In the last 10 yr, the International Atomic Energy Agency (IAEA) revised its safety standards for site evaluations of nuclear installations in response to emerging fault displacement hazard evaluation practices developed in Member States. New amendments in the revised safety guidance (DS507) explicitly recommend fault displacement hazard assessment, including separate approaches for candidate new sites versus existing sites. If there is insufficient basis to conclusively determine that a fault is not capable of surface displacement at an existing site, then a probabilistic fault displacement hazard analysis (PFDHA) is recommended to better characterize the hazard. This new recommendation has generated the need for the IAEA to provide its Member States with guidance on performing PFDHA, including its formulation and implementation. This article provides an overview of current PFDHA state‐of‐practice for nuclear installations that is consistent with the new IAEA safety standards. We also summarize progress in an ongoing international PFDHA benchmark project that will ultimately provide technical guidance to Member States for conducting site‐specific fault displacement hazard assessments.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120210083","usgsCitation":"Valentini, A., Fukushima, Y., Contri, P., Ono, M., Sakai, T., Thompson, S., Viallet, E., Annaka, T., Chen, R., Moss, R.E., Petersen, M.D., Visini, F., and Youngs, R., 2021, Probabilistic fault displacement hazard assessment (PFDHA) for nuclear installations according to IAEA safety standards: Bulletin of the Seismological Society of America, v. 111, no. 5, p. 2661-2672, https://doi.org/10.1785/0120210083.","productDescription":"12 p.","startPage":"2661","endPage":"2672","ipdsId":"IP-130132","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":391084,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"111","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-08-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Valentini, Alessandro","contributorId":221390,"corporation":false,"usgs":false,"family":"Valentini","given":"Alessandro","email":"","affiliations":[{"id":40356,"text":"Università degli Studi “G. d’Annunzio” di Chieti-Pescara, InGeo Department","active":true,"usgs":false}],"preferred":false,"id":825940,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fukushima, Yoshimitsu","contributorId":268149,"corporation":false,"usgs":false,"family":"Fukushima","given":"Yoshimitsu","email":"","affiliations":[{"id":55576,"text":"International Atomic Energy Agency, IAEA, Vienna, Austria","active":true,"usgs":false}],"preferred":false,"id":825941,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Contri, Paolo","contributorId":268150,"corporation":false,"usgs":false,"family":"Contri","given":"Paolo","email":"","affiliations":[{"id":55576,"text":"International Atomic Energy Agency, IAEA, Vienna, Austria","active":true,"usgs":false}],"preferred":false,"id":825942,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ono, Masato","contributorId":268151,"corporation":false,"usgs":false,"family":"Ono","given":"Masato","email":"","affiliations":[{"id":55576,"text":"International Atomic Energy Agency, IAEA, Vienna, Austria","active":true,"usgs":false}],"preferred":false,"id":825943,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sakai, Toshiaki","contributorId":268152,"corporation":false,"usgs":false,"family":"Sakai","given":"Toshiaki","email":"","affiliations":[{"id":55577,"text":"Central Research Institute of Electric Power Industry, Abiko, Japan","active":true,"usgs":false}],"preferred":false,"id":825944,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thompson, Stephen","contributorId":202211,"corporation":false,"usgs":false,"family":"Thompson","given":"Stephen","email":"","affiliations":[],"preferred":false,"id":825945,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Viallet, Emmanuel","contributorId":268153,"corporation":false,"usgs":false,"family":"Viallet","given":"Emmanuel","email":"","affiliations":[{"id":55578,"text":"Électricité de France, Paris, France","active":true,"usgs":false}],"preferred":false,"id":825946,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Annaka, Tadashi","contributorId":268154,"corporation":false,"usgs":false,"family":"Annaka","given":"Tadashi","email":"","affiliations":[{"id":55579,"text":"Tokyo Electric Power Services Company, Ltd., Tokyo, Japan","active":true,"usgs":false}],"preferred":false,"id":825947,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Chen, Rui","contributorId":187504,"corporation":false,"usgs":false,"family":"Chen","given":"Rui","email":"","affiliations":[],"preferred":false,"id":825948,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Moss, Robb E. S.","contributorId":211466,"corporation":false,"usgs":false,"family":"Moss","given":"Robb","email":"","middleInitial":"E. S.","affiliations":[{"id":38253,"text":"California Polytechnic State Univ","active":true,"usgs":false}],"preferred":false,"id":825949,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825950,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Visini, Francesco","contributorId":221392,"corporation":false,"usgs":false,"family":"Visini","given":"Francesco","email":"","affiliations":[{"id":40358,"text":"Istituto Nazionale di Geofisica e Vulcanologia, sezione di Pisa","active":true,"usgs":false}],"preferred":false,"id":825951,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Youngs, Robert","contributorId":140544,"corporation":false,"usgs":false,"family":"Youngs","given":"Robert","affiliations":[],"preferred":false,"id":825952,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70225643,"text":"70225643 - 2021 - Acoustic interaction between a pair of owls and a wolf","interactions":[],"lastModifiedDate":"2021-10-29T13:45:59.520529","indexId":"70225643","displayToPublicDate":"2021-08-31T08:34:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Acoustic interaction between a pair of owls and a wolf","docAbstract":"During summer 2019, we recorded an apparent vocal interaction, lasting just under 4 min, between a pair of Great Horned Owls (Bubo virginianus) and a gray wolf (Canis lupus) in Yellowstone National Park. To our knowledge, this is the first report of such an acoustic interaction in the scientific literature. The increased use of passive acoustic recorders, which record spontaneous vocalizations emitted by animals over long periods, will allow us to better document and study the importance of such interspecific interactions.
","language":"English","publisher":"Monte L. Bean Life Science Museum, Brigham Young University","usgsCitation":"Marti-Domken, B., Palacios, V., and Barber-Meyer, S., 2021, Acoustic interaction between a pair of owls and a wolf: Western North American Naturalist, v. 81, no. 3, p. 457-461.","productDescription":"5 p.","startPage":"457","endPage":"461","ipdsId":"IP-126183","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":391148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391142,"type":{"id":15,"text":"Index Page"},"url":"https://scholarsarchive.byu.edu/wnan/vol81/iss3/15/"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.005859375,\n 43.866218006556394\n ],\n [\n -109.44580078125,\n 43.866218006556394\n ],\n [\n -109.44580078125,\n 44.98811302615805\n ],\n [\n -111.005859375,\n 44.98811302615805\n ],\n [\n -111.005859375,\n 43.866218006556394\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marti-Domken, Barbara","contributorId":268183,"corporation":false,"usgs":false,"family":"Marti-Domken","given":"Barbara","email":"","affiliations":[{"id":56116,"text":"ARCA / ACNHE Spain","active":true,"usgs":false}],"preferred":false,"id":826038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palacios, Vicente","contributorId":73043,"corporation":false,"usgs":true,"family":"Palacios","given":"Vicente","email":"","affiliations":[],"preferred":false,"id":826039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barber-Meyer, Shannon 0000-0002-3048-2616","orcid":"https://orcid.org/0000-0002-3048-2616","contributorId":217941,"corporation":false,"usgs":true,"family":"Barber-Meyer","given":"Shannon","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":826040,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224304,"text":"70224304 - 2021 - Phytoplankton and cyanobacteria abundances in mid-21st century lakes depend strongly on future land use and climate projections","interactions":[],"lastModifiedDate":"2021-11-16T15:44:27.13098","indexId":"70224304","displayToPublicDate":"2021-08-31T07:54:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Phytoplankton and cyanobacteria abundances in mid-21st century lakes depend strongly on future land use and climate projections","docAbstract":"Land use and climate change are anticipated to affect phytoplankton of lakes worldwide. The effects will depend on the magnitude of projected land use and climate changes and lake sensitivity to these factors. We used random forests fit with long-term (1971–2016) phytoplankton and cyanobacteria abundance time series, climate observations (1971–2016), and upstream catchment land use (global Clumondo models for the year 2000) data from 14 European and 15 North American lakes basins. We projected future phytoplankton and cyanobacteria abundance in the 29 focal lake basins and 1567 lakes across focal regions based on three land use (sustainability, middle of the road, and regional rivalry) and two climate (RCP 2.6 and 8.5) scenarios to mid-21st century. On average, lakes are expected to have higher phytoplankton and cyanobacteria due to increases in both urban land use and temperature, and decreases in forest habitat. However, the relative importance of land use and climate effects varied substantially among regions and lakes. Accounting for land use and climate changes in a combined way based on extensive data allowed us to identify urbanization as the major driver of phytoplankton development in lakes located in urban areas, and climate as major driver in lakes located in remote areas where past and future land use changes were minimal. For approximately one-third of the studied lakes, both drivers were relatively important. The results of this large scale study suggest the best approaches for mitigating the effects of human activity on lake phytoplankton and cyanobacteria will depend strongly on lake sensitivity to long-term change and the magnitude of projected land use and climate changes at a given location. Our quantitative analyses suggest local management measures should focus on retaining nutrients in urban landscapes to prevent nutrient pollution from exacerbating ongoing changes to lake ecosystems from climate change.
Non-native organisms have invaded novel ecosystems for centuries, yet we have only a limited understanding of why their impacts vary widely from minor to severe. Predicting the impact of non-established or newly detected species could help focus biosecurity measures on species with the highest potential to cause widespread damage. However, predictive models require an understanding of potential drivers of impact and the appropriate level at which these drivers should be evaluated. Here, we used non-native, specialist herbivorous insects of forest ecosystems to test which factors drive impact and if there were differences based on whether they used woody angiosperms or conifers as hosts. We identified convergent and divergent patterns between the two host types indicating fundamental similarities and differences in their interactions with non-native insects. Evolutionary divergence time between native and novel hosts was a significant driver of insect impact for both host types but was modulated by different factors in the two systems. Beetles in the subfamily Scolytinae posed the highest risk to woody angiosperms, and different host traits influenced impact of specialists on conifers and woody angiosperms. Tree wood density was a significant predictor of host impact for woody angiosperms with intermediate densities (0.5–0.6 mg/mm3) associated with highest risk, whereas risk of impact was highest for conifers that coupled shade tolerance with drought intolerance. These results underscore the importance of identifying the relevant levels of biological organization and ecological interactions needed to develop accurate risk models for species that may arrive in novel ecosystems.
This study was undertaken by the U.S. Geological Survey to assess the detectability of landslides in the densely forested and mountainous island of Pohnpei in the Federated States of Micronesia. The study used existing field-observed land-cover changes and landslides visible on Google Earth (GE) images. A limited number of ALOS-2 PALSAR-2 L-band synthetic aperture radar (SAR) images were collected on two adjacent orbit paths before and after an intense rainfall event that affected Pohnpei in mid-March 2018. Similar sets of images were collected in 2019 and 2020. Low coherence throughout the island interior eliminated use of phase-change products, and change analysis identified no landslide features as having formed in 2019 or 2020. The assessment of red-green-blue image composites and application of the log-ratio method to the 2018 ground-range SAR images identified 5 of the 11 landslides observed on the GE images. Visual comparisons of the co-event and post-event coherence image products detected 9 of the 11 landslides observed on the GE images. Combined, the ground-based SAR and interferometric SAR coherence change detections overcame high temporal and spatial decorrelations, identified all but one landslide visible in the GE comparison, and included substantial redundancy. The robustness of the landslide detection indicates that an increased collection frequency of L-band images could support systematic monitoring of land-cover change on Pohnpei at the scale reported in this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211084","usgsCitation":"Ramsey, E.W., III, and Rangoonwala, A., 2021, Using ALOS-2 synthetic aperture radar (SAR) and interferometric SAR to detect landslides on the mountainous island of Pohnpei, Federated States of Micronesia: U.S. Geological Survey Open-File Report 2021–1084, 28 p., https://doi.org/10.3133/ofr20211084.","productDescription":"vii, 28 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-131020","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":388659,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1084/coverthb.jpg"},{"id":388660,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1084/ofr20211084.pdf","text":"Report","size":"5.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1084"},{"id":388661,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1084/images"}],"country":"Federated States of Micronesia","otherGeospatial":"Island of Pohnpei","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 158.06442260742188,\n 6.770988820924266\n ],\n [\n 158.38577270507812,\n 6.770988820924266\n ],\n [\n 158.38577270507812,\n 7.027297875479451\n ],\n [\n 158.06442260742188,\n 7.027297875479451\n ],\n [\n 158.06442260742188,\n 6.770988820924266\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152
A two-year study (2013 and 2017) was conducted to determine if annual releases of hatchery rainbow trout (resident Oncorhynchus mykiss) in the upper Cowlitz River Basin, Washington adversely affected anadromous fish in the basin. Rainbow trout tagged with radio transmitters were monitored after release to describe movement patterns, entrainment rates at Cowlitz Falls Dam, and survival. Additionally, trout that were radio-tagged in 2017 were monitored during spring 2018 to determine if any moved upstream and entered tributaries where winter steelhead (anadromous Oncorhynchus mykiss) spawning occurs. A total of 580 hatchery rainbow trout (122 in 2013 and 458 in 2017) were radio-tagged and released at three release sites: (1) Cowlitz Falls Campground on Cowlitz River Arm of Lake Scanewa river kilometer (rkm) 155, (2) Cispus River Arm of Lake Scanewa rkm 1, and (3) Day Use Park on Cowlitz River Arm of Lake Scanewa rkm 146. Most radio-tagged trout (70 percent) remained within 6.4 rkm of the release site but some fish moved at least 25.7 rkm from the release site. The predominant movement direction was downstream. More than twice as many fish released at Cowlitz Falls Campground in 2017 (compared to the other two release sites) remained in the Cowlitz River, where potential overlap with steelhead occurs. A total of 28.3 percent of the study fish were entrained at Cowlitz Falls Dam. Apparent survival (time until movement ceased) for most tagged trout was fewer than 100 days from release in both years and no fish were detected moving during the spring following their release. In summary, hatchery rainbow trout released upstream from Cowlitz Falls Dam seem to remain primarily in Lake Scanewa or entrained at Cowlitz Falls Dam with few fish surviving to winter months. We found no evidence of hatchery trout interacting with steelhead in spawning tributaries during spring months. These results suggest that trout stocking in the upper Cowlitz River Basin poses minimal threat to anadromous fish in the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211085","collaboration":"Prepared in cooperation with the Bonneville Power Administration and Public Utility District Number 1 of Lewis County, Washington","usgsCitation":"Hansen, A.C., Kock, T.J., Ekstrom, B.K., and Liedtke, T.L., 2021, Behavior and survival of hatchery rainbow trout (Oncorhynchus mykiss) in the upper Cowlitz River Basin, Washington, 2013 and 2017 (ver. 1.1, September 2021): U.S. Geological Survey Open-File Report 2021–1085, 14 p., https://doi.org/10.3133/ofr20211085.","onlineOnly":"Y","ipdsId":"IP-127058","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":397377,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1085/ofr20211085.XML"},{"id":397376,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1085/images"},{"id":388965,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1085/versionhist.txt"},{"id":403443,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211085/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2021-1085"},{"id":388676,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1085/ofr20211085.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1085"},{"id":388675,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1085/coverthb2.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Upper Cowlitz River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.13476562499997,\n 46.057985244793024\n ],\n [\n -121.66259765624999,\n 46.057985244793024\n ],\n [\n -121.66259765624999,\n 46.73986059969267\n ],\n [\n -123.13476562499997,\n 46.73986059969267\n ],\n [\n -123.13476562499997,\n 46.057985244793024\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
The Black River flows through southeast Missouri and northeast Arkansas to its confluence with the White River in Arkansas. The U.S. Army Corps of Engineers operates Clearwater Dam on the Black River and a series of dams in the White River Basin primarily for flood control. In this study, the hydrology and geomorphology of the Black River are examined through an analysis of annual mean and peak discharges at streamgages, a specific stage analysis of stage and discharge at streamgages, and an examination of bathymetric data and aerial imagery. Five streamgages on the Black River were analyzed, in addition to four streamgages on Black River tributaries and one streamgage on the White River, located just downstream from the Black River confluence. The analyses indicated that regulation of discharges at the flood-control dams caused a decrease in the magnitude and variability of the peak discharges at several of the analyzed gages on the Black and White Rivers. Conversely, peak discharges on the Black River have been increasing since water year 2000, though this is not matched by an increase in peak discharges on the White River for the same time period. The specific stage analyses and the available morphologic data generally did not indicate pronounced changes in stage-discharge relations at streamgages on the Black River, with the exception of the gages nearest to Clearwater Dam.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215067","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"LeRoy, J.Z., Huizinga, R.J., Heimann, D.C., Lindroth, E.M., and Doyle, H.F., 2021, Historical hydrologic and geomorphic conditions on the Black River and selected tributaries, Arkansas and Missouri: U.S. Geological Survey Scientific Investigations Report 2021–5067, 72 p., https://doi.org/10.3133/sir20215067.","productDescription":"Report: ix, 72 p.; Appendix; Dataset","numberOfPages":"86","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-114034","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":388646,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5067/images","description":"SIR 2021–5067 Images"},{"id":388645,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5067/sir20215067.xml","text":"Report","size":"298 kB","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2021–5067"},{"id":388644,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":388641,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5067/coverthb.jpg"},{"id":388642,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5067/sir20215067.pdf","text":"Report","size":"7.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5067"},{"id":388643,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5067/downloads","text":"Appendix Tables 1.0 through 1.10 (.csv and .xlsx formats)"}],"country":"United States","state":"Arkansas, Missouri","otherGeospatial":"Black River and selected tributaries","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.51611328125,\n 35.585851593232384\n ],\n [\n -89.95605468749999,\n 35.585851593232384\n ],\n [\n -89.95605468749999,\n 37.317751851636906\n ],\n [\n -91.51611328125,\n 37.317751851636906\n ],\n [\n -91.51611328125,\n 35.585851593232384\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Hydrologic processes are often important determinants of successful recruitment of native fishes. However, water management practices can result in abnormal changes in daily and seasonal hydrology patterns. Rarely has fish recruitment across river–reservoir landscapes been considered in relation to flow management, despite the direct relationship between reservoir water management and the resulting upstream and downstream hydrology. We evaluated the relationships between lotic and lentic hydrology and recruitment of two native broadcast-spawning fishes, Freshwater Drum Aplodinotus grunniens and Gizzard Shad Dorosoma cepedianum. Four seasonal periods for each species were identified that related to the species’ spawning biology, from which we derived our remaining hydrology variables. Annual hydrology variables were also considered in our analysis. We developed regression models in conjunction with a model-selection procedure for each species and habitat type based on the catch-curve residuals from fish populations in hydrologically connected river–reservoir systems in the Ozark Highland and Ouachita Mountain ecoregions, USA. Our results indicated that recruitment of reservoir Freshwater Drum was negatively correlated to annual reservoir retention time. In lotic habitats, Freshwater Drum recruitment was positively correlated with prespawn discharge conditions and negatively correlated with annual flow variability. Similarly, riverine Gizzard Shad recruitment was positively correlated to the frequency of high-flow pulses during the spawning period. Our results indicate that releasing reservoir water to best mimic relatively natural flow patterns may benefit some broadcast-spawning species that occupy both lentic and downstream lotic environments, especially during the spring. This information, combined with future efforts on additional spawning guilds, will provide a foundation for developing holistic river–reservoir water-allocation plans.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10692","usgsCitation":"Dattilo, J., Brewer, S.K., and Shoup, D., 2021, Flow dynamics influence fish recruitment in hydrologically connected river-reservoir landscapes: North American Journal of Fisheries Management, v. 41, no. 6, p. 1752-1763, https://doi.org/10.1002/nafm.10692.","productDescription":"12 p.","startPage":"1752","endPage":"1763","ipdsId":"IP-096322","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395372,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri, Oklahoma","otherGeospatial":"Elk River, Grand Lake O’ the Cherokee, Kiamichi River, Sardis Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.372314453125,\n 36.43012234551576\n ],\n [\n -93.80126953124999,\n 36.43012234551576\n ],\n [\n -93.80126953124999,\n 37.142803443716836\n ],\n [\n -95.372314453125,\n 37.142803443716836\n ],\n [\n -95.372314453125,\n 36.43012234551576\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.95458984375,\n 33.779147331286474\n ],\n [\n -94.493408203125,\n 33.779147331286474\n ],\n [\n -94.493408203125,\n 34.488447837809304\n ],\n [\n -95.95458984375,\n 34.488447837809304\n ],\n [\n -95.95458984375,\n 33.779147331286474\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-08-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Dattilo, J.","contributorId":274267,"corporation":false,"usgs":false,"family":"Dattilo","given":"J.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":832863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832865,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shoup, D. E.","contributorId":242905,"corporation":false,"usgs":false,"family":"Shoup","given":"D. E.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":832864,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223282,"text":"sir20215064 - 2021 - Geohydrology and water quality of the stratified-drift aquifers in West Branch Cayuga Inlet and Fish Kill Valleys, Newfield, Tompkins County, New York","interactions":[],"lastModifiedDate":"2021-08-30T15:07:53.555341","indexId":"sir20215064","displayToPublicDate":"2021-08-30T10:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5064","displayTitle":"Geohydrology and Water Quality of the Stratified-Drift Aquifers in West Branch Cayuga Inlet and Fish Kill Valleys, Newfield, Tompkins County, New York","title":"Geohydrology and water quality of the stratified-drift aquifers in West Branch Cayuga Inlet and Fish Kill Valleys, Newfield, Tompkins County, New York","docAbstract":"From 2011 to 2016, the U.S. Geological Survey, in cooperation with the Town of Newfield and the Tompkins County Planning Department, performed a study of the stratified-drift aquifers in the West Branch Cayuga Inlet and Fish Kill Valleys in Newfield, Tompkins County, New York. Both confined and unconfined aquifers were identified, mostly in the valleys. The confined aquifer consists of a discontinuous sand and gravel layer that overlies bedrock and is commonly confined by overlying fine-grained sediments. The unconfined aquifer consists of surficial ice contact sand and gravel, alluvial silt, sand and gravel, and areas where several large tributary streams deposited alluvial fans in the valley, all of which were deposited during and after the last glacial recession.
The unconfined aquifers are primarily recharged by direct infiltration of precipitation at the land surface, by surface runoff and shallow subsurface flow from adjacent hillsides, and by seepage loss from streams crossing the aquifer, especially on alluvial fans. The confined aquifers are primarily recharged by groundwater stored in the overlying sand and gravel aquifer that slowly seeps downward through the underlying confining layer. Other sources of recharge are precipitation that falls directly on the surficial confining unit and adjacent valley walls, which then slowly seeps downward and enters the confined aquifer, and groundwater flow from bordering till and bedrock and from bedrock below the valley. There may also be some recharge where confining units are absent or where parts of the confining units contain sediments with moderate permeability.
The groundwater naturally discharges to the Fish Kill and West Branch Cayuga Inlet streams and to wetlands overlying the aquifer boundaries, with additional losses due to evapotranspiration. Groundwater is pumped from the aquifers by domestic, municipal, and agricultural wells. Approximately 57.9 million gallons per year was withdrawn from the stratified-drift (sand and gravel) aquifers.
Groundwater samples were collected from 11 wells, and surface water samples were collected at 2 sites, one each from Fish Kill and West Branch Cayuga Inlet. None of the common ions (for example, sodium, chloride, and magnesium) exceeded existing drinking water standards at either surface water site. The concentration of nitrate plus nitrite detected was 0.4 milligram per liter as nitrogen in the West Branch Cayuga Inlet site. Total phosphorus was detected at 0.01 milligram per liter as phosphate for both sites. Of the 11 wells sampled, 8 were finished in confined sand and gravel aquifers, 1 was finished in unconfined sand and gravel, and 2 were finished in shale bedrock. Groundwater quality in the study area generally met Federal and State drinking-water standards. However, of the 11 samples taken, 2 exceeded the U.S. Environmental Protection Agency drinking water advisory taste threshold of 20 milligrams per liter for sodium, 8 exceeded the secondary maximum contaminant level of 300 micrograms per liter for iron, and 9 exceeded the secondary maximum contaminant level of 50 micrograms per liter for manganese.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215064","collaboration":"Prepared in cooperation with the Town of Newfield and the Tompkins County Planning Department","usgsCitation":"Fisher, B.N., Heisig, P.M., and Kappel, W.M., 2021, Geohydrology and water quality of the stratified-drift aquifers in West Branch Cayuga Inlet and Fish Kill Valleys, Newfield, Tompkins County, New York: U.S. Geological Survey Scientific Investigations Report 2021–5064, 42 p., https://doi.org/10.3133/sir20215064.","productDescription":"Report: vii, 42 p.; 2 Tables; 2 Data Releases","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-103464","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":388165,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5064/coverthb.jpg"},{"id":388166,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5064/sir20215064.pdf","text":"Report","size":"5.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5064"},{"id":388167,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94Y3E81","text":"USGS data release","linkHelpText":"Geospatial datasets for the geohydrology and water quality of the stratified-drift aquifers in West Branch Cayuga Inlet/Fish Kill aquifers in Newfield, Tompkins County, New York"},{"id":388169,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2021/5064/sir20215064_table03.01.csv","text":"Table 3.1","size":"4.74 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Physical properties and concentrations of common ions, nutrients, radiochemical properties, and dissolved gases in groundwater samples from confined aquifers in the West Branch Cayuga Inlet and Fish Kill Creek Valleys, Newfield, Tompkins County, New York"},{"id":388217,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5064/images/"},{"id":388218,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5064/sir20215064.XML"},{"id":388170,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2021/5064/sir20215064_table03.02.csv","text":"Table 3.2","size":"2.98 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Concentrations of trace elements in groundwater samples from confined aquifers in the West Branch Cayuga Inlet and Fish Kill Creek Valleys, Newfield, Tompkins County, New York"},{"id":388168,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N6AZ4E","text":"USGS data release","linkHelpText":"Horizontal-to-vertical spectral ratio and depth-to-bedrock for geohydrology and water quality of the stratified-drift aquifer in West Branch Cayuga Inlet and Fish Kill Valleys, Newfield, Tompkins County, New York, July 2011–November 2016"}],"country":"United States","state":"New York","otherGeospatial":"West Branch Cayuga Inlet and Fish Kill Valleys","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.83333333,\n 42.1666\n ],\n [\n -76.83333333,\n 42.8333\n ],\n [\n -76.00,\n 42.83333333\n ],\n [\n -76.00,\n 42.1666\n ],\n [\n -76.83333333,\n 42.1666\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Improving our understanding of hazards posed by future large earthquakes on the Cascadia Subduction Zone requires advancements in the methods and sampling used to date and characterize past events.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EO162183","usgsCitation":"Pearl, J.K., and Staisch, L.M., 2021, Swipe left on the “big one”: Better dates for Cascadia quakes: Eos Science News, no. 102, HTML Document, https://doi.org/10.1029/2021EO162183.","productDescription":"HTML Document","ipdsId":"IP-128367","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":451033,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021eo162183","text":"Publisher Index Page"},{"id":394578,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -136.58203125,\n 38.65119833229951\n ],\n [\n -119.83886718750001,\n 38.65119833229951\n ],\n [\n -119.83886718750001,\n 55.87531083569679\n ],\n [\n -136.58203125,\n 55.87531083569679\n ],\n [\n -136.58203125,\n 38.65119833229951\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"102","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pearl, Jessie K. 0000-0002-1556-2159","orcid":"https://orcid.org/0000-0002-1556-2159","contributorId":242893,"corporation":false,"usgs":true,"family":"Pearl","given":"Jessie","email":"","middleInitial":"K.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":831188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Staisch, Lydia M. 0000-0002-1414-5994 lstaisch@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-5994","contributorId":167068,"corporation":false,"usgs":true,"family":"Staisch","given":"Lydia","email":"lstaisch@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":831189,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227494,"text":"70227494 - 2021 - Book review of \"A most remarkable creature: The hidden life and epic journey of the world’s smartest birds of prey\"","interactions":[],"lastModifiedDate":"2022-01-20T14:31:48.234308","indexId":"70227494","displayToPublicDate":"2021-08-30T08:31:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Book review of \"A most remarkable creature: The hidden life and epic journey of the world’s smartest birds of prey\"","docAbstract":"No abstract available.
","language":"English","publisher":"Wiley","doi":"10.1111/jofo.12377","usgsCitation":"Andersen, D.E., 2021, Book review of \"A most remarkable creature: The hidden life and epic journey of the world’s smartest birds of prey\": Journal of Field Ornithology, v. 92, no. 3, p. 305-306, https://doi.org/10.1111/jofo.12377.","productDescription":"2 p.","startPage":"305","endPage":"306","ipdsId":"IP-130276","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":394576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"92","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-08-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":831180,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70223824,"text":"70223824 - 2021 - Early Pleistocene climate-induced erosion of the Alaska Range formed the Nenana Gravel","interactions":[],"lastModifiedDate":"2021-11-26T17:55:00.772513","indexId":"70223824","displayToPublicDate":"2021-08-30T07:32:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Early Pleistocene climate-induced erosion of the Alaska Range formed the Nenana Gravel","docAbstract":"The Pliocene-Pleistocene transition resulted in extensive global cooling and glaciation, but isolating this climate signal within erosion and exhumation responses in tectonically active regimes can be difficult. The Nenana Gravel is a foreland basin deposit in the northern foothills of the Alaska Range (USA) that has long been linked to unroofing of the Alaska Range starting ca. 6 Ma. Using 26Al/10Be cosmogenic nuclide burial dating, we determined the timing of deposition of the Nenana Gravel and an overlying remnant of the first glacial advance into the northern foothills. Our results indicate that initial deposition of the Nenana Gravel occurred at the onset of the Pleistocene ca. 2.34 Ma and continued until at least ca. 1.7 Ma. The timing of initial deposition is correlative with expansion of the Cordilleran ice sheet, suggesting that the deposit formed due to increased glacial erosion in the Alaska Range. Abandonment of Nenana Gravel deposition occurred prior to the first glaciation extending into the northern foothills. This glaciation was hypothesized to have occurred ca. 1.5 Ma, but we found that it occurred ca. 0.39 Ma. A Pleistocene age for the Nenana Gravel and marine oxygen isotope stage 10 age for the oldest glaciation of the foothills necessitate reanalysis of incision and tectonic rates in the northern foothills of the Alaska Range, in addition to a shift in perspective on how these deposits fit into the climatic and tectonic history of the region.
Adaptive traits can be dramatically altered by genome duplication. The study of interactions among traits, ploidy, and the environment are necessary to develop an understanding of how polyploidy affects niche differentiation and to develop restoration strategies for resilient native ecosystems.
Growth and fecundity were measured in common gardens for 39 populations of big sagebrush (Artemisia tridentata) containing two subspecies and two ploidy levels. General linear mixed-effect models assessed how much of the trait variation could be attributed to genetics (i.e., ploidy and climatic adaptation), environment, and gene–environment interactions.
Growth and fecundity variation were explained well by the mixed models (80% and 91%, respectively). Much of the trait variation was attributed to environment, and 15% of variation in growth and 34% of variation in seed yield were attributed to genetics. Genetic trait variation was mostly attributable to ploidy, with much higher growth and seed production in diploids, even in a warm-dry environment typically dominated by tetraploids. Population-level genetic variation was also evident and was related to the climate of each population's origin.
Ploidy is a strong predictor growth and seed yield, regardless of common-garden environment. The superior growth and fecundity of diploids across environments raises the question as to how tetraploids can be more prevalent than diploids, especially in warm-dry environments. Two hypotheses that may explain the abundance of tetraploids on the landscape include selection for drought resistance at the seedling stage, and greater competitive ability in water uptake in the upper soil horizon.
Surface energy balance (SEB) strongly influences the thermal state of permafrost, cryohydrological processes, and infrastructure stability. Road construction and snow accumulation affect the energy balance of underlying permafrost. Herein, we use an experimental road section of the Alaska Highway to develop a SEB model to quantify the surface energy components and ground surface temperature (GST) for different land cover types with varying snow regimes and properties. Simulated and measured ground temperatures are in good agreement, and our results show that the quantity of heat entering the embankment center and slope is mainly controlled by net radiation, and less by the sensible heat flux. In spring, lateral heat flux from the embankment center leads to earlier disappearance of snowpack on the embankment slope. In winter, the insulation created by the snow cover on the embankment slope reduces heat loss by a factor of three compared with the embankment center where the snow is plowed. The surface temperature offsets are 5.0°C and 7.8°C for the embankment center and slope, respectively. Furthermore, the heat flux released on the embankment slope exponentially decreases with increasing snow depth, and linearly decreases with earlier snow cover in fall and shorter snow-covered period in spring.
","language":"English","publisher":"Wiley","doi":"10.1002/ppp.2129","usgsCitation":"Chen, L., Voss, C., Fortier, D., and McKenzie, J.M., 2021, Surface energy balance of sub-Arctic roads with varying snow regimes and properties in permafrost regions: Permafrost and Periglacial Processes, v. 32, no. 4, p. 681-701, https://doi.org/10.1002/ppp.2129.","productDescription":"21 p.","startPage":"681","endPage":"701","ipdsId":"IP-121759","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":410466,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Yukon","otherGeospatial":"Beaver Creek area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -140.9,\n 62.4\n ],\n [\n -140.9,\n 62.3\n ],\n [\n -140.85,\n 62.3\n ],\n [\n -140.85,\n 62.4\n ],\n [\n -140.9,\n 62.4\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"32","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-08-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Chen, Lin","contributorId":299914,"corporation":false,"usgs":false,"family":"Chen","given":"Lin","email":"","affiliations":[],"preferred":false,"id":858867,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voss, Clifford I. 0000-0001-5923-2752","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":211844,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":858868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fortier, Daniel","contributorId":194641,"corporation":false,"usgs":false,"family":"Fortier","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":858869,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKenzie, Jeffrey M.","contributorId":176299,"corporation":false,"usgs":false,"family":"McKenzie","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":858870,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248735,"text":"70248735 - 2021 - Resilience of terrestrial and aquatic fauna to historical and future wildfire regimes in western North America","interactions":[],"lastModifiedDate":"2023-09-19T12:25:00.745005","indexId":"70248735","displayToPublicDate":"2021-08-30T07:22:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Resilience of terrestrial and aquatic fauna to historical and future wildfire regimes in western North America","docAbstract":"Wildfires in many western North American forests are becoming more frequent, larger, and severe, with changed seasonal patterns. In response, coniferous forest ecosystems will transition toward dominance by fire-adapted hardwoods, shrubs, meadows, and grasslands, which may benefit some faunal communities, but not others. We describe factors that limit and promote faunal resilience to shifting wildfire regimes for terrestrial and aquatic ecosystems. We highlight the potential value of interspersed nonforest patches to terrestrial wildlife. Similarly, we review watershed thresholds and factors that control the resilience of aquatic ecosystems to wildfire, mediated by thermal changes and chemical, debris, and sediment loadings. We present a 2-dimensional life history framework to describe temporal and spatial life history traits that species use to resist wildfire effects or to recover after wildfire disturbance at a metapopulation scale. The role of fire refuge is explored for metapopulations of species. In aquatic systems, recovery of assemblages postfire may be faster for smaller fires where unburned tributary basins or instream structures provide refuge from debris and sediment flows. We envision that more-frequent, lower-severity fires will favor opportunistic species and that less-frequent high-severity fires will favor better competitors. Along the spatial dimension, we hypothesize that fire regimes that are predictable and generate burned patches in close proximity to refuge will favor species that move to refuges and later recolonize, whereas fire regimes that tend to generate less-severely burned patches may favor species that shelter in place. Looking beyond the trees to forest fauna, we consider mitigation options to enhance resilience and buy time for species facing a no-analog future.
Geospatial artificial intelligence (GeoAI) can be defined broadly as the application of artificial intelligence methods and techniques to geospatial data, processes, models, and applications. The application of these methods to topographic data and phenomena is a focus of research in the US Geological Survey (USGS). Specifically, the USGS has researched and developed applications in terrain feature extraction, hydrographic network extraction, and semantic modeling. This article is a documentation of the recent work and current state of research and development. The article helps define the accomplishments and directions of research and applications in fields of GeoAI for topographic mapping within the USGS and more broadly.
Groundwater-dependent ecosystems and species (GDEs) are found throughout watersheds at locations of groundwater discharge, yet not all GDEs are the same, nor are the groundwater systems supporting them. Groundwater moves along a variety of flow paths of different lengths and with different contributing areas, ranging from shorter local flow paths with low discharge and large seasonal variability to streams, springs and wetlands to longer regional flow paths with potentially larger discharge and low seasonal variability, commonly at low basin elevations. How does this variation in physical hydrology affect the type and distribution of GDEs? Using data on hypsographic position, groundwater-dependent species distributions, groundwater pumping and streamflow from Oregon, USA, we provide a conceptual model and initial supporting evidence demonstrating that spatial variation in groundwater flow path scales, illustrated using basin hypsography, is a driver of non-random distribution of GDEs across watersheds. Further, we posit that the spatial variation in primary stressors to groundwater (e.g. pumping and climate change) will differentially affect GDEs depending on their hypsographic position. Furthermore, because of their use for irrigation and municipal water supply, regional groundwater systems and associated species are more likely to be studied and receive regulatory protection. Our initial data point to a disproportionate focus on larger discharge, lower elevation GDEs, which leads to a bias in our understanding of the full suite of biodiversity associated with groundwater discharge as well as their stressors and potential mechanisms for protection.
Despite increasing interest in winter limnology, few studies have examined under-ice zooplankton communities and the factors shaping them in different types of temperate lakes. To better understand drivers of zooplankton community structure in winter and summer, we sampled 13 lakes across a large trophic status gradient for crustacean zooplankton abundance, taxonomic and functional community composition and C/N stable isotopes. Average winter zooplankton densities were one-third of summer densities across the study lakes. Proportionally, cladocerans were more abundant in summer than winter, with the opposite pattern for calanoids and cyclopoids. In green (eutrophic) lakes, zooplankton densities were higher under the ice than in brown (dystrophic) and blue (oligotrophic) lakes, suggesting better conditions for zooplankton in productive lakes during winter. Overall, zooplankton communities were more similar across lakes under the ice than during the open water season. Feeding group classification showed a decrease in herbivore abundance and an increase in predators from summer to winter. C/N stable isotope results suggested higher lipid content in overwintering zooplankton and potentially increased reliance on the microbial loop by winter zooplankton. Our results show substantial variation in the seasonality of zooplankton communities in different lake types and identify some of the factors responsible for this variation.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/plankt/fbab050","usgsCitation":"Shchapov, K., Wilburn, P., Bramburger, A., Silsbe, G., Olmanson, L., Crawford, C., Litchmann, E., and Ozersky, T., 2021, Taxonomic and functional differences between winter and summer crustacean zooplankton communities in lakes across a trophic gradient: Journal of Plankton Research, v. 43, no. 5, p. 732-750, https://doi.org/10.1093/plankt/fbab050.","productDescription":"19 p.","startPage":"732","endPage":"750","ipdsId":"IP-129395","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":451050,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/41624","text":"External Repository"},{"id":389326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.41650390625,\n 44.793530904744074\n ],\n [\n -90.615234375,\n 44.793530904744074\n ],\n [\n -90.615234375,\n 48.56024979174329\n ],\n [\n -94.41650390625,\n 48.56024979174329\n ],\n [\n -94.41650390625,\n 44.793530904744074\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Shchapov, Kirill","contributorId":265794,"corporation":false,"usgs":false,"family":"Shchapov","given":"Kirill","email":"","affiliations":[{"id":18006,"text":"University of Minnesota Duluth","active":true,"usgs":false}],"preferred":false,"id":823401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilburn, P.","contributorId":265795,"corporation":false,"usgs":false,"family":"Wilburn","given":"P.","email":"","affiliations":[{"id":54804,"text":"NASA Ames","active":true,"usgs":false}],"preferred":false,"id":823402,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bramburger, A.","contributorId":265796,"corporation":false,"usgs":false,"family":"Bramburger","given":"A.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":823403,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Silsbe, G.","contributorId":265798,"corporation":false,"usgs":false,"family":"Silsbe","given":"G.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":823404,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olmanson, L.","contributorId":265799,"corporation":false,"usgs":false,"family":"Olmanson","given":"L.","affiliations":[{"id":33108,"text":"University of Minnesota Twin Cities","active":true,"usgs":false}],"preferred":false,"id":823405,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":213607,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher J.","email":"cjcrawford@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":823406,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Litchmann, E.","contributorId":265800,"corporation":false,"usgs":false,"family":"Litchmann","given":"E.","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":823407,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ozersky, T.","contributorId":265801,"corporation":false,"usgs":false,"family":"Ozersky","given":"T.","affiliations":[{"id":18006,"text":"University of Minnesota Duluth","active":true,"usgs":false}],"preferred":false,"id":823408,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70263865,"text":"70263865 - 2021 - LiDAR and paleoseismology solve earthquake mystery in the Pacific Northwest, USA","interactions":[],"lastModifiedDate":"2025-02-27T14:14:12.482234","indexId":"70263865","displayToPublicDate":"2021-08-28T00:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"LiDAR and paleoseismology solve earthquake mystery in the Pacific Northwest, USA","docAbstract":"One of the largest historical earthquakes in the U.S. Pacific Northwest occurred on December 15, 1872 near the south end of Lake Chelan. Lack of recognized surface deformation suggested that the earthquake occurred on a blind, perhaps deep, fault. New LiDAR data revealed a NW-side-up scarp along the north side of Spencer Canyon near Entiat, Washington. Landslides triggered during the earthquake impounded small ponds in Spencer Canyon; the larger of the two landslides obliterated a portion of the scarp. Tree-ring counts show that the oldest trees on each landslide are 130 and 128 years old, and lend credence to the idea that the earthquake triggered the landslides. Trenches across the scarp exposed a NW-dipping thrust fault offsetting young soils and Mesozoic bedrock. Radiocarbon and tree ring data shows that the last fault movement was between 1856 and 1873 CE, and was most likely during the 1872 CE earthquake.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL093318","usgsCitation":"Sherrod, B.L., Blakely, R., and Weaver, C., 2021, LiDAR and paleoseismology solve earthquake mystery in the Pacific Northwest, USA: Geophysical Research Letters, v. 48, no. 16, e2021GL093318, 9 p., https://doi.org/10.1029/2021GL093318.","productDescription":"e2021GL093318, 9 p.","ipdsId":"IP-097563","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":487175,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021gl093318","text":"Publisher Index Page"},{"id":482509,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Idaho, Montana, Oregon, Washington","otherGeospatial":"Pacific Northwest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -128.51232932665914,\n 52.80136491932822\n ],\n [\n -128.51232932665914,\n 42.07755395865152\n ],\n [\n -111.38444038177542,\n 42.07755395865152\n ],\n [\n -111.38444038177542,\n 52.80136491932822\n ],\n [\n -128.51232932665914,\n 52.80136491932822\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"48","issue":"16","noUsgsAuthors":false,"publicationDate":"2021-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blakely, Richard J.","contributorId":351509,"corporation":false,"usgs":false,"family":"Blakely","given":"Richard J.","affiliations":[{"id":36625,"text":"Emeritus","active":true,"usgs":false}],"preferred":false,"id":928753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weaver, Craig S.","contributorId":224057,"corporation":false,"usgs":false,"family":"Weaver","given":"Craig S.","affiliations":[],"preferred":false,"id":928754,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223484,"text":"ofr20211077 - 2021 - Water quality, instream habitat, and the distribution of suckers in the upper Lost River watershed of Oregon and California, summer 2018","interactions":[],"lastModifiedDate":"2021-08-30T11:54:50.759707","indexId":"ofr20211077","displayToPublicDate":"2021-08-27T10:32:27","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1077","displayTitle":"Water Quality, Instream Habitat, and the Distribution of Suckers in the Upper Lost River Watershed of Oregon and California, Summer 2018","title":"Water quality, instream habitat, and the distribution of suckers in the upper Lost River watershed of Oregon and California, summer 2018","docAbstract":"Endangered Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) suckers primarily use lotic habitats during the spring spawning season in the Upper Klamath Lake watershed. However, summer-time surveys of the upper Lost River watershed in 1972, 1975 and 1989–90 indicated that adults of both endangered species use tributaries of Clear Lake Reservoir (hereafter: Clear Lake) year-round. Adult shortnose suckers have also been documented to use tributaries of Gerber Reservoir year-round. We surveyed the tributaries of Clear Lake and Gerber Reservoir to provide up-to-date information on the timing, distribution, and habitat use within the upper Lost River drainage by these two endangered sucker species.
Contrary to previous studies, this study did not capture any Lost River suckers in the Clear Lake tributaries. Genetics samples from suckers collected during this study were used to verify that no Lost River suckers were captured. At the time of this study, genetics could not identify the differences between shortnose and the non-endangered Klamath largescale suckers (Catostomus snyderi), therefore, morphology was used to separate these two species. Furthermore, the shortnose suckers and the Klamath largescale suckers documented in the upper Lost River drainage are more similar to Klamath largescale suckers than shortnose suckers that exist in the Upper Klamath Lake recovery unit. Therefore, the suckers we documented during our surveys were most likely Klamath largescale suckers.
We captured suckers, age-0 to age-9, in the Clear Lake tributaries within stream pools and flooded meadows behind water retention structures. However, no suckers were collected in small reservoirs sampled upstream of Clear Lake. Suckers were found in habitats with mud and fine substrate at depths of 0.5–3.0 meters, with most captured at 1.0 meter or less. Suckers co-occurred with nonnative species, which were more abundant in our survey than in previous surveys in the tributaries to Clear Lake.
Gerber Reservoir tributaries yielded more suckers per unit effort than Clear Lake tributaries. All suckers captured in the tributaries of Gerber Reservoir were identified as Klamath Largescale suckers. The suckers in tributaries to Gerber Reservoir were collected in similar habitat as those in Clear Lake tributaries and were age-0 to age-6.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211077","collaboration":"Prepared in cooperation with the U.S. Bureau of Reclamation","usgsCitation":"Martin, B.A., Burdick, S.M., Staiger, S.T., and Kelsey, C., 2021, Water quality, instream habitat, and the distribution of suckers in the upper Lost River watershed of Oregon and California, summer 2018: U.S. Geological Survey Open-File Report 2021–1077, 29 p., https://doi.org/10.3133/ofr20211077.","productDescription":"v, 29 p.","onlineOnly":"Y","ipdsId":"IP-122858","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":388609,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1077/coverthb.jpg"},{"id":388610,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1077/ofr20211077.pdf","text":"Report","size":"3.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1077"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Lost River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.27783203125,\n 41.63186741069748\n ],\n [\n -120.73974609374999,\n 41.63186741069748\n ],\n [\n -120.73974609374999,\n 42.66628070564928\n ],\n [\n -122.27783203125,\n 42.66628070564928\n ],\n [\n -122.27783203125,\n 41.63186741069748\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016