{"pageNumber":"260","pageRowStart":"6475","pageSize":"25","recordCount":46679,"records":[{"id":70260133,"text":"70260133 - 2020 - Mechanisms for ballistic block ejection during the 2016–2017 shallow submarine eruption of Bogoslof volcano, Alaska","interactions":[],"lastModifiedDate":"2024-10-29T16:44:36.747968","indexId":"70260133","displayToPublicDate":"2020-01-11T11:38:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Mechanisms for ballistic block ejection during the 2016–2017 shallow submarine eruption of Bogoslof volcano, Alaska","docAbstract":"<p><span>Ejection of ballistic blocks was a characteristic feature of the 2016–2017 Bogoslof eruption. High-resolution satellite images acquired throughout the duration of the 9-month long eruptive period permitted the recognition and mapping of ballistic blocks on the surface of Bogoslof Island. Many of the satellite images recorded the accumulation of ballistic material over several individual eruptive events, but a few images recorded the effects of a single event. The nonuniform spatial distribution of blocks suggests that some of the eruption columns were inclined. Ballistic trajectories were estimated using the Eject! model and indicate that accumulation of blocks on Bogoslof Island required launch angles of 45–80° and initial velocities of 50–100&nbsp;ms</span><sup>−1</sup><span>&nbsp;to reproduce observed travel distances. The amount of ballistic fallout observed in satellite data indicates that there must have been a shallow submarine source of rock within the conduit/upper edifice system. Dense, accidental cryptodome trachyandesite, and juvenile basalt to trachybasalt scoria make up the bulk of the surface ejecta. Abundant accidental fragments and inclined eruption columns point to periodic vent-wall collapse and jetting around edges of temporarily blocked vents as the likely cause of ballistic ejection.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00445-019-1351-4","usgsCitation":"Waythomas, C.F., and Mastin, L.G., 2020, Mechanisms for ballistic block ejection during the 2016–2017 shallow submarine eruption of Bogoslof volcano, Alaska: Bulletin of Volcanology, v. 82, 13, 20 p., https://doi.org/10.1007/s00445-019-1351-4.","productDescription":"13, 20 p.","ipdsId":"IP-113632","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":463356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -168.04572245314344,\n              53.93741980478987\n            ],\n            [\n              -168.04572245314344,\n              53.92361535465113\n            ],\n            [\n              -168.0255939265047,\n              53.92361535465113\n            ],\n            [\n              -168.0255939265047,\n              53.93741980478987\n            ],\n            [\n              -168.04572245314344,\n              53.93741980478987\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2020-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Waythomas, Christopher F. 0000-0002-3898-272X cwaythomas@usgs.gov","orcid":"https://orcid.org/0000-0002-3898-272X","contributorId":640,"corporation":false,"usgs":true,"family":"Waythomas","given":"Christopher","email":"cwaythomas@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mastin, Larry G. 0000-0002-4795-1992","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":265985,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917131,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70237952,"text":"70237952 - 2020 - Conjoint use of hydraulic head and groundwater age data to detect hydrogeologic barriers","interactions":[],"lastModifiedDate":"2022-11-01T14:06:22.857819","indexId":"70237952","displayToPublicDate":"2020-01-11T08:57:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Conjoint use of hydraulic head and groundwater age data to detect hydrogeologic barriers","docAbstract":"<p><span>Hydraulic head and groundwater age data are effective in building understanding of groundwater systems. Yet their joint role in detecting and characterising low-permeability geological structures, i.e. hydrogeologic barriers such as faults and dykes, has not been widely studied. Here, numerical flow and transport models, using MODFLOW-NWT and MT3D-USGS, were developed with different hydrogeologic barrier configurations in a hypothetical aquifer. Computed hydraulic head and groundwater age distributions were compared to those without a barrier. The conjoint use of these datasets helps in detecting vertically-oriented barriers. Two forms of recharge were compared: (1) applied across the entire aquifer surface (uniform), and (2) applied to the upstream part of the aquifer (upgradient). The hydraulic head distribution is significantly impacted by a barrier that penetrates the aquifer’s full vertical thickness. This barrier also perturbs the groundwater age distribution when upgradient recharge prevails; however, with uniform recharge, groundwater age is not successful in detecting the barrier. When a barrier is buried, such as by younger sediment, hydraulic head data also do not clearly identify the barrier. Groundwater age data could, on the other hand, prove to be useful if sampled at depth-specific intervals. These results are important for the detection and characterisation of hydrogeologic barriers, which may play a significant role in the compartmentalisation of groundwater flow, spring dynamics, and drawdown and recovery associated with groundwater extraction.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10040-019-02095-9","usgsCitation":"Marshall, S.K., Cook, P., Konikow, L.F., Simmons, C., and Dogramaci, S., 2020, Conjoint use of hydraulic head and groundwater age data to detect hydrogeologic barriers: Hydrogeology Journal, v. 28, p. 1003-1019, https://doi.org/10.1007/s10040-019-02095-9.","productDescription":"17 p.","startPage":"1003","endPage":"1019","ipdsId":"IP-109151","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":408987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","noUsgsAuthors":false,"publicationDate":"2020-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Marshall, Sarah K.","contributorId":298728,"corporation":false,"usgs":false,"family":"Marshall","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":40595,"text":"Flinders University","active":true,"usgs":false}],"preferred":false,"id":856337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, Peter G.","contributorId":298729,"corporation":false,"usgs":false,"family":"Cook","given":"Peter G.","affiliations":[{"id":40595,"text":"Flinders University","active":true,"usgs":false}],"preferred":false,"id":856338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Konikow, Leonard F. 0000-0002-0940-3856 lkonikow@usgs.gov","orcid":"https://orcid.org/0000-0002-0940-3856","contributorId":158,"corporation":false,"usgs":true,"family":"Konikow","given":"Leonard","email":"lkonikow@usgs.gov","middleInitial":"F.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":856339,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simmons, Craig T.","contributorId":298730,"corporation":false,"usgs":false,"family":"Simmons","given":"Craig T.","affiliations":[{"id":40595,"text":"Flinders University","active":true,"usgs":false}],"preferred":false,"id":856340,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dogramaci, Shawan","contributorId":298731,"corporation":false,"usgs":false,"family":"Dogramaci","given":"Shawan","email":"","affiliations":[{"id":64684,"text":"Rio Tinto Iron Ore Co.","active":true,"usgs":false}],"preferred":false,"id":856341,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70209325,"text":"70209325 - 2020 - Heterogeneity in migration strategies of the whooping crane","interactions":[],"lastModifiedDate":"2020-04-01T08:27:50","indexId":"70209325","displayToPublicDate":"2020-01-11T08:21:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Heterogeneity in migration strategies of the whooping crane","docAbstract":"Migratory birds use numerous strategies to successfully complete twice-annual movements between breeding and wintering sites. Context for conservation and management can be provided by characterizing these strategies. Variations in strategy among and within individuals support population persistence in response to changes in land use and climate. We used location data from 58 marked Whooping Cranes (Grus americana) from 2010–2016 to characterize migration strategies in the U.S. Great Plains and Canadian Prairies and southern boreal region, and to explore sources of heterogeneity in their migration strategy, including space use, timing, and performance. Whooping Cranes completed approximately 3,900-km migrations that averaged 29 days during spring and 45 days during autumn, while making 11–12 nighttime stops. At the scale of our analysis, individual Whooping Cranes showed little consistency in stopover sites used among migration seasons (i.e., low site fidelity). In contrast, individuals expressed a measure of consistency in timing, especially migration initiation date. Whooping Cranes migrated at different times based on age and reproductive status, where adults with young initiated autumn migration after other birds, and adults with and without young initiated spring migration before subadult birds. Time spent at stopover sites was associated with migration bout length and time spent at previous stopover sites, suggesting Whooping Cranes acquired energy resources at some stopover sites that they used to fuel migration. Whooping Cranes were faithful to a defined migration corridor but showed less fidelity in their selection of nighttime stopover sites; hence, spatial targeting of conservation actions may be better informed by associations with landscape and habitat features rather than documented past use at specific locations. The preservation of variation in migration strategies existing within this species that experienced a severe population bottleneck suggests that Whooping Cranes have maintained a capacity to adjust strategies when confronted with future changes in land use and climate.","language":"English","publisher":"American Ornithological Society","doi":"10.1093/condor/duz056","usgsCitation":"Pearse, A.T., Metzger, K.L., Brandt, D.A., Bidwell, M.T., Harner, M.J., Baasch, D.M., and Harrell, W.C., 2020, Heterogeneity in migration strategies of the whooping crane: The Condor, v. 122, no. 1, duz056, https://doi.org/10.1093/condor/duz056.","productDescription":"duz056","ipdsId":"IP-099078","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":437169,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NRAY6F","text":"USGS data release","linkHelpText":"Characterization of whooping crane migrations and stopover sites used in the Central Flyway, 2010-2016"},{"id":373699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Great Plains, Canadian Prairies ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -95.09765625,\n              29.38217507514529\n            ],\n            [\n              -95.97656249999999,\n              33.797408767572485\n            ],\n            [\n              -97.119140625,\n              39.027718840211605\n            ],\n            [\n              -98.349609375,\n              45.1510532655634\n            ],\n            [\n              -100.107421875,\n              48.922499263758255\n            ],\n            [\n              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NM","active":true,"usgs":false}],"preferred":false,"id":786080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandt, David A. 0000-0001-9786-307X dbrandt@usgs.gov","orcid":"https://orcid.org/0000-0001-9786-307X","contributorId":149929,"corporation":false,"usgs":true,"family":"Brandt","given":"David","email":"dbrandt@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":786078,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bidwell, Mark T.","contributorId":202007,"corporation":false,"usgs":false,"family":"Bidwell","given":"Mark","email":"","middleInitial":"T.","affiliations":[{"id":36318,"text":"CWS","active":true,"usgs":false}],"preferred":false,"id":786079,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harner, Mary J.","contributorId":177584,"corporation":false,"usgs":false,"family":"Harner","given":"Mary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":786081,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baasch, David M.","contributorId":147145,"corporation":false,"usgs":false,"family":"Baasch","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":16795,"text":"Headwaters Corp, Kearney, NE","active":true,"usgs":false}],"preferred":false,"id":786082,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harrell, Wade C.","contributorId":147143,"corporation":false,"usgs":false,"family":"Harrell","given":"Wade","email":"","middleInitial":"C.","affiliations":[{"id":16793,"text":"USFWS, Ecological Services, Austwell, TX","active":true,"usgs":false}],"preferred":false,"id":786083,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70208875,"text":"70208875 - 2020 - Demography of snowshoe hare population cycles","interactions":[],"lastModifiedDate":"2020-03-04T16:16:48","indexId":"70208875","displayToPublicDate":"2020-01-10T16:01:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Demography of snowshoe hare population cycles","docAbstract":"<p><span>Cyclic fluctuations in abundance exhibited by some mammalian populations in northern habitats (“population cycles”) are key processes in the functioning of many boreal and tundra ecosystems. Understanding population cycles, essentially demographic processes, necessitates discerning the demographic mechanisms that underlie numerical changes. Using mark–recapture data spanning five population cycles (1977–2017), we examined demographic mechanisms underlying the 9–10‐yr cycles exhibited by snowshoe hares (</span><i>Lepus americanus</i><span>&nbsp;Erxleben) in southwestern Yukon, Canada. Snowshoe hare populations always decreased during winter and increased during summer; the balance between winter declines and summer increases characterized the four, multiyear cyclic phases: increase, peak, decline, and low. Little or no recruitment occurred during winter, but summer recruitment varied markedly across the four phases with the highest and lowest recruitment observed during the increase and decline phase, respectively. Population crashes during the decline were triggered by a substantial decline in winter survival and by a lack of subsequent summer recruitment. In contrast, initiation of the increase phase was triggered by a twofold increase in summer recruitment abetted secondarily by improvements in subsequent winter survival. We show that differences in peak density across cycles are explained by differences in overall population growth rate, amount of time available for population growth to occur, and starting population density. Demographic mechanisms underlying snowshoe hare population cycles were consistent across cycles in our study site but we do not yet know if similar demographic processes underlie population cycles in other northern snowshoe hare populations.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ecy.2969","usgsCitation":"Oli, M.K., Krebs, C., Kenney, A.J., Boonstra, R., Boutin, S., and Hines, J.E., 2020, Demography of snowshoe hare population cycles: Ecology, v. 101, no. 3, 02969, 15 p., https://doi.org/10.1002/ecy.2969.","productDescription":"02969, 15 p.","ipdsId":"IP-106392","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":501028,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1807/144262","text":"External Repository"},{"id":372927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Yukon","otherGeospatial":"Kluane Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -140.526123046875,\n              60.267066292456654\n            ],\n            [\n              -136.065673828125,\n              60.267066292456654\n            ],\n            [\n              -136.065673828125,\n              62.3190027860309\n            ],\n            [\n              -140.526123046875,\n              62.3190027860309\n            ],\n            [\n              -140.526123046875,\n              60.267066292456654\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"101","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Oli, Madan K. 0000-0001-6944-0061","orcid":"https://orcid.org/0000-0001-6944-0061","contributorId":201302,"corporation":false,"usgs":false,"family":"Oli","given":"Madan","email":"","middleInitial":"K.","affiliations":[{"id":13453,"text":"University of Florida, Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":783801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krebs, Charles J","contributorId":146456,"corporation":false,"usgs":false,"family":"Krebs","given":"Charles J","affiliations":[{"id":16701,"text":"Dept. of Zoology, University of British Columbia, Vancouver","active":true,"usgs":false}],"preferred":false,"id":783802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kenney, Alice J","contributorId":223008,"corporation":false,"usgs":false,"family":"Kenney","given":"Alice","email":"","middleInitial":"J","affiliations":[],"preferred":false,"id":783803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boonstra, Rudy","contributorId":223009,"corporation":false,"usgs":false,"family":"Boonstra","given":"Rudy","affiliations":[],"preferred":false,"id":783804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boutin, Stan","contributorId":223010,"corporation":false,"usgs":false,"family":"Boutin","given":"Stan","email":"","affiliations":[],"preferred":false,"id":783805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":783800,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70208310,"text":"70208310 - 2020 - How often can Earthquake Early Warning systems alert sites with high intensity ground motion?","interactions":[],"lastModifiedDate":"2020-02-04T07:34:49","indexId":"70208310","displayToPublicDate":"2020-01-10T07:33:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"How often can Earthquake Early Warning systems alert sites with high intensity ground motion?","docAbstract":"Although numerous Earthquake Early Warning (EEW) algorithms have been developed we still lack a detailed understanding of how often and under what circumstances useful ground motion alerts can be provided to end-users. Here we analyze the alerting performance of the PLUM, EPIC and FinDer algorithms by running them retrospectively on the seismic strong motion data of the 219 earthquakes in Japan since 1996 that exceeded Modified Mercalli Intensity (MMI) of 4.5 on at least 10 sites (Mw 4.5-9.1). Our analysis suggests that, irrespective of the algorithm, EEW end-users should be prepared that EEW can often but not always provide useful ground motion alerts. A majority of sites with moderate-strong ground motion (MMI 5-6) can generally get at least a few seconds of warning time from all algorithms. If such shaking is caused by a shallow crustal event, around 50% of such sites receive alerts with warning times >5 s. Many sites with severe-extreme ground motion (MMI >=8) can be alerted successfully in the case of very large offshore earthquakes, but less than 20% can be alerted ahead of time if such shaking is caused by a shallow crustal event. Our results provide detailed quantitative insight into the expected alerting performance for EEW algorithms under realistic conditions. The main caveat is that the largest shallow crustal event in our data set has Mw7.0, i.e. the data set does not contain very large strike slip events.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JB017718","usgsCitation":"Meier, M., Kodera, Y., Bose, M., Chung, A.I., Hoshiba, M., Cochran, E.S., Minson, S.E., Hauksson, E., and Heaton, T., 2020, How often can Earthquake Early Warning systems alert sites with high intensity ground motion?: Journal of Geophysical Research, v. 125, e2019JB017718, 17 p., https://doi.org/10.1029/2019JB017718.","productDescription":"e2019JB017718, 17 p.","ipdsId":"IP-107685","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":458167,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019jb017718","text":"Publisher Index Page"},{"id":371988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Meier, M.-A.","contributorId":222138,"corporation":false,"usgs":false,"family":"Meier","given":"M.-A.","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":781351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kodera, Y.","contributorId":216381,"corporation":false,"usgs":false,"family":"Kodera","given":"Y.","affiliations":[{"id":39398,"text":"JMA","active":true,"usgs":false}],"preferred":false,"id":781352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bose, M.","contributorId":222139,"corporation":false,"usgs":false,"family":"Bose","given":"M.","email":"","affiliations":[{"id":40494,"text":"ETH-Zurich","active":true,"usgs":false}],"preferred":false,"id":781353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chung, A. I.","contributorId":39293,"corporation":false,"usgs":false,"family":"Chung","given":"A.","email":"","middleInitial":"I.","affiliations":[{"id":7033,"text":"School of Earth Sciences, Stanford University","active":true,"usgs":false}],"preferred":false,"id":781354,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoshiba, M.","contributorId":222140,"corporation":false,"usgs":false,"family":"Hoshiba","given":"M.","affiliations":[{"id":39398,"text":"JMA","active":true,"usgs":false}],"preferred":false,"id":781355,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":781350,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":781356,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hauksson, E.","contributorId":196003,"corporation":false,"usgs":false,"family":"Hauksson","given":"E.","affiliations":[],"preferred":false,"id":781357,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Heaton, T.","contributorId":222141,"corporation":false,"usgs":false,"family":"Heaton","given":"T.","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":781358,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70227742,"text":"70227742 - 2020 - Combined influence of intrinsic and environmental factors in shaping productivity in a small pelagic gull, the black-legged kittiwake Rissa tridactyla","interactions":[],"lastModifiedDate":"2022-01-28T16:01:47.756094","indexId":"70227742","displayToPublicDate":"2020-01-09T09:57:37","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Combined influence of intrinsic and environmental factors in shaping productivity in a small pelagic gull, the black-legged kittiwake <i>Rissa tridactyla</i>","title":"Combined influence of intrinsic and environmental factors in shaping productivity in a small pelagic gull, the black-legged kittiwake Rissa tridactyla","docAbstract":"<p><span>While we have a good understanding in many systems of the effects of single variable changes on organisms, we understand far less about how variables act in concert to affect living systems, where interactions among variables can lead to unanticipated results. We used mixed-effect models to evaluate the effects of multiple variables that we expected to play a role in the early reproductive stages of a North Pacific seabird, the black-legged kittiwake&nbsp;</span><i>Rissa tridactyla,</i><span>&nbsp;during 1992-2008 using data collected on known-aged individuals. Our work revealed the potential for contrasting stressor effects across successive stages of reproduction. Bird age, timing of egg laying, and winter ENSO conditions best explained individual laying success, such that laying success was greater when parents were older, the average winter ENSO index was positive (as occurs during El Niño episodes), and the median laying date for the colony was earlier. Age and salmon run timing (a proxy for predator presence at the colony) best explained hatching success, such that hatching success was greater when parents were older and when salmon runs were early. Identifying such differential effects of multiple stressors across consecutive reproductive stages can greatly enhance our ability to interpret trends and manage populations in the face of changes currently occurring in living systems.</span></p>","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/meps13162","usgsCitation":"McKnight, A., Irons, D., Loftin, C., McKinney, S., and Olsen, B., 2020, Combined influence of intrinsic and environmental factors in shaping productivity in a small pelagic gull, the black-legged kittiwake Rissa tridactyla: Marine Ecology Progress Series, v. 633, p. 207-223, https://doi.org/10.3354/meps13162.","productDescription":"17 p.","startPage":"207","endPage":"223","ipdsId":"IP-088508","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"633","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKnight, Aly","contributorId":272505,"corporation":false,"usgs":false,"family":"McKnight","given":"Aly","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":832006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irons, David B.","contributorId":272506,"corporation":false,"usgs":false,"family":"Irons","given":"David B.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":832007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832005,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKinney, Shawn T.","contributorId":272507,"corporation":false,"usgs":false,"family":"McKinney","given":"Shawn T.","affiliations":[],"preferred":false,"id":832008,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olsen, Brian J.","contributorId":272508,"corporation":false,"usgs":false,"family":"Olsen","given":"Brian J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":832009,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70207989,"text":"70207989 - 2020 - Challenges for leveraging citizen science to support statistically robust monitoring programs","interactions":[],"lastModifiedDate":"2020-01-23T06:36:56","indexId":"70207989","displayToPublicDate":"2020-01-09T06:35:43","publicationYear":"2020","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":"Challenges for leveraging citizen science to support statistically robust monitoring programs","docAbstract":"Large samples and long time series are often needed for effective broad-scale monitoring of status and trends in wild populations. Obtaining those sample sizes can be more feasible when volunteers contribute to the dataset, but volunteer-selected sites are not always representative of a population. Previous work to account for biased site selection has relied on knowledge of covariates to explain differences between site types, but such knowledge is often unavailable. For cases where relevant covariates have not been defined, we used a simulation study to identify the consequences of including non-probabilistically selected sites (NP sites) in addition to sites selected from a probability-based design (P sites), test modeling frameworks that might correct for biases, and evaluate whether those frameworks could allow NP sites to reduce the sampling requirement for P sites and potentially reduce costs of monitoring. We informed the simulation with pilot data from surveys of monarch butterflies and their obligate larval host plant, milkweed. We found strong biases in NP sites versus P sites in density and trends of monarchs and milkweed. Modeling frameworks that accounted for site type with a group effect or that strongly downweighted NP sites successfully produced unbiased estimates. However, sampling more NP sites typically did not improve accuracy or precision, and adding NP sites sometimes required also adding P sites to prevent biases. Further work on novel modeling frameworks would be useful to allow citizen-science data to contribute useful information to conservation.","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2020.108411","usgsCitation":"Weiser, E.L., Diffendorfer, J., Lopez-Hoffman, L., Semmens, D., and Thogmartin, W.E., 2020, Challenges for leveraging citizen science to support statistically robust monitoring programs: Biological Conservation, v. 242, 108411, 10 p., https://doi.org/10.1016/j.biocon.2020.108411.","productDescription":"108411, 10 p.","ipdsId":"IP-112580","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":458175,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2020.108411","text":"Publisher Index Page"},{"id":371491,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"242","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Weiser, Emily L. 0000-0003-1598-659X","orcid":"https://orcid.org/0000-0003-1598-659X","contributorId":213770,"corporation":false,"usgs":true,"family":"Weiser","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":780046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":780047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lopez-Hoffman, Laura","contributorId":149127,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":17654,"text":"School of Natural Resources & the Environment and Udall Center for Studies in Public Policy, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":780048,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Semmens, Darius J. 0000-0001-7924-6529","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":64201,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":780049,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":780050,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70207244,"text":"sir20195141 - 2020 - Water-balance techniques for determining available soil-water storage for selected sandy and clay soil study sites in Cass County, North Dakota, 2016–17","interactions":[],"lastModifiedDate":"2022-04-25T20:16:09.086144","indexId":"sir20195141","displayToPublicDate":"2020-01-08T16:45:00","publicationYear":"2020","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":"2019-5141","displayTitle":"Water-Balance Techniques for Determining Available Soil-Water Storage for Selected Sandy and Clay Soil Study Sites in Cass County, North Dakota, 2016–17","title":"Water-balance techniques for determining available soil-water storage for selected sandy and clay soil study sites in Cass County, North Dakota, 2016–17","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service, collected field and remotely sensed data on precipitation, evapotranspiration (ET), and soil-water content to determine available soil-water storage (AWS) at six study sites on sandy and clay soils in Cass County, North Dakota. Data were collected at all the study sites from May 1–October 31, 2016, and from May 1–October 24, 2017. Estimated daily AWS was determined using daily meteorological and potential evapotranspiration (PET) data obtained from various climate stations, and estimated monthly AWS was determined using monthly meteorological and PET data and monthly ET data determined using the Operational Simplified Surface Energy Balance model. AWS during 2016 and 2017 was determined at daily and monthly time steps because of data availability and to assess results using varying time steps. Comparisons of measured and estimated daily values of AWS at the Brewer Lake site indicated poor agreement during May–October 2016 and May–October 2017. Comparisons of measured and estimated daily values of AWS at the Embden East and Embden West sites indicated poor and fair agreement respectively. At the Lynchburg Crop and Lynchburg Grass sites, comparisons of measured and estimated daily values of AWS indicated fair and good relations, respectively, even with the possible effects of soil cracks. Mean estimated values of daily runoff plus soil percolation for the four sandy soil sites indicated that a maximum of about 19 percent of the estimated runoff plus soil percolation could be considered runoff and that the remaining 81 percent could be considered soil percolation, and for the two clay soil sites about 13 percent of the runoff plus soil percolation could have been considered runoff and about 87 percent could have been considered soil percolation. Results indicated little difference between using monthly PET or monthly ET in water-balance equations to estimate monthly AWS for the grouped sandy soil sites, and only slightly better results were obtained using monthly PET than monthly ET to estimate monthly AWS for the grouped clay soil study sites. Overall, the monthly water-balance models did not perform as well as the daily water-balance models for determining AWS at the six study sites. Additional data collection from a longer-period study and adjustments to the models may improve results from the monthly water-balance techniques.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195141","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service","usgsCitation":"Vining, K.C., 2020, Water-balance techniques for determining available soil-water storage for selected sandy and clay soil study sites in Cass County, North Dakota, 2016–17: U.S. Geological Survey Scientific Investigations Report 2019–5141, 39 p., https://doi.org/10.3133/sir20195141.","productDescription":"Report: vii, 39 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-098347","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":399616,"rank":4,"type":{"id":36,"text":"NGMDB Index 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<a href=\"https://www.usgs.gov/centers/dakota-water\" data-mce-href=\"https://www.usgs.gov/centers/dakota-water\">Dakota Water Science Center</a><br>U.S. Geological Survey<br>821 East Interstate Avenue<br>Bismarck, ND 58503<br>1608 Mountain View Road<br>Rapid City, SD 57702</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results of Water-Balance Techniques and Available Soil-Water Storage Analyses</li><li>Limitations</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-01-08","noUsgsAuthors":false,"publicationDate":"2020-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Vining, Kevin C. 0000-0001-5738-3872","orcid":"https://orcid.org/0000-0001-5738-3872","contributorId":221225,"corporation":false,"usgs":true,"family":"Vining","given":"Kevin","email":"","middleInitial":"C.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777428,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70219522,"text":"70219522 - 2020 - Components and predictors of biological soil crusts vary at the regional vs. plant community scales","interactions":[],"lastModifiedDate":"2021-04-12T13:30:31.762854","indexId":"70219522","displayToPublicDate":"2020-01-08T08:28:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Components and predictors of biological soil crusts vary at the regional vs. plant community scales","docAbstract":"<p><span>Although biological soil crusts (biocrusts) occur globally in arid and semi-arid environments, most of our knowledge of biocrust cover and ecology is from a relatively small number of locations worldwide. Some plant communities are known to have high cover of biocrusts, but the abundance of biocrusts is largely undocumented in most plant communities. Using a data driven approach, we identified 16 plant communities based on plant cover from the Assessment, Inventory, and Monitoring Strategy data from the Bureau of Land Management (AIM, 5,200 plots). We found that abundance of lichens and mosses varies among communities, but that both components of biocrusts are present in all plant communities. Biocrusts are indicators of two of these communities: one that is defined by high cover of mosses and basin big sagebrush and one that is defined by high cover of lichens and shadscale saltbush. Using non-parametric multiplicative regression, we evaluated a suite of abiotic and disturbance variables to assess the degree to which climate and soils are associated with the abundance of lichens and mosses at the regional scale. At the regional scale, soil depth and maximum vapor pressure deficit were found to be strongly associated with the abundance of lichens and January minimum temperature dictated the abundance of mosses. At the scale of plant communities, community specific metrics of soils and climate were better able to explain the abundance of biocrusts. Our demonstration of the presence of biocrusts across the western US suggests that studies on ecosystem function could include these organisms because they are present in all plant communities, maintain arguably stronger associations with climatic variation, are directly associated with soils, and contribute to ecosystem functions that are not solely maintained by vascular plants.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2019.00449","usgsCitation":"Condon, L.A., and Pyke, D.A., 2020, Components and predictors of biological soil crusts vary at the regional vs. plant community scales: Frontiers in Ecology and Evolution, v. 7, 449, 10 p., https://doi.org/10.3389/fevo.2019.00449.","productDescription":"449, 10 p.","ipdsId":"IP-101902","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":458184,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2019.00449","text":"Publisher Index Page"},{"id":385005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","noUsgsAuthors":false,"publicationDate":"2020-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Condon, Lea A. 0000-0002-9357-3881","orcid":"https://orcid.org/0000-0002-9357-3881","contributorId":202908,"corporation":false,"usgs":true,"family":"Condon","given":"Lea","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813925,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209229,"text":"70209229 - 2020 - Characterization of the genetic structure of four sucker species in the Klamath River. Final Report","interactions":[],"lastModifiedDate":"2020-03-26T06:42:12","indexId":"70209229","displayToPublicDate":"2020-01-08T06:47:21","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Characterization of the genetic structure of four sucker species in the Klamath River. Final Report","docAbstract":"Four species of suckers (family Catostomidae) inhabit the Klamath River Basin of Oregon and California: Lost River suckers (LRS; Deltistes luxatus), shortnose suckers (SNS; Chasmistes brevirostris), Klamath largescale suckers (KLS; Catostomus snyderi), and Klamath smallscale suckers (KSS; Catostomus rimiculus). All but Klamath smallscale suckers are endemic and restricted to the Klamath River Basin where they occur sympatrically in large lakes and reservoirs, including the Lost River and Klamath Lake subbasins (Figure 1; USFWS 2012).\nPopulation declines, primarily due to loss or degradation of spawning, rearing, and adult habitat, have resulted in Lost River and shortnose suckers being listed as endangered throughout their entire range under the U.S. Endangered Species Act (USFWS 1988).\n\nContinued population declines coupled with failed adult recruitment prompted the USFWS to initiate an assisted rearing program in 2015 as a part of their recovery strategy (Childress et al. 2019). The program was designed to maintain as much genetic diversity as possible while improving recruitment by averting high early life stage mortality (Day et al. 2017). However, while assisted rearing efforts are targeted towards endangered LRS and SNS, species differentiation of larval and juvenile suckers is problematic in the Klamath River Basin. This, in turn, complicates the management of these species as well as the population modeling used to evaluate recovery efforts. Maintaining as much as possible of the genetic resources, or “evolutionary legacy” of a species is a goal common to conservation and endangered species recovery strategies. Inappropriate assumptions regarding species’ evolutionary lineages, and genetic characteristics may lead to the mismanagement of an endangered species through a failure to recognize and appropriately manage species boundaries and genetic population structure.\n\nDespite a considerable amount of research, the partitioning of genetic diversity within and among the four species of suckers in the Klamath River Basin remains unclear. Previously developed genetic markers are effective at differentiating some species, but fail to effectively differentiate all four species of suckers in the basin (Tranah et al. 2001; Wagman 2003; Tranah and May 2006; Hoy and Ostberg 2015; Dowling et al. 2016). Peer-reviewed publications describing the morphological characteristics of (Markle et al. 2005) and genetic relationships\n \namong (Dowling et al. 2016; Tranah and May 2006) Klamath River Basin suckers have not resolved uncertainties regarding the systematic relationships among the four currently recognized taxa. Specifically, genetic and morphological data generally support LRS and KSS as being distinct entities, but genetic evidence does not support a distinction between KLS and SNS. All three publications above refer to unpublished information regarding ecological differences between KLS and SNS as evidence to support the existence of two entities. However, the authors also acknowledge that overlap in morphological characters (Markle et al. 2005) and a lack of genetic differentiation (Dowling et al. 2016; Tranah and May 2006) between KLS and SNS raises the question of their specific identity. This is particularly problematic in the Lost River subbasin, where overlap in morphological characters between KLS and SNS is greatest.\n\nIn our opinion, the basis of the strong genetic similarity between KLS and SNS has not been resolved. Morphological characters mostly support the existence of two distinct species, while genetic characters do not (i.e., genetic divergence between KLS and SNS is less than divergence among populations of each species; (Smith et al. 2015). Some have suggested that introgressive hybridization may have resulted in a lack of genetic differentiation between KLS and SNS and a breakdown of monophyletic species (Dowling et al. 2016; Tranah and May 2006), and that this hybridization may be an important process in","language":"English","publisher":"U.S. Fish and Wildlife Service","collaboration":"Bureau of Reclamation","usgsCitation":"Smith, M., Von Bargen, J., Smith, C.A., Miller, M.A., Rasmussen, J., and Hewitt, D.A., 2020, Characterization of the genetic structure of four sucker species in the Klamath River. Final Report, 32 p.","productDescription":"32 p.","ipdsId":"IP-115877","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":373497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":373490,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/aftc/Reports.cfm"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.695068359375,\n              40.88029480552824\n            ],\n            [\n              -120.9375,\n              40.88029480552824\n            ],\n            [\n              -120.9375,\n              42.83569550641452\n            ],\n            [\n              -123.695068359375,\n              42.83569550641452\n            ],\n            [\n              -123.695068359375,\n              40.88029480552824\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Matt","contributorId":223557,"corporation":false,"usgs":false,"family":"Smith","given":"Matt","email":"","affiliations":[{"id":40741,"text":"USFWS, Abernathy Fish Technology Center, Longview, WA","active":true,"usgs":false}],"preferred":false,"id":785470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Von Bargen, Jennifer","contributorId":223558,"corporation":false,"usgs":false,"family":"Von Bargen","given":"Jennifer","email":"","affiliations":[{"id":40741,"text":"USFWS, Abernathy Fish Technology Center, Longview, WA","active":true,"usgs":false}],"preferred":false,"id":785471,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Christian A.","contributorId":200768,"corporation":false,"usgs":false,"family":"Smith","given":"Christian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":785472,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Michael A.","contributorId":85920,"corporation":false,"usgs":false,"family":"Miller","given":"Michael","email":"","middleInitial":"A.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":785473,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rasmussen, Josh","contributorId":223559,"corporation":false,"usgs":false,"family":"Rasmussen","given":"Josh","email":"","affiliations":[{"id":40742,"text":"USFWS, Klamath Falls Fish and Wildlife Office, Klamath Falls, OR","active":true,"usgs":false}],"preferred":false,"id":785474,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":785475,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70208949,"text":"70208949 - 2020 - Using a dense seismic array to determine structure and site effects of the Two Towers earthflow in northern California","interactions":[],"lastModifiedDate":"2020-03-09T06:45:36","indexId":"70208949","displayToPublicDate":"2020-01-08T06:43:41","publicationYear":"2020","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":"Using a dense seismic array to determine structure and site effects of the Two Towers earthflow in northern California","docAbstract":"We deployed a network of 68 three-component geophones on the slow moving Two\n\tTowers earthflow in northern California. We compute horizontal-to-vertical spectral ratios\n\t(HVSRs) from the ambient seismic field. The HVSRs have two prominent peaks, one near\n\t1.23 Hz and another between 4 and 8 Hz at most stations. The 1.23 Hz resonance is a property of the background noise field and may be due to a velocity contrast at a few hundred\n\tmeters depth. We interpret the higher frequency peaks as being related to slide deposits and invert the spectral ratios for shallow velocity structure using in situ thickness measurements\n\tas a priori constraints on the inversion. The thickness of the shallowest, low-velocity layer\n\tis systematically larger than landslide thicknesses inferred from inclinometer data acquired\n\tsince 2013. Given constraints from field observations and boreholes, the inversion may reflect the thickness of deposits of an older slide that is larger in spatial extent and depth than\n\tthe currently active slide. Because the HVSR peaks measured at Two Towers are caused by shallow slide deposits and represent frequencies that will experience amplification during\n\tearthquakes, the depth of the actively sliding mass may be less relevant for assessing potential slide volume and associated hazard than the thicknesses determined by our inversions.\n\tMore generally, our results underscore the utility of combining both geotechnical measurements and subsurface imaging for landslide characterization and hazard assessment.","language":"English","publisher":"GSW","doi":"10.1785/0220190206","usgsCitation":"Thomas, A.M., Spica, Z., Bodmer, M., Schulz, W.H., and Roering, J., 2020, Using a dense seismic array to determine structure and site effects of the Two Towers earthflow in northern California: Seismological Research Letters, v. 91, no. 2A, p. 913-920, https://doi.org/10.1785/0220190206.","productDescription":"8 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Oregon","active":true,"usgs":false}],"preferred":false,"id":784145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schulz, William H. 0000-0001-9980-3580 wschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-9980-3580","contributorId":942,"corporation":false,"usgs":true,"family":"Schulz","given":"William","email":"wschulz@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":784146,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roering, Joshua J.","contributorId":194297,"corporation":false,"usgs":false,"family":"Roering","given":"Joshua J.","affiliations":[],"preferred":false,"id":784147,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70208745,"text":"70208745 - 2020 - Resolving small-scale forest snow patterns using an energy-balance snow model with a 1-layer canopy","interactions":[],"lastModifiedDate":"2020-02-28T06:31:32","indexId":"70208745","displayToPublicDate":"2020-01-08T06:28:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Resolving small-scale forest snow patterns using an energy-balance snow model with a 1-layer canopy","docAbstract":"Modelling spatiotemporal dynamics of snow in forests is challenging, as involved processes are strongly dependent on small-scale canopy properties. In this study, we explore how local canopy structure information can be integrated in a medium-complexity energy-balance snow model to replicate observed snow patterns at very high spatial resolutions. Snow depth distributions simulated with the Flexible Snow Model (FSM2) were tested against extensive experimental data acquired in discontinuous subalpine forest stands in Eastern Switzerland over three winters. While the default canopy implementation in FSM2 fails to capture the observed snow depth variability, performance is considerably improved when local canopy cover fraction and hemispherical sky view fraction are additionally accounted for (30% reduction in RMSE). However, realistic snow depth distribution patterns throughout the season are only achieved if effective temperatures of near and distant canopy elements are discerned, and if a mechanism to mimic preferential deposition of snow in canopy gaps is included. We demonstrate that by diversifying the canopy structure input in order to reflect respective portions of the canopy relevant to different processes, even a simple model based on widely used process parametrizations and canopy metrics can be applied for high-resolution simulations of the sub-canopy snow cover with just a few modifications. The presented approaches could be implemented in commonly used land surface models, allowing upscaling experiments and development of sub-grid parametrizations without necessitating complex high-resolution models.","language":"English","publisher":"Wiley","doi":"10.1029/2019WR026129","usgsCitation":"Mazzotti, G., Essery, R., Moeser, C.D., and Jonas, T., 2020, Resolving small-scale forest snow patterns using an energy-balance snow model with a 1-layer canopy: Water Resources Research, v. 56, no. 1, e2019WR026129, 22 p., https://doi.org/10.1029/2019WR026129.","productDescription":"e2019WR026129, 22 p.","ipdsId":"IP-112070","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":458191,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.research.ed.ac.uk/en/publications/941ef274-b54b-48d0-8263-ae1287bd8584","text":"External Repository"},{"id":372718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Switzerland","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[9.59423,47.52506],[9.63293,47.3476],[9.47997,47.10281],[9.93245,46.92073],[10.4427,46.89355],[10.36338,46.48357],[9.92284,46.3149],[9.18288,46.44021],[8.96631,46.03693],[8.48995,46.00515],[8.31663,46.16364],[7.75599,45.82449],[7.27385,45.77695],[6.84359,45.99115],[6.5001,46.42967],[6.02261,46.27299],[6.03739,46.72578],[6.76871,47.28771],[6.73657,47.5418],[7.1922,47.44977],[7.46676,47.62058],[8.3173,47.61358],[8.52261,47.83083],[9.59423,47.52506]]]},\"properties\":{\"name\":\"Switzerland\"}}]}","volume":"56","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Mazzotti, Giulia","contributorId":222821,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Giulia","email":"","affiliations":[{"id":40604,"text":"WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland and Laboratory of Hydraulics, Hydrology and Glaciology, ETHZ, Zurich, Switzerland","active":true,"usgs":false}],"preferred":false,"id":783256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Essery, Richard","contributorId":222822,"corporation":false,"usgs":false,"family":"Essery","given":"Richard","email":"","affiliations":[{"id":40605,"text":"School of Geosciences, University of Edinburgh, Edinburgh, UK","active":true,"usgs":false}],"preferred":false,"id":783257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moeser, C. David 0000-0003-0154-9110","orcid":"https://orcid.org/0000-0003-0154-9110","contributorId":214563,"corporation":false,"usgs":true,"family":"Moeser","given":"C.","email":"","middleInitial":"David","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jonas, Tobias","contributorId":222823,"corporation":false,"usgs":false,"family":"Jonas","given":"Tobias","email":"","affiliations":[{"id":40606,"text":"WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":783258,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70208690,"text":"70208690 - 2020 - Acute toxicity of the lampricides TFM and niclosamide: Effects on a vascular plant and a chironomid species","interactions":[],"lastModifiedDate":"2020-02-25T06:38:59","indexId":"70208690","displayToPublicDate":"2020-01-07T19:05:40","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Acute toxicity of the lampricides TFM and niclosamide: Effects on a vascular plant and a chironomid species","docAbstract":"The lampricides 3-trifluoromethyl-4-nitrophenol (TFM) and niclosamide have been used for about 60 years to control sea lamprey (Petromyzon marinus) in the Great Lakes Basin and Lake Champlain.  To register these chemicals as pesticides in North America, their environmental effects must be reviewed on a periodic basis.  As a part of this effort, toxicity of TFM and niclosamide to duckweed (Lemna gibba), and of niclosamide to aquatic midge (Chironomus tentans), was assessed.  Results of these studies suggest that for both lampricides, the no-observable and lowest observable effects concentrations (NOEC and LOEC) exceed expected environmental concentrations, with effects only in the highest concentrations tested and the longest exposure times.  Duckweed exposed to TFM indicated 7-day LOECs ≥ 4.88 mg/L for average specific growth rate and yield, with the EC50 > 9.74 mg/L.  For duckweed exposed to niclosamide, 7-day LOECs for average specific growth rate and yield ranged from 0.271 to 0.569 mg/L, with the IC50 0.725 mg/L or greater depending on the parameter measured.  For midge larvae exposed to niclosamide-dosed sediment, the LOEC values based on survival and growth were 26.2 mg/kg and > 82.1 mg/kg, respectively, and the EC50 based on survival was 49.6 mg/kg.  Based on these data, deleterious effects on aquatic plants and benthic invertebrates are unlikely to result from use of TFM and niclosamide for lamprey control, given that the effect concentrations are in excess of the expected environmental concentrations.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2019.11.007","usgsCitation":"Leak, T., Aufderheide, J., Bergfield, A., and Hubert, T.D., 2020, Acute toxicity of the lampricides TFM and niclosamide: Effects on a vascular plant and a chironomid species: Journal of Great Lakes Research, v. 46, no. 1, p. 180-187, https://doi.org/10.1016/j.jglr.2019.11.007.","productDescription":"8 p.","startPage":"180","endPage":"187","ipdsId":"IP-094759","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":372592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Great Lakes Basin, Lake Champlain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.5048828125,\n              47.07012182383309\n            ],\n            [\n              -92.6806640625,\n              46.89023157359399\n            ],\n            [\n              -91.845703125,\n              45.336701909968134\n            ],\n            [\n              -90.791015625,\n              42.87596410238256\n            ],\n            [\n              -89.384765625,\n              42.032974332441405\n            ],\n            [\n              -87.36328125,\n              41.178653972331674\n            ],\n            [\n              -86.044921875,\n              41.50857729743935\n            ],\n            [\n              -85.69335937499999,\n              43.13306116240612\n            ],\n            [\n              -84.814453125,\n              43.929549935614595\n            ],\n            [\n              -84.5068359375,\n              42.68243539838623\n            ],\n            [\n              -83.671875,\n              41.47566020027821\n            ],\n            [\n              -82.30957031249999,\n              40.245991504199026\n            ],\n            [\n              -77.607421875,\n              42.16340342422401\n            ],\n            [\n              -74.091796875,\n              43.77109381775651\n            ],\n            [\n              -70.7958984375,\n              44.653024159812\n            ],\n            [\n              -73.95996093749999,\n              46.22545288226939\n            ],\n            [\n              -77.607421875,\n              44.77793589631623\n            ],\n            [\n              -80.244140625,\n              46.6795944656402\n            ],\n            [\n              -83.3642578125,\n              48.22467264956519\n            ],\n            [\n              -86.8798828125,\n              49.439556958940855\n            ],\n            [\n              -89.12109375,\n              49.009050809382046\n            ],\n            [\n              -92.5048828125,\n              47.07012182383309\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"46","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Leak, Tom","contributorId":222717,"corporation":false,"usgs":false,"family":"Leak","given":"Tom","email":"","affiliations":[{"id":40594,"text":"EAG Laboratories","active":true,"usgs":false}],"preferred":false,"id":783007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aufderheide, John","contributorId":222718,"corporation":false,"usgs":false,"family":"Aufderheide","given":"John","email":"","affiliations":[{"id":40594,"text":"EAG Laboratories","active":true,"usgs":false}],"preferred":false,"id":783008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergfield, Alan","contributorId":222719,"corporation":false,"usgs":false,"family":"Bergfield","given":"Alan","email":"","affiliations":[{"id":40594,"text":"EAG Laboratories","active":true,"usgs":false}],"preferred":false,"id":783009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hubert, Terrance D. 0000-0001-9712-1738 thubert@usgs.gov","orcid":"https://orcid.org/0000-0001-9712-1738","contributorId":3036,"corporation":false,"usgs":true,"family":"Hubert","given":"Terrance","email":"thubert@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":783006,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70208125,"text":"70208125 - 2020 - Habitat of the endangered salt marsh harvest mouse (Reithrodontomys raviventris) in San Francisco Bay","interactions":[],"lastModifiedDate":"2020-02-06T11:44:25","indexId":"70208125","displayToPublicDate":"2020-01-07T16:40:04","publicationYear":"2020","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}},"displayTitle":"Habitat of the endangered salt marsh harvest mouse (<i>Reithrodontomys raviventris</i>) in San Francisco Bay","title":"Habitat of the endangered salt marsh harvest mouse (Reithrodontomys raviventris) in San Francisco Bay","docAbstract":"<p><span>Understanding habitat associations is vital for conservation of at‐risk marsh‐endemic wildlife species, particularly those under threat from sea level rise. We modeled environmental and habitat associations of the marsh‐endemic, Federally endangered salt marsh harvest mouse (</span><i>Reithrodontomys raviventris</i><span>, RERA) and co‐occurrence with eight associated small mammal species from annual trap data, 1998–2014, in six estuarine marshes in North San Francisco Bay, California. Covariates included microhabitat metrics of elevation and vegetation species and cover; and landscape metrics of latitude–longitude, distance to anthropogenic features, and habitat patch size. The dominant cover was pickleweed (</span><i>Salicornia pacifica</i><span>) with 86% mean cover and 37&nbsp;cm mean height, and bare ground with about 10% mean cover. We tested 38 variants of Bayesian network (BN) models to determine covariates that best account for presence of RERA and of all nine small mammal species. Best models had lowest complexity and highest classification accuracy. Among RERA presence models, three best BN models used covariates of latitude–longitude, distance to paved roads, and habitat patch size, with 0% error of false presence, 20% error of false nonpresence, and 20% overall error. The all‐species presence models suggested that within the pickleweed marsh environment, RERA are mostly habitat generalists. Accounting for presence of other species did not improve prediction of RERA. Habitat attributes compared between RERA and the next most frequently captured species, California vole (</span><i>Microtus californicus</i><span>), suggested substantial habitat overlap, with RERA habitat being somewhat higher in marsh elevation, greater in percent cover of the dominant plant species, closer to urban areas, further from agricultural areas, and, perhaps most significant, larger in continuous size of marsh patch. Findings will inform conservation management of the marsh environment for RERA by identifying best microhabitat elements, landscape attributes, and adverse interspecific interactions.</span></p>","language":"English","publisher":"Wiley-Blackwell","doi":"10.1002/ece3.5860","usgsCitation":"Marcot, B.G., Woo, I., Thorne, K., Freeman, C.M., and Guntenspergen, G.R., 2020, Habitat of the endangered salt marsh harvest mouse (Reithrodontomys raviventris) in San Francisco Bay: Ecology and Evolution, v. 0, no. 2, p. 662-677, https://doi.org/10.1002/ece3.5860.","productDescription":"16 p.","startPage":"662","endPage":"677","ipdsId":"IP-101159","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458198,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5860","text":"Publisher Index Page"},{"id":437176,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96Q5D2T","text":"USGS data release","linkHelpText":"Small mammal surveys from northern San Francisco Bay: 1998-2014"},{"id":371662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.7117919921875,\n              37.82497195707114\n            ],\n            [\n              -121.98669433593749,\n              37.82497195707114\n            ],\n            [\n              -121.98669433593749,\n              38.190704293996504\n            ],\n            [\n              -122.7117919921875,\n              38.190704293996504\n            ],\n            [\n              -122.7117919921875,\n              37.82497195707114\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"0","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Marcot, Bruce G.","contributorId":152612,"corporation":false,"usgs":false,"family":"Marcot","given":"Bruce","email":"","middleInitial":"G.","affiliations":[{"id":18944,"text":"Pacific Northwest Research Station, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":780617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeman, Chase M. 0000-0003-4211-6709 cfreeman@usgs.gov","orcid":"https://orcid.org/0000-0003-4211-6709","contributorId":150052,"corporation":false,"usgs":true,"family":"Freeman","given":"Chase","email":"cfreeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780619,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":780620,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70210790,"text":"70210790 - 2020 - Petrologic insights into rift zone magmatic interactions from the 2011 eruption of Kīlauea Volcano, Hawaiʻi","interactions":[],"lastModifiedDate":"2020-06-25T14:54:58.664449","indexId":"70210790","displayToPublicDate":"2020-01-07T09:50:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2420,"text":"Journal of Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Petrologic insights into rift zone magmatic interactions from the 2011 eruption of Kīlauea Volcano, Hawaiʻi","docAbstract":"The high frequency of historical eruptions at Kīlauea Volcano presents an exceptional opportunity to address fundamental questions related to the transport, storage, and interaction of magmas within rift zones. The Nāpau Crater area on Kīlauea’s East Rift Zone (ERZ) experienced nine fissure eruptions within 50 years (1961–2011). Most of the magma intruded during these frequent eruptions remained stored within the rift zone, creating a potential magma mixing depot within the ERZ. The superbly monitored and sampled 2011 eruption (Puʻu ʻŌʻō episode 59) presents an extraordinary opportunity to evaluate magma mixing processes within the ERZ. Whole-rock, glass, and olivine compositions were determined, not only for lava from the 2011 eruption, but also for a new suite of Nāpau Crater area samples from the 1963, 1965, 1968, 1983, and 1997 eruptions, as well as the previously undocumented 1922 eruption. Whole-rock XRF data revealed two geochemically distinct magma batches for episode 59: one less evolved (∼6·6 wt % MgO, 0·46 wt % K2O) than the other (∼6·2 wt % MgO, 0·58 wt % K2O). Episode 59 lava is remarkably aphyric (∼0·1 vol. % phenocrysts), making use of mineralogy to identify parent magma affinities problematic. Linear compositional trends of whole-rock major and trace elements, and reversely zoned olivine crystals indicate episode 59 lavas underwent magma mixing. Least squares regression calculations and plots of major and trace element data, were used to evaluate whether the episode 59 samples are products of mixing summit-derived magma with residual magma from previous Nāpau Crater area eruptions. The regression results and trace element ratios are inconsistent with previously proposed mixing scenarios, but they do support mixing between summit-derived magma and residual magma from the 1983 and 1997 Nāpau Crater area eruptions. These magmas were stored in physically and chemically distinct pods at depths of 1·6–3·0 km prior to mixing with new magma intruded from the summit to produce the episode 59 lava. One pod contained a fractionated equivalent of 1983 lava, and the other a hybrid of compositions similar to 1983 and 1997 lavas. The petrology of episode 59 lava demonstrates that magmas from two previous eruptions (1983 and 1997) were available to mix with magma intruded from the summit region. This study clarifies the pre-eruptive history of the mixed episode 59 lava, and elucidates the evolution of the volcano's magmatic system in a region of frequent eruptions.","language":"English","publisher":"Oxford University Press","doi":"10.1093/petrology/egz064","usgsCitation":"Walker, B.H., Garcia, M.O., and Orr, T.R., 2020, Petrologic insights into rift zone magmatic interactions from the 2011 eruption of Kīlauea Volcano, Hawaiʻi: Journal of Petrology, v. 60, no. 11, p. 2051-2075, https://doi.org/10.1093/petrology/egz064.","productDescription":"25 p.","startPage":"2051","endPage":"2075","ipdsId":"IP-091040","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":458203,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/petrology/egz064","text":"Publisher Index Page"},{"id":375917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"East Rift Zone","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.3521728515625,\n              19.16592425362802\n            ],\n            [\n              -155.01708984375,\n              19.16592425362802\n            ],\n            [\n              -155.01708984375,\n              19.33706180106996\n            ],\n            [\n              -155.3521728515625,\n              19.33706180106996\n            ],\n            [\n              -155.3521728515625,\n              19.16592425362802\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"60","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Walker, Brett H.","contributorId":225523,"corporation":false,"usgs":false,"family":"Walker","given":"Brett","email":"","middleInitial":"H.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":791433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Michael O.","contributorId":225524,"corporation":false,"usgs":false,"family":"Garcia","given":"Michael","email":"","middleInitial":"O.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":791434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orr, Tim R. 0000-0003-1157-7588 torr@usgs.gov","orcid":"https://orcid.org/0000-0003-1157-7588","contributorId":149803,"corporation":false,"usgs":true,"family":"Orr","given":"Tim","email":"torr@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":791435,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70209618,"text":"70209618 - 2020 - Copper concentrations in the upper Columbia River as a limiting factor in White Sturgeon recruitment and recovery","interactions":[],"lastModifiedDate":"2020-04-16T13:04:55.09969","indexId":"70209618","displayToPublicDate":"2020-01-07T08:01:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Copper concentrations in the upper Columbia River as a limiting factor in White Sturgeon recruitment and recovery","docAbstract":"Currently there is little natural recruitment of white sturgeon (Acipenser transmontanus) in the Upper Columbia River located in British Columbia, Canada and Washington, USA. This review of life history, physiology, and behavior of white sturgeon, along with data from recent toxicological studies, suggest that trace metals, especially Cu, affect survival and behavior of early life stage fish. Sturgeon free embryos, first feeding embryos, and mixed feeding embryos utilize interstitial \nspaces between gravel. Although concentrations of Cu in the water column of the Upper Columbia River are typically less than US water quality criteria defined to protect aquatic life, samples at the sediment–water interface were as large as 24 µg/L and exceed the criteria. Toxicological studies reviewed here demonstrate mortality, loss of equilibrium, and immobility at Cu concentrations of 1.5 to <16 µg/L and reduced swimming activity was documented at 0.88 to 7 μg/L. Contaminated invertebrates and slag particles provide other routes of exposure. These additional routes of exposure can cause indirect effects from starvation due to potential lack of prey items and ingestion of contaminated prey or slag particles. The lack of food in stomachs during these critical early life stages may coincide with a threshold “point of no return” at which sturgeon will be unable to survive even if food becomes available following that early time frame. These findings become especially important as work progresses to enhance white sturgeon recruitment in the Upper Columbia River. To date, decisions against including trace metals as a factor in sturgeon recovery have focused on surface‐water concentrations and measurements of lethality (LC50) to establish threshold concentrations for sturgeon sensitivity. However, information provided here suggests that measurements from the sediment–water interface and effect concentrations (EC50) be considered with white sturgeon life history characteristics. These data support minimizing Cu exposure risk to enhance a successful white sturgeon recovery effort.","language":"English","publisher":"SETAC","doi":"10.1002/ieam.4240","collaboration":"","usgsCitation":"Puglis, H.J., Farag, A., and Mebane, C.A., 2020, Copper concentrations in the upper Columbia River as a limiting factor in White Sturgeon recruitment and recovery: Integrated Environmental Assessment and Management, v. 16, no. 3, p. 378-391, https://doi.org/10.1002/ieam.4240.","productDescription":"14 p.","startPage":"378","endPage":"391","ipdsId":"IP-098467","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":374050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","state":"Washington, British Columbia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.71850585937501,\n              49.23194729854554\n            ],\n            [\n              -117.784423828125,\n              49.75287993415023\n            ],\n            [\n              -118.828125,\n              49.78835749241399\n            ],\n            [\n              -118.89404296875,\n              49.01625665778159\n            ],\n            [\n              -120.73974609374999,\n              49.01625665778159\n            ],\n            [\n              -120.62988281249999,\n              48.23199134320962\n            ],\n            [\n              -120.421142578125,\n              46.475699386607516\n            ],\n            [\n              -117.7734375,\n              46.66451741754235\n            ],\n            [\n              -117.71850585937501,\n              49.23194729854554\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"16","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":787190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farag, Aida 0000-0003-4247-6763 aida_farag@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6763","contributorId":200690,"corporation":false,"usgs":true,"family":"Farag","given":"Aida","email":"aida_farag@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":787191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787192,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70239440,"text":"70239440 - 2020 - Introduction to this special section: Geothermal energy","interactions":[],"lastModifiedDate":"2023-01-13T12:49:12.91956","indexId":"70239440","displayToPublicDate":"2020-01-07T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3568,"text":"The Leading Edge","active":true,"publicationSubtype":{"id":10}},"title":"Introduction to this special section: Geothermal energy","docAbstract":"<div id=\"128438448\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>Geothermal energy is a global renewable resource that has the potential to provide a significant portion of baseload energy in many regions. In the United States, it has the potential to provide 8.5% of the electric generation capacity by the middle of the century. In general, geothermal systems require heat, permeability, and water to be viable for energy generation. However, with current technologies, only heat is strictly necessary in a native system. Engineered geothermal systems (EGS) introduce water into the subsurface at elevated pressures and reduced temperatures and enhance permeability through hydraulic and/or shear fracturing. Additionally, although moderate- to high-temperature resources currently dominate geothermal energy production, low-temperature resources have been utilized for direct-use cases. When well balanced and maintained, geothermal resources can produce significant amounts of heat and achieve long-term sustainability on the order of an estimated tens to hundreds of years.</p></div>","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/tle39120855.1","usgsCitation":"Kaven, J., Templeton, D., and Bathija, A.P., 2020, Introduction to this special section: Geothermal energy: The Leading Edge, v. 39, no. 12, p. 855-856, https://doi.org/10.1190/tle39120855.1.","productDescription":"2 p.","startPage":"855","endPage":"856","ipdsId":"IP-123786","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":458209,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1772306","text":"External Repository"},{"id":411838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kaven, Joern 0000-0003-2625-2786","orcid":"https://orcid.org/0000-0003-2625-2786","contributorId":217694,"corporation":false,"usgs":true,"family":"Kaven","given":"Joern","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":861578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Templeton, Dennise","contributorId":300819,"corporation":false,"usgs":false,"family":"Templeton","given":"Dennise","email":"","affiliations":[{"id":65265,"text":"Lawrence Livermore National Lab","active":true,"usgs":false}],"preferred":false,"id":861579,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bathija, Arpita P.","contributorId":300831,"corporation":false,"usgs":false,"family":"Bathija","given":"Arpita","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":861598,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70213244,"text":"70213244 - 2020 - An open source database for the synthesis of soil radiocarbon data: ISRaD version 1.0","interactions":[],"lastModifiedDate":"2020-09-16T13:28:46.247242","indexId":"70213244","displayToPublicDate":"2020-01-06T13:58:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"title":"An open source database for the synthesis of soil radiocarbon data: ISRaD version 1.0","docAbstract":"<p><span>Radiocarbon is a critical constraint on our estimates of the timescales of soil carbon cycling that can aid in identifying mechanisms of carbon stabilization and destabilization and improve the forecast of soil carbon response to management or environmental change. Despite the wealth of soil radiocarbon data that have been reported over the past 75&nbsp;years, the ability to apply these data to global-scale questions is limited by our capacity to synthesize and compare measurements generated using a variety of methods. Here, we present the International Soil Radiocarbon Database (ISRaD;&nbsp;</span><span class=\"uri\"><a rel=\"noopener\" href=\"http://soilradiocarbon.org/\" target=\"_blank\" data-mce-href=\"http://soilradiocarbon.org/\">http://soilradiocarbon.org</a></span><span>, last access: 16&nbsp;December&nbsp;2019), an open-source archive of soil data that include reported measurements from bulk soils, distinct soil carbon pools isolated in the laboratory by a variety of soil fractionation methods, samples of soil gas or water collected interstitially from within an intact soil profile,&nbsp;</span><span class=\"inline-formula\">CO<sub>2</sub></span><span>&nbsp;gas isolated from laboratory soil incubations, and fluxes collected in situ from a soil profile. The core of ISRaD is a relational database structured around individual datasets (entries) and organized hierarchically to report soil radiocarbon data, measured at different physical and temporal scales as well as other soil or environmental properties that may also be measured and may assist with interpretation and context. Anyone may contribute their own data to the database by entering it into the ISRaD template and subjecting it to quality assurance protocols. ISRaD can be accessed through (1)&nbsp;a web-based interface, (2)&nbsp;an R package (ISRaD), or (3)&nbsp;direct access to code and data through the GitHub repository, which hosts both code and data. The design of ISRaD allows for participants to become directly involved in the management, design, and application of ISRaD data. The synthesized dataset is available in two forms: the original data as reported by the authors of the datasets and an enhanced dataset that includes ancillary geospatial data calculated within the ISRaD framework. ISRaD also provides data management tools in the ISRaD-R package that provide a starting point for data analysis; as an open-source project, the broader soil community is invited and encouraged to add data, tools, and ideas for improvement. As a whole, ISRaD provides resources to aid our evaluation of soil dynamics across a range of spatial and temporal scales. The ISRaD v1.0 dataset is archived and freely available at&nbsp;</span><a href=\"https://doi.org/10.5281/zenodo.2613911\" data-mce-href=\"https://doi.org/10.5281/zenodo.2613911\">https://doi.org/10.5281/zenodo.2613911</a><span>&nbsp;(Lawrence et al., 2019).</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-12-61-2020","usgsCitation":"Lawrence, C.R., Beem-Miller, J., Hoyt, A., Monroe, G., Sierra, C., Stoner, S., Heckman, K., Blankinship, J., Crow, S., McNichol, G., Trumbore, S., Levine, P., Vinduskova, O., Todd-Brown, K., Rasmussen, C., Hicks Pries, C., Schadel, C., McFarlane, K., Doetterl, S., Hatte, C., He, Y., Treat, C.C., Harden, J.W., Torn, M.S., Estop-Aragonés, C., Berhe, A.A., Keiluweit, M., Kuhnen, A.D., Marin-Spiotta, E., Plante, A.F., Thompson, A., Shi, Z., Schimel, J.P., Vaughn, L., von Fromm, S.F., and Wagai, R., 2020, An open source database for the synthesis of soil radiocarbon data: ISRaD version 1.0: Earth System Science Data, v. 12, no. 1, p. 61-76, https://doi.org/10.5194/essd-12-61-2020.","productDescription":"16 p.","startPage":"61","endPage":"76","ipdsId":"IP-105138","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":458214,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/essd-12-61-2020","text":"Publisher Index Page"},{"id":378427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Lawrence, Corey R. 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202390,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":798776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beem-Miller, Jeffrey 0000-0003-0955-6622","orcid":"https://orcid.org/0000-0003-0955-6622","contributorId":240693,"corporation":false,"usgs":false,"family":"Beem-Miller","given":"Jeffrey","affiliations":[{"id":36389,"text":"Max Planck Institute","active":true,"usgs":false}],"preferred":false,"id":798795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoyt, Alison 0000-0003-0813-5084","orcid":"https://orcid.org/0000-0003-0813-5084","contributorId":240694,"corporation":false,"usgs":false,"family":"Hoyt","given":"Alison","email":"","affiliations":[{"id":36389,"text":"Max Planck Institute","active":true,"usgs":false}],"preferred":false,"id":798796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Monroe, Grey","contributorId":240695,"corporation":false,"usgs":false,"family":"Monroe","given":"Grey","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":798797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sierra, Carlos 0000-0003-0009-4169","orcid":"https://orcid.org/0000-0003-0009-4169","contributorId":240696,"corporation":false,"usgs":false,"family":"Sierra","given":"Carlos","email":"","affiliations":[{"id":36389,"text":"Max Planck Institute","active":true,"usgs":false}],"preferred":false,"id":798798,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stoner, Shane 0000-0002-6977-4587","orcid":"https://orcid.org/0000-0002-6977-4587","contributorId":240697,"corporation":false,"usgs":false,"family":"Stoner","given":"Shane","email":"","affiliations":[{"id":36389,"text":"Max Planck Institute","active":true,"usgs":false}],"preferred":false,"id":798799,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heckman, Katherine 0000-0003-2265-4542","orcid":"https://orcid.org/0000-0003-2265-4542","contributorId":240698,"corporation":false,"usgs":false,"family":"Heckman","given":"Katherine","email":"","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":798800,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blankinship, Joseph 0000-0001-5154-7354","orcid":"https://orcid.org/0000-0001-5154-7354","contributorId":240699,"corporation":false,"usgs":false,"family":"Blankinship","given":"Joseph","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":798801,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Crow, Susan","contributorId":240700,"corporation":false,"usgs":false,"family":"Crow","given":"Susan","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":798802,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McNichol, Gavin","contributorId":240701,"corporation":false,"usgs":false,"family":"McNichol","given":"Gavin","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":798803,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Trumbore, Susan 0000-0003-3885-6202","orcid":"https://orcid.org/0000-0003-3885-6202","contributorId":240702,"corporation":false,"usgs":false,"family":"Trumbore","given":"Susan","email":"","affiliations":[{"id":36389,"text":"Max Planck 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University","active":true,"usgs":false}],"preferred":false,"id":798806,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rasmussen, Craig","contributorId":240706,"corporation":false,"usgs":false,"family":"Rasmussen","given":"Craig","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":798807,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Hicks Pries, Caitlin","contributorId":240707,"corporation":false,"usgs":false,"family":"Hicks Pries","given":"Caitlin","affiliations":[{"id":36404,"text":"Dartmouth University","active":true,"usgs":false}],"preferred":false,"id":798809,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Schadel, Christina","contributorId":202385,"corporation":false,"usgs":false,"family":"Schadel","given":"Christina","email":"","affiliations":[{"id":36405,"text":"University of Northern Arizona","active":true,"usgs":false}],"preferred":false,"id":798813,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"McFarlane, Karis","contributorId":240711,"corporation":false,"usgs":false,"family":"McFarlane","given":"Karis","email":"","affiliations":[],"preferred":false,"id":798814,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Doetterl, Sebastian","contributorId":240712,"corporation":false,"usgs":false,"family":"Doetterl","given":"Sebastian","email":"","affiliations":[],"preferred":false,"id":798815,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Hatte, Christine","contributorId":240713,"corporation":false,"usgs":false,"family":"Hatte","given":"Christine","email":"","affiliations":[],"preferred":false,"id":798816,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"He, Yujie","contributorId":207136,"corporation":false,"usgs":false,"family":"He","given":"Yujie","email":"","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":798817,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Treat, Claire C.","contributorId":96606,"corporation":false,"usgs":true,"family":"Treat","given":"Claire","email":"","middleInitial":"C.","affiliations":[{"id":25501,"text":"University of Eastern Finland","active":true,"usgs":false}],"preferred":false,"id":798818,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":798819,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Torn, Margaret S. 0000-0002-8174-0099","orcid":"https://orcid.org/0000-0002-8174-0099","contributorId":177740,"corporation":false,"usgs":false,"family":"Torn","given":"Margaret","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":798820,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Estop-Aragonés, Cristian","contributorId":240710,"corporation":false,"usgs":false,"family":"Estop-Aragonés","given":"Cristian","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":798821,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Berhe, Asmeret A.","contributorId":214701,"corporation":false,"usgs":false,"family":"Berhe","given":"Asmeret","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":798822,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Keiluweit, Marco","contributorId":197918,"corporation":false,"usgs":false,"family":"Keiluweit","given":"Marco","email":"","affiliations":[],"preferred":false,"id":798823,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Kuhnen, Agatha Della Rosa","contributorId":240714,"corporation":false,"usgs":false,"family":"Kuhnen","given":"Agatha","email":"","middleInitial":"Della Rosa","affiliations":[],"preferred":false,"id":798824,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Marin-Spiotta, Erika","contributorId":139165,"corporation":false,"usgs":false,"family":"Marin-Spiotta","given":"Erika","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":798825,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Plante, Alain F.","contributorId":198719,"corporation":false,"usgs":false,"family":"Plante","given":"Alain","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":798826,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Thompson, Aaron","contributorId":139820,"corporation":false,"usgs":false,"family":"Thompson","given":"Aaron","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":798827,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Shi, Zheng","contributorId":200158,"corporation":false,"usgs":false,"family":"Shi","given":"Zheng","email":"","affiliations":[],"preferred":false,"id":798828,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Schimel, Joshua P.","contributorId":90102,"corporation":false,"usgs":true,"family":"Schimel","given":"Joshua","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":798829,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Vaughn, Lydia J.S. ","contributorId":174871,"corporation":false,"usgs":false,"family":"Vaughn","given":"Lydia J.S. ","affiliations":[],"preferred":false,"id":798830,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"von Fromm, Sophie F.","contributorId":240715,"corporation":false,"usgs":false,"family":"von Fromm","given":"Sophie","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":798831,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Wagai, Rota","contributorId":202389,"corporation":false,"usgs":false,"family":"Wagai","given":"Rota","email":"","affiliations":[{"id":36407,"text":"Institute for Agro-Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":798832,"contributorType":{"id":1,"text":"Authors"},"rank":36}]}}
,{"id":70208924,"text":"70208924 - 2020 - Inundation exposure assessment for Majuro Atoll, Republic of the Marshall Islands using a high-accuracy digital elevation model","interactions":[],"lastModifiedDate":"2021-06-14T19:51:01.344547","indexId":"70208924","displayToPublicDate":"2020-01-06T10:59:28","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Inundation exposure assessment for Majuro Atoll, Republic of the Marshall Islands using a high-accuracy digital elevation model","docAbstract":"<p><span>Majuro Atoll in the central Pacific has high coastal vulnerability due to low-lying islands, rising sea level, high wave events, eroding shorelines, a dense population center, and limited freshwater resources. Land elevation is the primary geophysical variable that determines exposure to inundation in coastal settings. Accordingly, coastal elevation data (with accuracy information) are critical for assessments of inundation exposure. Previous research has demonstrated the importance of using high-accuracy elevation data and rigorously accounting for uncertainty in inundation assessments. A quantitative analysis of inundation exposure was conducted for Majuro Atoll, including accounting for the cumulative vertical uncertainty from the input digital elevation model (DEM) and datum transformation. The project employed a recently produced and validated DEM derived from structure-from-motion processing of very-high-resolution aerial imagery. Areas subject to marine inundation (direct hydrologic connection to the ocean) and low-lying lands (disconnected hydrologically from the ocean) were mapped and characterized for three inundation levels using deterministic and probabilistic methods. At the highest water level modeled (3.75 ft, or 1.143 m), more than 34% of the atoll study area is likely to be exposed to inundation (68% chance or greater), while more than 20% of the atoll is extremely likely to be exposed (95% chance or greater). The study demonstrates the substantial value of a high-accuracy DEM for assessing inundation exposure of low-relief islands and the enhanced information from accounting for vertical uncertainty.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs12010154","usgsCitation":"Gesch, D.B., Palaseanu-Lovejoy, M., Danielson, J.J., Fletcher, C., Kottermair, M., Barbee, M., and Jalandoni, A., 2020, Inundation exposure assessment for Majuro Atoll, Republic of the Marshall Islands using a high-accuracy digital elevation model: Remote Sensing, v. 12, no. 1, Article: 154, 20 p.; Data Release, https://doi.org/10.3390/rs12010154.","productDescription":"Article: 154, 20 p.; Data Release","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":458218,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12010154","text":"Publisher Index Page"},{"id":372951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":373335,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5ba9511ee4b08583a5ca09fe","text":"USGS data release","description":"USGS data release","linkHelpText":"Inundation exposure assessment for Majuro Atoll, Republic of the Marshall Islands"}],"country":"Republic of the Marshall Islands","otherGeospatial":"Majuro Atoll","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              170.98777770996094,\n              6.976183516197836\n            ],\n            [\n              171.43203735351562,\n              6.976183516197836\n            ],\n            [\n              171.43203735351562,\n              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(Geography)","active":false,"usgs":true}],"preferred":true,"id":784036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":784037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":784038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fletcher, Charles","contributorId":192304,"corporation":false,"usgs":false,"family":"Fletcher","given":"Charles","affiliations":[],"preferred":false,"id":784039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kottermair, Maria","contributorId":119958,"corporation":false,"usgs":true,"family":"Kottermair","given":"Maria","email":"","affiliations":[],"preferred":false,"id":784040,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barbee, Matthew 0000-0002-8929-7255","orcid":"https://orcid.org/0000-0002-8929-7255","contributorId":196651,"corporation":false,"usgs":false,"family":"Barbee","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":784041,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jalandoni, Andrea 0000-0002-4821-7183","orcid":"https://orcid.org/0000-0002-4821-7183","contributorId":196653,"corporation":false,"usgs":false,"family":"Jalandoni","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":784042,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70224539,"text":"70224539 - 2020 - Nest site selection influences cinnamon teal nest survival in Colorado","interactions":[],"lastModifiedDate":"2021-09-27T14:46:51.635435","indexId":"70224539","displayToPublicDate":"2020-01-06T09:40:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Nest site selection influences cinnamon teal nest survival in Colorado","docAbstract":"<p><span>Nest survival of ducks is partially a function of the spatiotemporal characteristics of the site at which a bird chooses to nest. Nest survival is also a fundamental component of population growth in waterfowl but is relatively unstudied for cinnamon teal (</span><i>Spatula cyanoptera</i><span>). We investigated cinnamon teal nest survival in a managed wetland complex in southern Colorado, USA, and assessed nest site selection to determine whether nest site characteristics were adaptive. We monitored 85 nests in 2015–2017 on Monte Vista National Wildlife Refuge, Colorado and did not detect a difference in nest survival across years. Based on nest site selection data from 2017, cinnamon teal selected nest sites characterized by a lower proportion of forbs than available sites. The relationships between habitat characteristics and nest survival were variable. Microhabitat characteristics exhibited only weak effects on nest survival during the laying stage. Nest survival during incubation was negatively related to the proportion of forbs at the nest site and, to a lesser extent, the proportion of grasses. Nest site selection was predictive of future nest survival based on the percent of forbs and grasses around the nest site, suggesting teal select nest locations to benefit reproductive success. These results have the potential to guide local habitat management actions for breeding waterfowl.&nbsp;</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21818","usgsCitation":"Kendall, W.L., Setash, C.M., and Olson, D., 2020, Nest site selection influences cinnamon teal nest survival in Colorado: Journal of Wildlife Management, v. 84, no. 3, p. 542-552, https://doi.org/10.1002/jwmg.21818.","productDescription":"11 p.","startPage":"542","endPage":"552","ipdsId":"IP-105687","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":389811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Monte Vista National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.18011474609375,\n              37.45687303762862\n            ],\n            [\n              -106.01394653320312,\n              37.45687303762862\n            ],\n            [\n              -106.01394653320312,\n              37.53477698849112\n            ],\n            [\n              -106.18011474609375,\n              37.53477698849112\n            ],\n            [\n              -106.18011474609375,\n              37.45687303762862\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"84","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":823982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Setash, Casey M.","contributorId":265282,"corporation":false,"usgs":false,"family":"Setash","given":"Casey","email":"","middleInitial":"M.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":823983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olson, David","contributorId":265284,"corporation":false,"usgs":false,"family":"Olson","given":"David","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":823984,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70261995,"text":"70261995 - 2020 - Seismic character and progression of explosive activity during the 2016-2017 eruption of Bogoslof volcano, Alaska","interactions":[],"lastModifiedDate":"2025-01-08T14:52:22.557026","indexId":"70261995","displayToPublicDate":"2020-01-06T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Seismic character and progression of explosive activity during the 2016-2017 eruption of Bogoslof volcano, Alaska","docAbstract":"Bogoslof volcano, in the central Aleutian arc, experienced a major eruption between December 2016 and August 2017 that was characterized by explosive activity (VEI 2 to 3) and the extrusion of lava domes.  The Alaska Volcano Observatory tracked the activity in real-time using seismicity observed on distant stations as well as infrasound, lightning, satellite data, and occasional visual observations.  In this study we measure the duration of seismic signals associated with individual explosive events to track their progression during the two explosive phases of the eruption.  Seismic recordings of Bogoslof explosions show complex waveforms that suggest both individual explosive events as well as sequences of several explosions separated by lower amplitude tremor. The lack of local seismic monitoring (stations at distances of 1 to 15 km distance) unfortunately limit our ability to closely observe seismicity and to interpret changing conditions at the vent such as position, presence of a lava dome or plug, and the role of seawater associated with the eruption.  We use the rate of explosive activity, seismic waveform character, and repose time between explosions to infer the conditions within the conduit.","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-019-1343-4","usgsCitation":"Searcy, C., and Power, J., 2020, Seismic character and progression of explosive activity during the 2016-2017 eruption of Bogoslof volcano, Alaska: Bulletin of Volcanology, v. 82, 12, 15 p., https://doi.org/10.1007/s00445-019-1343-4.","productDescription":"12, 15 p.","ipdsId":"IP-107037","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":465874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -168.05541389523495,\n              53.94243302102879\n            ],\n            [\n              -168.05541389523495,\n              53.92208824366685\n            ],\n            [\n              -168.01832898316061,\n              53.92208824366685\n            ],\n            [\n              -168.01832898316061,\n              53.94243302102879\n            ],\n            [\n              -168.05541389523495,\n              53.94243302102879\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2020-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Searcy, Cheryl 0000-0002-9474-5745","orcid":"https://orcid.org/0000-0002-9474-5745","contributorId":243217,"corporation":false,"usgs":true,"family":"Searcy","given":"Cheryl","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":922599,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Power, John 0000-0002-7233-4398","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":215240,"corporation":false,"usgs":true,"family":"Power","given":"John","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":922600,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70211340,"text":"70211340 - 2020 - Using conceptual models to relate multiparameter satellite data to subsurface volcanic processes in Latin America","interactions":[],"lastModifiedDate":"2020-09-01T13:54:44.456524","indexId":"70211340","displayToPublicDate":"2020-01-05T10:07:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Using conceptual models to relate multiparameter satellite data to subsurface volcanic processes in Latin America","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Satellite data have been extensively used to identify volcanic behavior. However, the physical subsurface processes causing any individual manifestation of activity can be ambiguous. We propose a classification scheme for the cause of unrest that simultaneously considers three multiparameter satellite observations. The scheme is based on characteristics of the volcanic system (open, closed, and eruptive) and unrest mechanisms (intrusion, evolution, and withdrawal) occurring at shallow depths in the volcanic system. We applied these models to satellite observations acquired at 47 of the most active volcanoes in Latin America. Of the volcanoes studied, 44 had a robust enough dataset for classification and were clustered into 4 groups and 10 subgroups with common behavioral characteristics. By identifying that these volcanoes can be clustered into a number of groupings significantly less than the number of volcanoes, we have demonstrated that commonalities in behavior patterns exist among diverse volcanic systems. Identifying volcanoes with similar characteristics underpins the use of past observations at one volcano to forecast activity at another and diverges from typical volcanic groupings, which are focused on geologic parameters (i.e., composition, volcano type, and tectonic setting). Based on satellite data alone, we have identified preeruptive intrusion prior to 15 eruptions at 12 different volcanoes, magma evolution prior to 18 eruptions at 13 volcanoes, and magma withdrawal at 3 eruptions and 3 volcanoes. Improvements to the spatial and temporal resolution are needed to make these relations robust. This classification scheme provides a framework for future automated clustering of volcanoes.</p></div></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GC008494","usgsCitation":"Reath, K., Pritchard, M., Biggs, J., Andrews, B., Ebmeier, S., Bagnardi, M., Girona, T., Lundgren, P., Lopez, T., and Poland, M.P., 2020, Using conceptual models to relate multiparameter satellite data to subsurface volcanic processes in Latin America: Geochemistry, Geophysics, Geosystems, v. 21, no. 2, e2019GC008494, 26 p., https://doi.org/10.1029/2019GC008494.","productDescription":"e2019GC008494, 26 p.","ipdsId":"IP-108935","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":499870,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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Bristol","active":true,"usgs":false}],"preferred":false,"id":793916,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Andrews, Ben","contributorId":229677,"corporation":false,"usgs":false,"family":"Andrews","given":"Ben","email":"","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":793917,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ebmeier, Susi","contributorId":229678,"corporation":false,"usgs":false,"family":"Ebmeier","given":"Susi","email":"","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":793918,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bagnardi, Marco","contributorId":124560,"corporation":false,"usgs":false,"family":"Bagnardi","given":"Marco","affiliations":[{"id":5112,"text":"University of 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,{"id":70217547,"text":"70217547 - 2020 - Turbidite stratigraphy in proglacial lakes: Deciphering trigger mechanisms using a statistical approach","interactions":[],"lastModifiedDate":"2023-11-14T14:49:46.10343","indexId":"70217547","displayToPublicDate":"2020-01-04T16:01:47","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3369,"text":"Sedimentology","active":true,"publicationSubtype":{"id":10}},"title":"Turbidite stratigraphy in proglacial lakes: Deciphering trigger mechanisms using a statistical approach","docAbstract":"<p><span>Turbidites embedded in lacustrine sediment sequences are commonly used to reconstruct regional flood or earthquake histories. A critical step for this method to be successful is that turbidites and their trigger mechanisms are determined unambiguously. The latter is particularly challenging for prehistoric proglacial lake records in high-seismicity settings where both earthquake-generated and flood-generated turbidites interrupt the background varved sedimentation. This calls for a new method to allow efficient and objective identification and classification of turbidites. This study examined turbidites in five long (9 to 17&nbsp;m) sediment cores from Eklutna Lake, a proglacial lake in south-central Alaska, using standard core logging and grain-size data. A novel statistical approach is presented, in which varve-thickness distributions were first analyzed to objectively identify the thickest turbidites and distinguish them from background sedimentation. For each&nbsp;turbidite, a selection of variables were then measured, including: basal grain-size, thickness, magnetic susceptibility and spectrophotometric variables. Triggering mechanisms were discriminated by a combination of principal component analysis and clustering, and by calibration with historical events. Using this approach, a 2250&nbsp;year long lake-wide event stratigraphy was constructed, with 94 prehistoric events, including 24 earthquake and 70 flood events. Basal grain-size and thickness variables turn out to be the most effective proxies for discrimination. This statistical approach is a powerful and new method to identify turbidites and their triggering mechanisms in long prehistoric sediment records. It opens up new prospects for palaeoseismological, palaeohydrological and palaeoclimate studies in proglacial lakes worldwide.</span></p>","language":"English","publisher":"International Association of Sedimentologists","doi":"10.1111/sed.12703","usgsCitation":"Praet, N., Van Daele, M., Collart, T., Moernaut, J., Vandekerkhove, E., Kempf, P., Haeussler, P., and De Batist, M., 2020, Turbidite stratigraphy in proglacial lakes: Deciphering trigger mechanisms using a statistical approach: Sedimentology, v. 67, no. 5, p. 2332-2359, https://doi.org/10.1111/sed.12703.","productDescription":"28 p.","startPage":"2332","endPage":"2359","ipdsId":"IP-112553","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":382465,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Eklutna Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -149.2,\n              61.1667\n            ],\n            [\n              -148.85,\n              61.1667\n            ],\n            [\n              -148.85,\n              61.45\n            ],\n            [\n              -149.2,\n              61.45\n            ],\n            [\n              -149.2,\n              61.1667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"67","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Praet, Nore","contributorId":194083,"corporation":false,"usgs":false,"family":"Praet","given":"Nore","email":"","affiliations":[],"preferred":false,"id":808647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Daele, Maarten 0000-0002-8530-4438","orcid":"https://orcid.org/0000-0002-8530-4438","contributorId":194085,"corporation":false,"usgs":false,"family":"Van Daele","given":"Maarten","email":"","affiliations":[{"id":27279,"text":"Department of Geology and Soil Science, Ghent University, Ghent, Belgium","active":true,"usgs":false}],"preferred":false,"id":808687,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collart, Tim","contributorId":248240,"corporation":false,"usgs":false,"family":"Collart","given":"Tim","email":"","affiliations":[{"id":27567,"text":"Ghent University","active":true,"usgs":false}],"preferred":false,"id":808648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moernaut, J.","contributorId":238170,"corporation":false,"usgs":false,"family":"Moernaut","given":"J.","affiliations":[{"id":47707,"text":"Institute of Geology, University of Innsbruck, Austria","active":true,"usgs":false}],"preferred":false,"id":808649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vandekerkhove, Elke 0000-0002-6184-2709","orcid":"https://orcid.org/0000-0002-6184-2709","contributorId":248243,"corporation":false,"usgs":false,"family":"Vandekerkhove","given":"Elke","email":"","affiliations":[{"id":27567,"text":"Ghent University","active":true,"usgs":false}],"preferred":false,"id":808650,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kempf, P.","contributorId":248246,"corporation":false,"usgs":false,"family":"Kempf","given":"P.","email":"","affiliations":[{"id":27567,"text":"Ghent University","active":true,"usgs":false}],"preferred":false,"id":808651,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":808652,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"De Batist, M.","contributorId":248249,"corporation":false,"usgs":false,"family":"De Batist","given":"M.","affiliations":[{"id":27567,"text":"Ghent University","active":true,"usgs":false}],"preferred":false,"id":808653,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70211922,"text":"70211922 - 2020 - Estimating bedload from suspended load and water discharge in sand bed rivers","interactions":[],"lastModifiedDate":"2020-08-11T20:13:57.981854","indexId":"70211922","displayToPublicDate":"2020-01-03T15:10:09","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Estimating bedload from suspended load and water discharge in sand bed rivers","docAbstract":"<p><span>Estimates of fluvial sediment discharge from in situ instruments are an important component of large‐scale sediment budgets that track long‐term geomorphic change. Suspended sediment load can be reliably estimated using acoustic or physical sampling techniques; however, bedload is difficult to measure directly and can consequently be one of the largest sources of uncertainty in estimates of total load. We propose a physically informed predictive empirical model for bedload sand flux as a function of variables that are measured using existing acoustic or physical sampling techniques. This model depends on the assumption that concentration and grain size in suspension are in equilibrium with reach‐averaged boundary conditions. Bayesian inference is used to fit model parameters to data from eight sand‐bed rivers and to simulate bedload flux over the available gage record at one site on the Colorado River in Grand Canyon National Park. We find that the cumulative bedload flux during the 9&nbsp;year period from 2008 to 2016 was 5% of the cumulative suspended sand load; however, instantaneous bedload flux ranged from as little as 1% of instantaneous suspended sand load to as much as 75% of instantaneous suspended sand load due to fluctuations in flow strength and sediment supply. Changes in bedload flux at a constant discharge are indicative of short‐term sediment supply enrichment and depletion. Long‐term average bedload flux cannot be expected to remain constant in the future as the river adjusts to changes in sediment runoff and the dam‐regulated discharge regime.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR025883","usgsCitation":"Ashley, T., McElroy, B., Buscombe, D., Grams, P.E., and Kaplinski, M., 2020, Estimating bedload from suspended load and water discharge in sand bed rivers: Water Resources Research, v. 56, no. 2, e2019WR025883, 25 p., https://doi.org/10.1029/2019WR025883.","productDescription":"e2019WR025883, 25 p.","ipdsId":"IP-108262","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":458242,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/essoar.10503756.1","text":"External Repository"},{"id":377386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.005126953125,\n              35.71083783530009\n            ],\n            [\n              -111.37390136718749,\n              35.71083783530009\n            ],\n            [\n              -111.37390136718749,\n              36.92793899776678\n            ],\n            [\n              -114.005126953125,\n              36.92793899776678\n            ],\n            [\n              -114.005126953125,\n              35.71083783530009\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"56","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Ashley, T.C.","contributorId":238017,"corporation":false,"usgs":false,"family":"Ashley","given":"T.C.","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":795824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McElroy, B.","contributorId":23797,"corporation":false,"usgs":true,"family":"McElroy","given":"B.","email":"","affiliations":[],"preferred":false,"id":795825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buscombe, D.","contributorId":44020,"corporation":false,"usgs":true,"family":"Buscombe","given":"D.","email":"","affiliations":[],"preferred":false,"id":795826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":216115,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":795827,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaplinski, M.","contributorId":31576,"corporation":false,"usgs":true,"family":"Kaplinski","given":"M.","email":"","affiliations":[],"preferred":false,"id":795828,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70207677,"text":"fs20193067 - 2020 - U.S. Geological Survey Earthquake Science Center","interactions":[],"lastModifiedDate":"2022-10-31T14:12:08.267675","indexId":"fs20193067","displayToPublicDate":"2020-01-03T11:51:24","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-3067","displayTitle":"U.S. Geological Survey Earthquake Science Center","title":"U.S. Geological Survey Earthquake Science Center","docAbstract":"<p>The mission of the U.S. Geological Survey (USGS) Earthquake Science Center is to collect a wide range of data on earthquakes, faults, and crustal deformation; conduct research to increase our understanding of earthquake source processes, occurrence, and effects; and synthesize this knowledge into probabilistic seismic hazard assessments, aftershock forecasts, and ground-shaking scenarios for anticipated major earthquakes. We disseminate these data products, hazard assessments, and research discoveries to scientists, engineers, emergency managers, and the public.</p><p>With university and State partners, we operate the California Integrated Seismic Network and the Pacific Northwest Seismic Network, as well as geodetic networks throughout the western United States. We also lead the National Strong Motion Project and the ShakeAlert earthquake early warning (EEW) system; house renowned rock mechanics laboratories and deep borehole geophysics facilities; and conduct extensive geophysical, geologic, and paleoseismic investigations along active faults. We are funded primarily by the USGS Earthquake Hazards Program, with additional support from the USGS Volcano Hazards and Energy Resources Programs, other Federal and State agencies, private foundations, and public and private utilities and corporations.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193067","usgsCitation":"This publication is available at https://pubs.er.usgs.gov/publication/fs20193067. 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Science Center","active":true,"usgs":true}],"preferred":true,"id":778853,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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