract":"

Sin Nombre virus (SNV) is a zoonotic virus that is highly pathogenic to humans. The deer mouse, Peromyscus maniculatus, is the primary host of SNV, and SNV prevalence in P. maniculatus is an important indicator of human disease risk. Because the California Channel Islands contain permanent human settlements, receive hundreds of thousands of visitors each year, and can have extremely high densities of P. maniculatus, surveillance for SNV in island P. maniculatus is important for understanding the human risk of zoonotic disease. Despite the importance of surveillance on these heavily utilized islands, SNV prevalence (i.e. the proportion of P. maniculatus that test positive to antibodies to SNV) has not been examined in the last 13–27 years. We present data on 1,610 mice sampled for four consecutive years (2014–2017) on five of the California Channel Islands: East Anacapa, Santa Barbara, Santa Catalina, San Nicolas, and San Clemente. Despite historical data indicating SNV-positive mice on San Clemente and Santa Catalina, we detected no SNV-positive mice on these islands, suggesting very low prevalence or possible loss of SNV. Islands historically free of SNV (East Anacapa, Santa Barbara, and San Nicolas) remained free of SNV, suggesting that rates of pathogen introduction from other islands and/or the mainland are low. Although continued surveillance is warranted to determine whether SNV establishes on these islands, our work helps inform current human disease risk in these locations and suggests that SNV prevalence on these islands is currently very low.

","language":"English","publisher":"Wiley","doi":"10.1111/zph.12855","usgsCitation":"Orrock, J.L., Connolly, B., Guiden, P., Chandler, J.L., Bron, G.M., Drost, C.A., and Garcelon, D.K., 2021, Sin Nombre virus prevalence from 2014–2017 in wild deer mice, Peromyscus maniculatus, on five of the California Channel Islands: Zoonoses and Public Health, v. 68, no. 7, p. 849-853, https://doi.org/10.1111/zph.12855.","productDescription":"5 p.","startPage":"849","endPage":"853","ipdsId":"IP-120303","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":500015,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research.wur.nl/en/publications/sin-nombre-virus-prevalence-from-20142017-in-wild-deer-mice-perom","text":"External Repository"},{"id":387384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Channel Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.64959716796874,\n 32.784965481461185\n ],\n [\n -118.3282470703125,\n 32.784965481461185\n ],\n [\n -118.3282470703125,\n 33.04320549616557\n ],\n [\n -118.64959716796874,\n 33.04320549616557\n ],\n [\n -118.64959716796874,\n 32.784965481461185\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.60015869140625,\n 33.26624989076275\n ],\n [\n -118.27331542968749,\n 33.26624989076275\n ],\n [\n -118.27331542968749,\n 33.502468829034314\n ],\n [\n -118.60015869140625,\n 33.502468829034314\n ],\n [\n -118.60015869140625,\n 33.26624989076275\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.58892822265626,\n 33.18813395605041\n ],\n [\n -119.42413330078125,\n 33.18813395605041\n ],\n [\n -119.42413330078125,\n 33.30757713015298\n ],\n [\n -119.58892822265626,\n 33.30757713015298\n ],\n [\n -119.58892822265626,\n 33.18813395605041\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.0540313720703,\n 33.45836989641371\n ],\n [\n -119.02313232421874,\n 33.45836989641371\n ],\n [\n -119.02313232421874,\n 33.49101671911273\n ],\n [\n -119.0540313720703,\n 33.49101671911273\n ],\n [\n -119.0540313720703,\n 33.45836989641371\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.44782257080078,\n 34.000873555388495\n ],\n [\n -119.3558120727539,\n 34.000873555388495\n ],\n [\n -119.3558120727539,\n 34.01965669732604\n ],\n [\n -119.44782257080078,\n 34.01965669732604\n ],\n [\n -119.44782257080078,\n 34.000873555388495\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"68","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-05-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Orrock, John L.","contributorId":209931,"corporation":false,"usgs":false,"family":"Orrock","given":"John","email":"","middleInitial":"L.","affiliations":[{"id":38031,"text":"Department of Zoology, University of Wisconsin, Madison, WI 53706; jorrock@wisc.edu","active":true,"usgs":false}],"preferred":false,"id":819684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connolly, Brian","contributorId":261299,"corporation":false,"usgs":false,"family":"Connolly","given":"Brian","email":"","affiliations":[{"id":52796,"text":"441 Mark Jefferson Science Complex, Biology Department, Eastern Michigan University, Ypsilanti, MI 48197;","active":true,"usgs":false}],"preferred":false,"id":819685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guiden, Peter","contributorId":261300,"corporation":false,"usgs":false,"family":"Guiden","given":"Peter","email":"","affiliations":[{"id":52797,"text":"Northern Illinois University, 429 Montgomery Hall, DeKalb IL 60115","active":true,"usgs":false}],"preferred":false,"id":819686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chandler, Jennifer L.","contributorId":261301,"corporation":false,"usgs":false,"family":"Chandler","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":52798,"text":"250 Natural Resources Rd., Agricultural Engineering Rm 115, Amherst, MA 01003","active":true,"usgs":false}],"preferred":false,"id":819687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bron, Gebbiena M.","contributorId":261302,"corporation":false,"usgs":false,"family":"Bron","given":"Gebbiena","email":"","middleInitial":"M.","affiliations":[{"id":52800,"text":"1630 Linden Drive, Department of Entomology, University of Wisconsin-Madison, Madison, WI, 53706","active":true,"usgs":false}],"preferred":false,"id":819688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drost, Charles A. 0000-0002-4792-7095 charles_drost@usgs.gov","orcid":"https://orcid.org/0000-0002-4792-7095","contributorId":3151,"corporation":false,"usgs":true,"family":"Drost","given":"Charles","email":"charles_drost@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":819689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Garcelon, David K.","contributorId":204012,"corporation":false,"usgs":false,"family":"Garcelon","given":"David","email":"","middleInitial":"K.","affiliations":[{"id":36796,"text":"Institute for Wildlife Studies, Arcata, CA, USA","active":true,"usgs":false}],"preferred":false,"id":819690,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70220862,"text":"70220862 - 2021 - Time marches on, but do the causal pathways driving instream habitat and biology remain consistent?","interactions":[],"lastModifiedDate":"2021-06-01T17:50:52.039437","indexId":"70220862","displayToPublicDate":"2021-05-24T07:29:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Time marches on, but do the causal pathways driving instream habitat and biology remain consistent?","docAbstract":"

Stream ecosystems are complex networks of interacting terrestrial and aquatic drivers. To untangle these ecological networks, efforts evaluating the direct and indirect effects of landscape, climate, and instream predictors on biological condition through time are needed. We used structural equation modeling and leveraged a stream survey program to identify and compare important predictors driving condition of benthic macroinvertebrate and fish assemblages. We used data resampled 14 years apart at 252 locations across Maryland, USA. Sample locations covered a wide range of conditions that varied spatiotemporally. Overall, the relationship directions were consistent between sample periods, but their relative strength varied temporally. For benthic macroinvertebrates, we found that the total effect of natural landscape (e.g., elevation, longitude, latitude, geology) and land use (i.e., forest, development, agriculture) predictors was 1.4 and 1.5 times greater in the late 2010s compared to the 2000s. Moreover, the total effect of water quality (e.g., total nitrogen and conductivity) and habitat (e.g., embeddedness, riffle quality) was 1.2 and 4.8 times lower in the 2010s, respectively. For fish assemblage condition, the total effect of land use-land cover predictors was 2.3 times greater in the 2010s compared to the 2000s, while the total effect of local habitat was 1.4 times lower in the 2010s, respectively. As expected, we found biological assemblages in catchments with more agriculture and urban development were generally comprised of tolerant, generalist species, while assemblages in catchments with greater forest cover had more-specialized, less-tolerant species (e.g., Ephemeroptera, Plecoptera, and Trichoptera taxa, clingers, benthic and lithophilic spawning fishes). Changes in the relative importance of landscape and land-use predictors suggest other correlated, yet unmeasured, proximal factors became more important over time. By untangling these ecological networks, stakeholders can gain a better understanding of the spatiotemporal relationships driving biological condition to implement management practices aimed at improving stream condition.

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0000-0002-6635-4309","orcid":"https://orcid.org/0000-0002-6635-4309","contributorId":203315,"corporation":false,"usgs":true,"family":"Cashman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":816490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fanelli, Rosemary M. 0000-0002-0874-1925","orcid":"https://orcid.org/0000-0002-0874-1925","contributorId":206608,"corporation":false,"usgs":true,"family":"Fanelli","given":"Rosemary M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krause, Kevin P. 0000-0002-0255-7027","orcid":"https://orcid.org/0000-0002-0255-7027","contributorId":218454,"corporation":false,"usgs":true,"family":"Krause","given":"Kevin","email":"","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":816492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":816493,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":816494,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224947,"text":"70224947 - 2021 - Range-wide declines of northern spotted owl populations in the Pacific Northwest: A meta-analysis","interactions":[],"lastModifiedDate":"2025-05-21T14:41:11.086167","indexId":"70224947","displayToPublicDate":"2021-05-23T06:02:01","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9374,"text":"Biological Conservation,","active":true,"publicationSubtype":{"id":10}},"title":"Range-wide declines of northern spotted owl populations in the Pacific Northwest: A meta-analysis","docAbstract":"

The northern spotted owl (Strix occidentalis caurina) inhabits older coniferous forests in the Pacific Northwest and has been at the center of forest management issues in this region. The immediate threats to this federally listed species include habitat loss and competition with barred owls (Strix varia), which invaded from eastern North America. We conducted a prospective meta-analysis to assess population trends and factors affecting those trends in northern spotted owls using 26 years of survey and capture-recapture data from 11 study areas across the owls' geographic range to analyze demographic traits, rates of population change, and occupancy parameters for spotted owl territories. We found that northern spotted owl populations experienced significant declines of 6–9% annually on 6 study areas and 2–5% annually on 5 other study areas. Annual declines translated to ≤35% of the populations remaining on 7 study areas since 1995. Barred owl presence on spotted owl territories was the primary factor negatively affecting apparent survival, recruitment, and ultimately, rates of population change. Analysis of spotted and barred owl detections in an occupancy framework corroborated the capture-recapture analyses with barred owl presence increasing territorial extinction and decreasing territorial colonization of spotted owls. While landscape habitat components reduced the effect of barred owls on these rates of decline, they did not reverse the negative trend. Our analyses indicated that northern spotted owl populations potentially face extirpation if the negative effects of barred owls are not ameliorated while maintaining northern spotted owl habitat across their range.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2021.109168","usgsCitation":"Franklin, A.B., Dugger, K.M., Lesmeister, D.B., Davis, R.J., Wiens, J.D., White, G.C., Nichols, J., Hines, J.E., Yackulic, C.B., Schwarz, C.J., Ackers, S.H., Stevens, A.L., Bailey, L., Bown, R., Burgher, J., Burnham, K.P., Carlson, P., Chestnut, T., Conner, M.M., Dilione, K., Forsman, E.D., Glenn, E., Gremel, S., Hamm, K.A., Herter, D.R., Higley, J.M., Horn, R.B., Jenkins, J.M., Kendall, W.L., Lamphear, D., McCafferty, C., McDonald, T.L., Reid, J.A., Rockweit, J.T., Simon, D.C., Sovern, S., Swingle, J., and Wise, H., 2021, Range-wide declines of northern spotted owl populations in the Pacific Northwest: A meta-analysis: Biological Conservation,, v. 259, 109168, 20 p., https://doi.org/10.1016/j.biocon.2021.109168.","productDescription":"109168, 20 p.","ipdsId":"IP-126750","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":390318,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":452174,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2021.109168","text":"Publisher Index Page"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.04687499999999,\n 49.03786794532644\n ],\n [\n -123.00292968749999,\n 48.8936153614802\n ],\n [\n -122.958984375,\n 48.31242790407178\n ],\n [\n -123.57421875,\n 48.3416461723746\n ],\n [\n -125.068359375,\n 48.45835188280866\n ],\n [\n -124.5849609375,\n 46.89023157359399\n ],\n [\n -124.76074218749999,\n 44.05601169578525\n ],\n [\n -124.8046875,\n 42.5530802889558\n ],\n [\n -124.76074218749999,\n 40.84706035607122\n ],\n [\n -124.18945312500001,\n 39.16414104768742\n ],\n [\n -123.0908203125,\n 38.09998264736481\n ],\n [\n -122.16796875,\n 37.82280243352756\n ],\n [\n -122.56347656249999,\n 39.470125122358176\n ],\n [\n -121.77246093750001,\n 41.07935114946899\n ],\n [\n -121.1572265625,\n 42.58544425738491\n ],\n [\n -120.498046875,\n 43.70759350405294\n ],\n [\n -119.61914062499999,\n 45.98169518512228\n ],\n [\n -119.70703125,\n 47.42808726171425\n ],\n [\n -119.674072265625,\n 49.001843917978526\n ],\n [\n -123.04687499999999,\n 49.03786794532644\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"259","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Franklin, Alan B.","contributorId":101999,"corporation":false,"usgs":false,"family":"Franklin","given":"Alan","email":"","middleInitial":"B.","affiliations":[{"id":12434,"text":"USDA, Wildlife Services, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":824766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dugger, Katie M. 0000-0002-4148-246X","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":36037,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"","middleInitial":"M.","affiliations":[{"id":517,"text":"Oregon Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":824779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lesmeister, Damon B. 0000-0003-1102-0122","orcid":"https://orcid.org/0000-0003-1102-0122","contributorId":205006,"corporation":false,"usgs":false,"family":"Lesmeister","given":"Damon","email":"","middleInitial":"B.","affiliations":[{"id":37019,"text":"USDA Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":824780,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Raymond J.","contributorId":150574,"corporation":false,"usgs":false,"family":"Davis","given":"Raymond","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":824781,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wiens, J. 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Volcanic tremor occurring at the beginning of the 2018 Kīlauea eruption is characterized using both seismic and tilt data recorded at the Kīlauea summit. An automatic seismic network-based approach detects several types of tremor including (a) 0.5–1 Hz long-period tremor preceding the eruption, located at the south-southwest edge of Halema'uma'u Crater and attributed to the quasi-steady radiation from a shallow hydrothermal system and (b) two sequences of gliding tremor at the beginning of the eruption, both with locations on the edges of the crater and within it. The first sequence is attributed to two swarms of low-amplitude regularly repeating earthquakes induced by the jerky motions of a cylindrical rock piston with radius of 325 m, height of 250 m, and mass of 2.07 × 1011 kg, progressively intruding 12.3 m into the shallow hydrothermal system with volume of 108 m3 and depth extent of 300 m. The second sequence is attributed to a gradual evolution in the properties of a bubbly magma within an east-striking dike below Halema'uma'u Crater, impacted by repeated roof collapses. A fluid-filled crack model points to a decrease in gas volume fraction from 4.22% to 1.6 × 10−2% in the magma filling the dike, and a model of gas retro-diffusion within the melt suggests a two orders of magnitude decrease in bubble number density from 7 × 108 m−3 down to 4 × 106 m−3. Both models feature a quasi to totally degassed magma by May 26.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB021572","usgsCitation":"Soubestre, J., Chouet, B., and Dawson, P.B., 2021, Sources of volcanic tremor associated with the summit caldera collapse during the 2018 east rift eruption of Kīlauea Volcano, Hawai'i: Journal of Geophysical Research: Solid Earth, v. 126, no. 6, e2020JB021572, 33 p., https://doi.org/10.1029/2020JB021572.","productDescription":"e2020JB021572, 33 p.","ipdsId":"IP-125499","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":386584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.35423278808594,\n 19.20288950660437\n ],\n [\n -155.00885009765625,\n 19.20288950660437\n ],\n [\n -155.00885009765625,\n 19.480186937661344\n ],\n [\n -155.35423278808594,\n 19.480186937661344\n ],\n [\n -155.35423278808594,\n 19.20288950660437\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Soubestre, J. 0000-0002-9403-8821","orcid":"https://orcid.org/0000-0002-9403-8821","contributorId":260399,"corporation":false,"usgs":false,"family":"Soubestre","given":"J.","email":"","affiliations":[{"id":52584,"text":"Instituto Volcanologico de Canarias (INVOLCAN)","active":true,"usgs":false}],"preferred":false,"id":817860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chouet, B. 0000-0001-5527-0532","orcid":"https://orcid.org/0000-0001-5527-0532","contributorId":260400,"corporation":false,"usgs":false,"family":"Chouet","given":"B.","affiliations":[{"id":52585,"text":"Retired (USGS)","active":true,"usgs":false}],"preferred":false,"id":817861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dawson, Phillip B. 0000-0003-4065-0588 dawson@usgs.gov","orcid":"https://orcid.org/0000-0003-4065-0588","contributorId":206751,"corporation":false,"usgs":true,"family":"Dawson","given":"Phillip","email":"dawson@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":817862,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70220582,"text":"ofr20201147 - 2021 - GIS-based identification of areas that have resource potential for sediment-hosted Pb-Zn deposits in Alaska","interactions":[],"lastModifiedDate":"2021-05-21T14:58:21.181526","indexId":"ofr20201147","displayToPublicDate":"2021-05-20T18:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1147","displayTitle":"GIS-Based Identification of Areas that have Resource Potential for Sediment-hosted Pb-Zn deposits in Alaska","title":"GIS-based identification of areas that have resource potential for sediment-hosted Pb-Zn deposits in Alaska","docAbstract":"

A state-wide Geographic Information System analysis was conducted to assess prospectivity for lead (Pb) and zinc (Zn) in sediment-hosted deposits in Alaska. The datasets that were utilized include publicly available geospatial datasets of lithologic, geochemical, and mineral occurrence data. Key characteristics of Pb-Zn deposits were identified in available datasets and scored with respect to relative importance. To evaluate resource potential, drainage basins of the smallest size were chosen, each of which covers approximately 100 square kilometers (km2). Drainage basins are the most logical and efficient unit for evaluation because the most regionally robust dataset comes from stream sediment geochemistry.

Sediment-hosted Pb-Zn deposits in Alaska include those contained in carbonate rocks (similar to Mississippi Valley Type or MVT deposits) and those contained in clastic-dominated (CD) sequences (CD Pb-Zn), historically referred to as SEDEX (sedimentary exhalative). The latter include the deposits currently being mined in the Red Dog district in the western Brooks Range. Host rocks for the two subtypes are distinct: carbonate versus fine-grained clastic rocks for CD Pb-Zn deposits. However, there are exceptions: some CD Pb-Zn deposits are hosted in carbonate layers within a thick clastic-dominated rock sequence. The statewide geologic map database contains units that commonly include mixed carbonate-clastic sequences that cannot be subdivided. The most significant difference between the two deposit types is their respective depositional environments and tectonic settings, but at the reconnaissance level of mapping in most areas of the state, these distinctions are not possible. Furthermore, nearly all critical geochemical parameters (silver [Ag], barium [Ba], Pb, Zn) are common to both types, and therefore it was not possible to do separate assessments for carbonate-hosted and CD Pb-Zn deposits.

Areas identified that have moderate to high potential for sediment-hosted Pb-Zn deposits include the (1) western and central Brooks Range, referred to in this report as the Brooks Range zinc belt; (2) Seward Peninsula (and adjacent St. Lawrence Island); (3) Farewell terrane in Interior Alaska; (4) two spatially distinct belts in east-central Alaska; and (5) the central Alaska Range. All areas contain some known deposits, and that provides credibility to the scoring process. Some hydrologic unit codes (HUCs) that have high potential for sediment-hosted Pb-Zn deposits are located adjacent to areas of known deposits and indicate the potential for expansion of known Pb-Zn districts. There are a few areas that have high potential but contain no known sediment hosted Pb-Zn occurrences, prospects, or deposits. In such areas, future investigations could be focused on better defining and constraining prospectivity with additional data.

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Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
MS 973, Box 25046
Denver, CO 80225

","tableOfContents":"","publishedDate":"2021-05-20","noUsgsAuthors":false,"publicationDate":"2021-05-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kelley, Karen D. 0000-0002-3232-5809 kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":179012,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":816084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Garth E. 0000-0003-0657-0365 ggraham@usgs.gov","orcid":"https://orcid.org/0000-0003-0657-0365","contributorId":1031,"corporation":false,"usgs":true,"family":"Graham","given":"Garth","email":"ggraham@usgs.gov","middleInitial":"E.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":816085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Labay, Keith A. 0000-0002-6763-3190 klabay@usgs.gov","orcid":"https://orcid.org/0000-0002-6763-3190","contributorId":217714,"corporation":false,"usgs":true,"family":"Labay","given":"Keith","email":"klabay@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":816086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shew, Nora B. 0000-0003-0025-7220 nshew@usgs.gov","orcid":"https://orcid.org/0000-0003-0025-7220","contributorId":3382,"corporation":false,"usgs":true,"family":"Shew","given":"Nora","email":"nshew@usgs.gov","middleInitial":"B.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":816087,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220861,"text":"70220861 - 2021 - Incorporating climate change in a harvest risk assessment for polar bears Ursus maritimus in Southern Hudson Bay","interactions":[],"lastModifiedDate":"2021-05-26T12:28:44.821314","indexId":"70220861","displayToPublicDate":"2021-05-19T07:26:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating climate change in a harvest risk assessment for polar bears Ursus maritimus in Southern Hudson Bay","docAbstract":"

Arctic marine mammals are harvested by Indigenous people for subsistence and are socially and culturally important. For ice-dependent species like the polar bear Ursus maritimus, management and conservation require understanding interactions between harvest and sea-ice loss due to climate change. We developed a demographic model to evaluate harvest risk for polar bears in Southern Hudson Bay, Canada, where the annual ice-free season has increased by approximately one month in recent decades. The model was based on the theta-logistic equation and allowed for density-dependent changes (through carrying capacity [K]) and density-independent changes (through population growth rate [r]). Model parameters were estimated using a Bayesian Monte Carlo method that included capture-recapture, aerial survey, and harvest data. Harvest management followed a state-dependent approach under which new estimates of abundance were used to update the harvest level every five years. Under a middle-of-the-road environmental scenario that assumed K and r would decline in proportion to projected sea-ice declines, annual removal of 0.02–0.03 of females resulted in a 0.8 probability of maintaining subpopulation abundance above maximum net productivity level for three polar bear generations (~34 years), our primary criterion for sustainability. Under more pessimistic and optimistic environmental scenarios, comparable female harvest rates were 0.01 and 0.055, respectively. Our coupled modeling-management framework can be used to inform tradeoffs between protection and sustainable use for wildlife populations experiencing habitat loss.

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Earthquake early warning (EEW) systems can quickly identify the beginning of a significant earthquake rupture, but the first seconds of seismic data have not been found to predict the final rupture length. We present two approaches for estimating probabilities of rupture length given the rupture initiation from an EEW system. In the first approach, bends and steps on the fault are interpreted as physical mechanisms for rupture arrest. Arrest probability relations are developed from empirical observations and depend on bend angle and step size. Probability of arrest compounds serially with increasing rupture length as bends or steps are encountered. In the second approach, time‐independent rates among ruptures from the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3), are interpreted to apply to the time‐dependent condition in which rupture grows from a known starting point. Length probabilities from a Gutenberg–Richter magnitude–frequency relation provide a reference of comparison. We illustrate the new approach using the discretized fault model for California developed for UCERF3. For the case of rupture initiating on the southeast end of the San Andreas fault we find the geometric complexity of the Mill Creek section impedes most ruptures, and only ∼5% are predicted to reach to San Bernardino on the eastern edge of the greater Los Angeles region. Conditional probabilities of length can be precompiled in this manner for any initiation point on the fault system and thus are of potential value in seismic hazard and EEW applications.

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\"}}]}","volume":"111","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-05-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Biasi, Glenn 0000-0003-0940-5488 gbiasi@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-5488","contributorId":195946,"corporation":false,"usgs":true,"family":"Biasi","given":"Glenn","email":"gbiasi@usgs.gov","affiliations":[],"preferred":true,"id":929127,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wesnousky, Steven G.","contributorId":193416,"corporation":false,"usgs":false,"family":"Wesnousky","given":"Steven","email":"","middleInitial":"G.","affiliations":[{"id":33746,"text":"Center for Neotectonic Studies, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":929128,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70221276,"text":"70221276 - 2021 - Molluscan aminostratigraphy of the US Mid-Atlantic Quaternary coastal system: Implications for onshore-offshore correlation, paleochannel and barrier island evolution, and local late Quaternary sea-level history","interactions":[],"lastModifiedDate":"2021-08-18T11:40:05.70642","indexId":"70221276","displayToPublicDate":"2021-05-18T06:48:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3216,"text":"Quaternary Geochronology","active":true,"publicationSubtype":{"id":10}},"title":"Molluscan aminostratigraphy of the US Mid-Atlantic Quaternary coastal system: Implications for onshore-offshore correlation, paleochannel and barrier island evolution, and local late Quaternary sea-level history","docAbstract":"

The Quaternary record of the US Mid-Atlantic coastal system includes onshore emergent late Pleistocene shoreline deposits, offshore inner shelf and barrier island units, and paleovalleys formed during multiple glacial stage sea-level lowstands. The geochronology of this coastal system is based on uranium series, radiocarbon, amino acid racemization (AAR), and optically stimulated luminescence (OSL) methods. We report over 600 mollusk AAR results from 93 sites between northeastern North Carolina and the central New Jersey shelf, representing samples from both onshore cores or outcrops, sub-barrier and offshore cores, and transported shells from barrier island beaches. AAR age estimates are constrained by paired 14C analyses on specific shells and associated U-series coral ages from onshore sites. AAR data from offshore cores are interpreted in the context of detailed seismic stratigraphy. The distribution of Pleistocene-age shells on the island beaches is linked to the distribution of inner shelf or sub-barrier source units. Age mixing over a range of time-scales (~1 ka to ~100 ka) is identified by AAR results from onshore, beach, and shelf collections, often contributing insights into the processes forming individual barrier islands. The regional aminostratigraphic framework identifies a widespread late Pleistocene (Marine Isotope Stage 5) aminozone, with isolated records of middle and early Pleistocene deposition. AAR results provide age estimates for the timing of formation of the three major paleochannels that underlie the Delmarva Peninsula: Persimmon Point paleochannel ≥800 ka; Exmore paleochannel ~400–500 ka (MIS 12); and Eastville paleochannel > 125 ka (MIS 6). The results demonstrate the value of synthesizing abundant AAR chronologic data across various coastal environments, integrating multiple distinct geologic studies. The ages and elevations of the Quaternary units are important for current hypotheses about relative sea-level history and crustal dynamics in the region, which was likely influenced by the Laurentide ice sheet, the margin just ~400 km to the north.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.quageo.2021.101177","usgsCitation":"Wehmiller, J., Brothers, L.L., Ramsey, K., Foster, D.S., Mattheus, C., Hein, C., and Shawler, J.L., 2021, Molluscan aminostratigraphy of the US Mid-Atlantic Quaternary coastal system: Implications for onshore-offshore correlation, paleochannel and barrier island evolution, and local late Quaternary sea-level history: Quaternary Geochronology, v. 66, 101177, 34 p., https://doi.org/10.1016/j.quageo.2021.101177.","productDescription":"101177, 34 p.","ipdsId":"IP-122893","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":452222,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quageo.2021.101177","text":"Publisher Index Page"},{"id":386336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Virginia","otherGeospatial":"Delmarva Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.365966796875,\n 36.914764288955936\n ],\n [\n -74.8828125,\n 36.914764288955936\n ],\n [\n -74.8828125,\n 39.791654835253425\n ],\n [\n -76.365966796875,\n 39.791654835253425\n ],\n [\n -76.365966796875,\n 36.914764288955936\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"66","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wehmiller, John","contributorId":260088,"corporation":false,"usgs":false,"family":"Wehmiller","given":"John","affiliations":[{"id":52500,"text":"University of Delaware, Newark DE","active":true,"usgs":false}],"preferred":false,"id":817215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Laura L. 0000-0003-2986-5166 lbrothers@usgs.gov","orcid":"https://orcid.org/0000-0003-2986-5166","contributorId":176698,"corporation":false,"usgs":true,"family":"Brothers","given":"Laura","email":"lbrothers@usgs.gov","middleInitial":"L.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramsey, Kelvin","contributorId":260089,"corporation":false,"usgs":false,"family":"Ramsey","given":"Kelvin","email":"","affiliations":[{"id":52502,"text":"Geological Survey, University of Delaware, Newark DE","active":true,"usgs":false}],"preferred":false,"id":817217,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, David S. 0000-0003-1205-0884 dfoster@usgs.gov","orcid":"https://orcid.org/0000-0003-1205-0884","contributorId":1320,"corporation":false,"usgs":true,"family":"Foster","given":"David","email":"dfoster@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817218,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mattheus, C.R.","contributorId":260090,"corporation":false,"usgs":false,"family":"Mattheus","given":"C.R.","email":"","affiliations":[{"id":52504,"text":"Illinois Geological Survey, DGS","active":true,"usgs":false}],"preferred":false,"id":817219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hein, Christopher","contributorId":214093,"corporation":false,"usgs":false,"family":"Hein","given":"Christopher","affiliations":[{"id":18865,"text":"VIMS","active":true,"usgs":false}],"preferred":false,"id":817220,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shawler, Justin L.","contributorId":256701,"corporation":false,"usgs":false,"family":"Shawler","given":"Justin","email":"","middleInitial":"L.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":817221,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70220496,"text":"70220496 - 2021 - Modeling of future COVID-19 cases, hospitalizations, and deaths, by vaccination rates and nonpharmaceutical intervention scenarios — United States, April–September 2021","interactions":[],"lastModifiedDate":"2021-05-17T15:55:08.190065","indexId":"70220496","displayToPublicDate":"2021-05-14T11:54:33","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8598,"text":"Morbidity and Mortality Weekly Report","active":true,"publicationSubtype":{"id":10}},"title":"Modeling of future COVID-19 cases, hospitalizations, and deaths, by vaccination rates and nonpharmaceutical intervention scenarios — United States, April–September 2021","docAbstract":"

What is already known about this topic?

Increases in COVID-19 cases in March and early April occurred despite a large-scale vaccination program. Increases coincided with the spread of SARS-CoV-2 variants and relaxation of nonpharmaceutical interventions (NPIs).

What is added by this report?

Data from six models indicate that with high vaccination coverage and moderate NPI adherence, hospitalizations and deaths will likely remain low nationally, with a sharp decline in cases projected by July 2021. Lower NPI adherence could lead to substantial increases in severe COVID-19 outcomes, even with improved vaccination coverage.

What are the implications for public health practice?

High vaccination coverage and compliance with NPIs are essential to control COVID-19 and prevent surges in hospitalizations and deaths in the coming months.

","language":"English","publisher":"Centers for Disease Control and Prevention","doi":"10.15585/mmwr.mm7019e3","usgsCitation":"Borchering, R.K., Viboud, C., Howerton, E., Smith, C.P., Truelove, S., Runge, M.C., Reich, N.G., Contamin, L., Levander, J., Salerno, J., van Panhuis, W., Kinsey, M., Tallaksen, K., Obrecht, R.F., Asher, L., Costello, C., Kelbaugh, M., Wilson, S., Shin, L., Gallagher, M., Mullany, L., Rainwater-Lovett, K., Lemaitre, J., Dent, J., Grantz, K., Kaminsky, J., Lauer, S., Lee, E., Meredith, H., Perez-Saez, J., Keegan, L.T., Karlen, D., Chinazzi, M., Davis, J., Mu, K., Xiong, X., Pastore y Piontti, A., Vespignani, A., Srivastava, A., Porebski, P., Venkatramanan, S., Adiga, A., Lewis, B., Klahn, B., Outten, J., Schlitt, J., Corbett, P., Telionis, P.A., Wang, L., Peddireddy, A.S., Hurt, B., Chen, J., Vullikanti, A., Marathe, M., Healy, J., Slayton, R.B., Biggerstaff, M., Johansson, M.A., Shea, K., and Lessler, J., 2021, Modeling of future COVID-19 cases, 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