Bromus tectorum (cheatgrass) has successfully invaded and established throughout the western United States. Bromus tectorum grows early in the season and this early growth allows B. tectorum to outcompete native species, which has led to dramatic shifts in ecosystem function and plant community composition after B. tectorum invades. If the phenology of native species is unable to track changing climate as effectively as B. tectorum’s phenology then climate change may facilitate further invasion. To better understand how B. tectorum phenology will respond to future climate, we tracked the timing of B. tectorum germination, flowering, and senescence over a decade in three in situ climate manipulation experiments with treatments that increased temperatures (2°C and 4°C above ambient), altered precipitation regimes, or applied a combination of each. Linear mixed-effects models were used to analyze treatment effects on the timing of germination, flowering, senescence, and on the length of the vegetative growing season (time from germination to flowering) in each experiment. Altered precipitation treatments were only applied in early years of the study and neither precipitation treatments nor the treatments’ legacies significantly affected B. tectorum phenology. The timing of germination did not significantly vary between any warming treatments and their respective ambient plots. However, plots that were warmed had advances in the timing of B. tectorum flowering and senescence, as well as shorter vegetative growing seasons. The phenological advances caused by warming increased with increasing degrees of experimental warming. The greatest differences between warmed and ambient plots were seen in the length of the vegetative growing season, which was shortened by approximately 12 and 7 days in the +4°C and +2°C warming levels, respectively. The effects of experimental warming were small compared to the effects of interannual climate variation, suggesting that interactive controls and the timing of multiple climatic factors are important in determining B. tectorum phenology. Taken together, these results help elucidate how B. tectorum phenology may respond to future climate, increasing our predictive capacity for estimating when to time B. tectorum control efforts and how to more effectively manage this exotic annual grass.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fpls.2020.570001","usgsCitation":"Howell, A.J., Winkler, D.E., Phillips, M.L., McNellis, B., and Reed, S., 2020, Experimental warming changes phenology and shortens growing season of the dominant invasive plant Bromus tectorum (cheatgrass): Frontiers in Plant Science, v. 11, 570001, 15 p., https://doi.org/10.3389/fpls.2020.570001.","productDescription":"570001, 15 p.","ipdsId":"IP-122205","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":455034,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fpls.2020.570001","text":"Publisher Index Page"},{"id":380789,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","city":"Moab","otherGeospatial":"Castle Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.69848632812499,\n 38.50948995925553\n ],\n [\n -109.33868408203125,\n 38.50948995925553\n ],\n [\n -109.33868408203125,\n 38.74123075381228\n ],\n [\n -109.69848632812499,\n 38.74123075381228\n ],\n [\n -109.69848632812499,\n 38.50948995925553\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2020-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Howell, Armin J. 0000-0003-1243-0238 ahowell@usgs.gov","orcid":"https://orcid.org/0000-0003-1243-0238","contributorId":196798,"corporation":false,"usgs":true,"family":"Howell","given":"Armin","email":"ahowell@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, Michala Lee 0000-0001-7005-8740","orcid":"https://orcid.org/0000-0001-7005-8740","contributorId":245186,"corporation":false,"usgs":true,"family":"Phillips","given":"Michala","email":"","middleInitial":"Lee","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805559,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNellis, Brandon","contributorId":245187,"corporation":false,"usgs":false,"family":"McNellis","given":"Brandon","affiliations":[{"id":49106,"text":"Department of Forest, Rangeland, and Fire Sciences, University of Idaho, Moscow, Idaho, USA","active":true,"usgs":false}],"preferred":false,"id":805560,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805561,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216544,"text":"70216544 - 2020 - Climate sensitivity of water use by riparian woodlands at landscape scales","interactions":[],"lastModifiedDate":"2020-12-14T16:56:03.212697","indexId":"70216544","displayToPublicDate":"2020-10-15T10:46:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Climate sensitivity of water use by riparian woodlands at landscape scales","docAbstract":"Semi‐arid riparian woodlands face threats from increasing extractive water demand and climate change in dryland landscapes worldwide. Improved landscape‐scale understanding of riparian woodland water use (evapotranspiration, ET) and its sensitivity to climate variables is needed to strategically manage water resources, as well as to create successful ecosystem conservation and restoration plans for potential climate futures. In this work, we assess the spatial and temporal variability of Cottonwood (Populus fremontii)‐Willow (Salix gooddingii) riparian gallery woodland ET and its relationships to vegetation structure and climate variables for 80 km of the San Pedro River corridor in southeastern Arizona, USA, between 2014 and 2019. We use a novel combination of publicly available remote sensing, climate and hydrological datasets: cloud‐based Landsat thermal remote sensing data products for ET (Google Earth Engine EEFlux), Landsat multispectral imagery and field data‐based calibrations to vegetation structure (leaf‐area index, LAI), and open‐source climate and hydrological data. We show that at landscape scales, daily ET rates (6–10 mm day−1) and growing season ET totals (400–1,400 mm) matched rates of published field data, and modelled reach‐scale average LAI (0.80–1.70) matched lower ranges of published field data. Over 6 years, the spatial variability of total growing season ET (CV = 0.18) exceeded that of temporal variability (CV = 0.10), indicating the importance of reach‐scale vegetation and hydrological conditions for controlling ET dynamics. Responses of ET to climate differed between perennial and intermittent‐flow stream reaches. At perennial‐flow reaches, ET correlated significantly with temperature, whilst at intermittent‐flow sites ET correlated significantly with rainfall and stream discharge. Amongst reaches studied in detail, we found positive but differing logarithmic relationships between LAI and ET. By documenting patterns of high spatial variability of ET at basin scales, these results underscore the importance of accurately accounting for differences in woodland vegetation structure and hydrological conditions for assessing water‐use requirements. Results also suggest that the climate sensitivity of ET may be used as a remote indicator of subsurface water resources relative to vegetation demand, and an indicator for informing conservation management priorities.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13942","usgsCitation":"Mayes, M., Caylor, K.K., Singer, M.B., Stella, J., Roberts, D., and Nagler, P.L., 2020, Climate sensitivity of water use by riparian woodlands at landscape scales: Hydrological Processes, v. 34, no. 25, p. 4884-4903, https://doi.org/10.1002/hyp.13942.","productDescription":"10 p.","startPage":"4884","endPage":"4903","ipdsId":"IP-120214","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":455038,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://orca.cardiff.ac.uk/id/eprint/135647/","text":"External Repository"},{"id":380788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"San Pedro River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.58563232421875,\n 31.3348710339506\n ],\n [\n -109.79461669921875,\n 31.3348710339506\n ],\n [\n -109.79461669921875,\n 32.15468722002481\n ],\n [\n -110.58563232421875,\n 32.15468722002481\n ],\n [\n -110.58563232421875,\n 31.3348710339506\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"25","noUsgsAuthors":false,"publicationDate":"2020-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Mayes, Marc","contributorId":245241,"corporation":false,"usgs":false,"family":"Mayes","given":"Marc","email":"","affiliations":[],"preferred":false,"id":805665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caylor, Kelly K.","contributorId":245242,"corporation":false,"usgs":false,"family":"Caylor","given":"Kelly","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":805666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Singer, Michael B.","contributorId":168369,"corporation":false,"usgs":false,"family":"Singer","given":"Michael","email":"","middleInitial":"B.","affiliations":[{"id":25268,"text":"University of St Andrews, UK","active":true,"usgs":false}],"preferred":false,"id":805667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stella, John C","contributorId":149423,"corporation":false,"usgs":false,"family":"Stella","given":"John C","affiliations":[{"id":17732,"text":"Professor, Dept of Forest & Natural Resources Mgmt, SUNY at ESF","active":true,"usgs":false}],"preferred":false,"id":805668,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, Dar","contributorId":13721,"corporation":false,"usgs":true,"family":"Roberts","given":"Dar","affiliations":[],"preferred":false,"id":805669,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805569,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216886,"text":"70216886 - 2020 - Sediment connectivity: A framework for analyzing coastal sediment transport pathways","interactions":[],"lastModifiedDate":"2020-12-14T14:53:07.559848","indexId":"70216886","displayToPublicDate":"2020-10-15T08:48:23","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"Sediment connectivity: A framework for analyzing coastal sediment transport pathways","docAbstract":"Connectivity provides a framework for analyzing coastal sediment transport pathways, building on conceptual advances in graph theory from other scientific disciplines. Connectivity schematizes sediment pathways as a directed graph (i.e., a set of nodes and links). This study presents a novel application of graph theory and connectivity metrics like modularity and centrality to coastal sediment dynamics, exemplified here using Ameland Inlet in the Netherlands. We divide the study site into geomorphic cells (i.e., nodes) and then quantify sediment transport between these cells (i.e., links) using a numerical model. The system of cells and fluxes between them is then schematized in a network described by an adjacency matrix. Network metrics like link density, asymmetry, and modularity quantify system‐wide connectivity. The degree, strength, and centrality of individual nodes identify key locations and pathways throughout the system. For instance, these metrics indicate that under strictly tidal forcing, sand originating near shore predominantly bypasses Ameland Inlet via the inlet channels, whereas sand on the deeper foreshore mainly bypasses the inlet via the outer delta shoals. Connectivity analysis can also inform practical management decisions about where to place sand nourishments, the fate of nourishment sand, or how to monitor locations vulnerable to perturbations. There are still open challenges associated with quantifying connectivity at varying space and time scales and the development of connectivity metrics specific to coastal systems. Nonetheless, connectivity provides a promising technique for predicting the response of our coasts to climate change and the human adaptations it provokes.
While there is growing demand for use of climate model projections to understand the potential impacts of future climate on resources, there is a lack of effective visuals that convey the range of possible climates across spatial scales and with uncertainties that potential users need to inform their impact assessments and studies. We use usability testing including eye tracking to explore how a group of resource professionals (foresters) interpret and understand a series of graphical representations of future climate change, housed within a web-based decision support system (DSS), that address limitations identified in other tools. We find that a three-map layout effectively communicates the spread of future climate projections spatially, that location-specific information is effectively communicated if depicted both spatially on a map and temporally on a time series plot, and that model error metrics may be useful for communicating uncertainty and in demonstrating the utility of these future climate datasets.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/WCAS-D-19-0152.1","usgsCitation":"Davis, C., Aldridge, H.D., Boyles, R., McNeal, K., Mauldin, L.C., and Atkins, R.M., 2020, Visually communicating future climate in a web environment: Weather, Climate, and Society, v. 12, no. 4, p. 877-896, https://doi.org/10.1175/WCAS-D-19-0152.1.","productDescription":"20 p.","startPage":"877","endPage":"896","ipdsId":"IP-107086","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":455049,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/wcas-d-19-0152.1","text":"Publisher Index Page"},{"id":379577,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Corey","contributorId":221987,"corporation":false,"usgs":false,"family":"Davis","given":"Corey","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":802272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Heather D","contributorId":221986,"corporation":false,"usgs":false,"family":"Aldridge","given":"Heather","email":"","middleInitial":"D","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":802273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyles, Ryan 0000-0001-9272-867X","orcid":"https://orcid.org/0000-0001-9272-867X","contributorId":221983,"corporation":false,"usgs":true,"family":"Boyles","given":"Ryan","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":802274,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNeal, Karen","contributorId":221985,"corporation":false,"usgs":false,"family":"McNeal","given":"Karen","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":802275,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mauldin, Lindsay C.","contributorId":221984,"corporation":false,"usgs":false,"family":"Mauldin","given":"Lindsay","email":"","middleInitial":"C.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":802276,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Atkins, Rachel M.","contributorId":221988,"corporation":false,"usgs":false,"family":"Atkins","given":"Rachel","email":"","middleInitial":"M.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":802277,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216299,"text":"70216299 - 2020 - Using Markov chains to quantitatively assess movement patterns of invasive fishes impacted by a carbon dioxide barrier in outdoor ponds","interactions":[],"lastModifiedDate":"2020-11-11T13:24:46.15541","indexId":"70216299","displayToPublicDate":"2020-10-14T07:19:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2827,"text":"Natural Resource Modeling","active":true,"publicationSubtype":{"id":10}},"title":"Using Markov chains to quantitatively assess movement patterns of invasive fishes impacted by a carbon dioxide barrier in outdoor ponds","docAbstract":"Natural resource managers use barriers to deter the movement of aquatic invasive species. Research and development of new invasive species barriers is often evaluated in pond and field scales using high‐resolution telemetry data. Telemetry data sets can be a rich source of data about fish movement and behavior but can be difficult to analyze due to the size of these data sets as well as their irregular sampling intervals. Due to the challenges, most barrier studies only use summary endpoints, such as barrier passage counts or average (e.g., mean or median) fish distance from the barrier, to describe the data. To examine more fine‐scale fish movement patterns, we developed a first‐order Markov chain. We then used this model to help understand the impacts of a barrier on fish behavior. For our study system, we used data from a previous study examining how bighead and silver carp (two invasive fish species in the United States) responded to a carbon dioxide (CO2) barrier in a pond.
","language":"English","publisher":"Wiley","doi":"10.1111/nrm.12281","usgsCitation":"Borland, L.K., Mulcahy, C.J., Bennie, B., Baumann, D.D., Haro, R.J., Van Appledorn, M., Jankowski, K.J., Cupp, A.R., and Erickson, R.A., 2020, Using Markov chains to quantitatively assess movement patterns of invasive fishes impacted by a carbon dioxide barrier in outdoor ponds: Natural Resource Modeling, v. 33, no. 4, e12281, 16 p., https://doi.org/10.1111/nrm.12281.","productDescription":"e12281, 16 p.","ipdsId":"IP-106075","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":455059,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nrm.12281","text":"Publisher Index Page"},{"id":380400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-09-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Borland, Lauren K","contributorId":244789,"corporation":false,"usgs":false,"family":"Borland","given":"Lauren","email":"","middleInitial":"K","affiliations":[{"id":36422,"text":"University of Texas","active":true,"usgs":false}],"preferred":false,"id":804592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mulcahy, Collin J","contributorId":244790,"corporation":false,"usgs":false,"family":"Mulcahy","given":"Collin","email":"","middleInitial":"J","affiliations":[{"id":48976,"text":"SUNY Cobleskill","active":true,"usgs":false}],"preferred":false,"id":804593,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennie, Barb","contributorId":244792,"corporation":false,"usgs":false,"family":"Bennie","given":"Barb","email":"","affiliations":[{"id":48977,"text":"UW-La Crosse","active":true,"usgs":false}],"preferred":false,"id":804594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baumann, Douglas D","contributorId":244793,"corporation":false,"usgs":false,"family":"Baumann","given":"Douglas","email":"","middleInitial":"D","affiliations":[{"id":48977,"text":"UW-La Crosse","active":true,"usgs":false}],"preferred":false,"id":804595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haro, Roger J.","contributorId":139538,"corporation":false,"usgs":false,"family":"Haro","given":"Roger","email":"","middleInitial":"J.","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":804596,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":804597,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jankowski, Kathi Jo 0000-0002-3292-4182","orcid":"https://orcid.org/0000-0002-3292-4182","contributorId":207429,"corporation":false,"usgs":true,"family":"Jankowski","given":"Kathi","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":804598,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":804599,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":804600,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70214666,"text":"ofr20201101 - 2020 - Geologic and mineral map (modified from the 1975 original map compilation by A.S. Shadchinev and others) and hyperspectral surface materials maps of the Ghorband, Salang, and Panjsher River Basins; Kapisa, Panjsher, Parwan, and Baghlan Provinces, Afghanistan","interactions":[],"lastModifiedDate":"2021-08-23T16:19:59.150981","indexId":"ofr20201101","displayToPublicDate":"2020-10-13T12:15:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1101","displayTitle":"Geologic and Mineral Map (Modified from the 1975 Original Map Compilation by A.S. Shadchinev and Others) and Hyperspectral Surface Materials Maps of the Ghorband, Salang, and Panjsher River Basins; Kapisa, Panjsher, Parwan, and Baghlan Provinces, Afghanistan","title":"Geologic and mineral map (modified from the 1975 original map compilation by A.S. Shadchinev and others) and hyperspectral surface materials maps of the Ghorband, Salang, and Panjsher River Basins; Kapisa, Panjsher, Parwan, and Baghlan Provinces, Afghanistan","docAbstract":"The geologic map and cross sections are a redrafted and modified version of the Geologic map and map of mineral resources of the basins of Ghorband, Salang, and Panjsher; located in the Kapisa, Panjsher, Parwan, and Baghlan Provinces, Afghanistan. The original map and cross sections are contained in an unpublished Soviet report no. 1162A (Shadchinev and others, 1975) prepared in cooperation with the Ministry of Mines and Industries of the Royal Government of Afghanistan, in Kabul during 1975, under contract no. 55–184/17500. This redrafted map consists of parts of quadrangle map sheets 503–F, 504–C, 504–D, 504–E, and 504–F shown on an index map that can be found on the original 1:100,000-scale map by Shadchinev and others (1975). The redrafted map and cross sections illustrate the mineral deposits and geologic structure of the Ghorband, Salang, and Panjsher River Basins. Because there were no location coordinates provided on the original Soviet map, the map was registered to drainage patterns identified by contours from the Global Digital Elevation Model (GDEM). The end result can only be considered a best fit for the map extend, and some features may not be positioned in their correct geographic location.
The redrafted geologic map and cross sections reproduce the topology of rock units, contacts, and faults of the original Soviet map and cross sections, and includes minor modifications based on our examination of the originals. Table 1, provided on both map sheets 1 and 2, shows mineral commodity locations also from the original Soviet map. However, because of the poor quality of the original map, some map features could not be identified and some may be misinterpreted. Further, we have attempted to translate the original Russian terminology and rock classifications into modern English geologic usage as literally as possible without changing any genetic or process-oriented implications in the original rock-unit descriptions. We also use the rock-unit age designations from the original maps, however, rock-unit colors and symbols differ from the colors and symbols shown on the original version. Unit colors were selected according to the color and pattern scheme of the Commission for the Geological Map of the World (http://www.ccgm.org). Unit symbols were assigned based on the geologic age and unit descriptions provided on the original Soviet map. Elevations on the cross sections are derived from the original topography and may not match the Global GDEM topography used on the redrafted geologic map of this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201101","collaboration":"Prepared in cooperation with the Afghan Geological Survey under the auspices of the U.S. Agency for International Development","usgsCitation":"Stettner, W.R., Koroleva, N.E., Masonic, L.M., and Shields, D.A., comps., 2020, Geologic and mineral map (modified from the 1975 original map compilation by A.S. Shadchinev and others) and hyperspectral surface materials maps of the Ghorband, Salang, and Panjsher River Basins; Kapisa, Panjsher, Parwan, and Baghlan Provinces, Afghanistan: U.S. Geological Survey Open-File Report 2020–1101, 2 sheets, scale 1:100,000, https://doi.org/10.3133/ofr20201101.","productDescription":"2 Sheets: 41.50 x 30.50 inches and 41.50 x 52.00 inches","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057774","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":379032,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1101/ofr20201101_sheet2.pdf","text":"Sheet 2","size":"203 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":378954,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1101/coverthb.jpg"},{"id":378955,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1101/ofr20201101_sheet1.pdf","text":"Sheet 1","size":"61.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1101"}],"scale":"100000","country":"Afghanistan","state":"Baghlan, Kapisa, Panjsher, Parwan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 67.21435546875,\n 34.32529192442733\n ],\n [\n 71.3671875,\n 34.32529192442733\n ],\n [\n 71.3671875,\n 36.35052700542763\n ],\n [\n 67.21435546875,\n 36.35052700542763\n ],\n [\n 67.21435546875,\n 34.32529192442733\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 21092
Sheet 1
Sheet 2
Salt marshes are valuable ecosystems that must trap sediments and accrete in order to counteract the deleterious effect of sea‐level rise. Previous studies have shown that the capacity of marshes to build up vertically depends on both autogenous and exogenous processes including eco‐geomorphic feedbacks and sediment supply from in‐land and coastal ocean. There have been numerous efforts to quantify the role played by the sediments coming from marsh edge erosion on the resistance of salt marshes to sea‐level rise. However, the majority of existing studies investigating the interplay between lateral and vertical dynamics use simplified modelling approaches and they do not consider that marsh retreat can affect the regional scale hydrodynamics and sediment retention in back‐barrier basins.
In this study, we evaluated the fate of the sediments originating from marsh lateral loss by using high‐resolution numerical model simulations of Jamaica Bay, a small lagoonal estuary located in New York City. Our findings show that up to 42% of the sediments released during marsh edge erosion deposits on the shallow areas of the basin and over the vegetated marsh platforms, contributing positively to the sediment budget of the remaining salt marshes. Furthermore, we demonstrate that with the present‐day sediment supply from the ocean the system cannot keep pace with sea‐level rise even accounting for the sediment liberated in the bay through marsh degradation. Our study highlights the relevance of multiple sediment sources for the maintenance of the marsh complex.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JF005751","usgsCitation":"Donatelli, C., Kalra, T., Fagherazzi, S., Zhang, X., and Leonardi, N., 2020, Dynamics of marsh-derived sediments in lagoon-type estuaries: Journal of Geophysical Research, v. 125, e2020JF005751, 15 p., https://doi.org/10.1029/2020JF005751.","productDescription":"e2020JF005751, 15 p.","ipdsId":"IP-122498","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":455066,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jf005751","text":"Publisher Index Page"},{"id":379479,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Jamaica Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.93524169921875,\n 40.56911064456484\n ],\n [\n -73.72718811035156,\n 40.56911064456484\n ],\n [\n -73.72718811035156,\n 40.656680564044166\n ],\n [\n -73.93524169921875,\n 40.656680564044166\n ],\n [\n -73.93524169921875,\n 40.56911064456484\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","noUsgsAuthors":false,"publicationDate":"2020-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Donatelli, Carmine","contributorId":205614,"corporation":false,"usgs":false,"family":"Donatelli","given":"Carmine","email":"","affiliations":[{"id":37127,"text":"University of Liverpool, Liverpool UK","active":true,"usgs":false}],"preferred":false,"id":801968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":801969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagherazzi, Sergio","contributorId":207153,"corporation":false,"usgs":false,"family":"Fagherazzi","given":"Sergio","email":"","affiliations":[{"id":37465,"text":"Boston University, Earth and Environment, Boston, 02215, USA.","active":true,"usgs":false}],"preferred":false,"id":801970,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhang, Xoaohe","contributorId":243292,"corporation":false,"usgs":false,"family":"Zhang","given":"Xoaohe","email":"","affiliations":[{"id":48675,"text":"Department of Geography and Planning, School of Environmental Sciences, Faculty of Science and Engineering, University of Liverpool, Roxby Building, Chatham St., Liverpool L69 7ZT, UK","active":true,"usgs":false}],"preferred":false,"id":801971,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leonardi, Nicoletta","contributorId":174783,"corporation":false,"usgs":false,"family":"Leonardi","given":"Nicoletta","affiliations":[{"id":27508,"text":"Dept of Earth and Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":801972,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216016,"text":"70216016 - 2020 - Does channel narrowing by floodplain growth necessarily indicate sediment surplus? Lessons from sediment‐transport analyses in the Green and Colorado rivers, Canyonlands, Utah","interactions":[],"lastModifiedDate":"2020-11-03T13:18:49.006877","indexId":"70216016","displayToPublicDate":"2020-10-13T07:12:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"Does channel narrowing by floodplain growth necessarily indicate sediment surplus? Lessons from sediment‐transport analyses in the Green and Colorado rivers, Canyonlands, Utah","docAbstract":"Analyses of suspended sediment transport provide valuable insight into the role that sediment supply plays in causing geomorphic change. The sediment supply within a river system evolves depending on the discharge, flood frequency and duration, changes in sediment input, and ecohydraulic conditions that modify sediment transport processes. Changes in supply can be evaluated through analyses of coupled changes in suspended sediment concentration and grain size. The concentration of sand in transport in the Green and Colorado Rivers is most strongly controlled by discharge and the bed sand grain size distribution. Since the 1950s, sand loads have decreased in response to declines in peak discharge in the Green River and coarsening of the bed sand in the Colorado River. However, changes in the bed sand grain size distribution are associated with large changes in suspended sand concentration in both rivers; concentration varies by a factor of ~3 in the Green River and a factor of ~8 in the Colorado River, depending on the bed sand grain size distribution. Analyses of hysteresis in suspended sediment measurements show that sediment depletion during annual floods is most strongly controlled by flood duration, with peak discharge being nearly equally important in the Green River. Despite channel narrowing in both rivers, periods of bed sand coarsening and sediment depletion during annual floods indicate that these rivers are not necessarily in sediment surplus. Channel narrowing appears to be strongly controlled by short‐term declines in flood magnitude and the ecohydraulic effects of vegetation and may not be indicative of the long‐term sediment budget.
Soil respiration is a primary component of the terrestrial carbon cycle. However, predicting the response of soil respiration to climate change remains a challenge due to the complex interactions between environmental drivers, especially plant phenology, temperature, and soil moisture. In this study, we use a 1‐D diffusion‐reaction model to calculate depth‐resolved CO2 production rates from soil CO2 concentrations and surface efflux observations in a subalpine meadow in the East River watershed, CO. Modeled rates are compared to in situ soil temperature and moisture conditions and MODIS satellite enhanced vegetation index (EVI) representing plant phenology across three hydrologically distinct growing seasons from 2016–2018. While soil respiration correlated with temperature on diel timescales (p < 0.05), seasonal variability was dominated by soil moisture and plant phenology (p < 0.05). We observed significant respiration increases in response to precipitation events; however, magnitude and duration were significantly higher in 2017 than 2016 despite similar wetting characteristics. Based on MODIS EVI, we suggest that the respiration response to rainfall is controlled by plant phenology, which in turn reflects the capacity of plants to respond to precipitation via increased photosynthesis and autotrophic respiration, behavior that is not captured in typical soil respiration pulse models. Projected changes in montane climate such as earlier snowmelt and prolonged fore‐summer drought may decrease soil respiration fluxes by decreasing the overlap between peak productivity and the summer monsoon. Finally, we observed significant late season CO2 fluxes from the deep subsoil (>165 cm) that support growing evidence for the importance of subsoil processes in driving integrated respiration fluxes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JG005924","usgsCitation":"Winnick, M., Lawrence, C.R., McCormick, M., Druhan, J., and Maher, K., 2020, Soil respiration response to rainfall modulated by plant phenology in a montane meadow, East River, Colorado, USA: Journal of Geophysical Research Biogeosciences, v. 125, no. 10, e2020JG005924, 20 p., https://doi.org/10.1029/2020JG005924.","productDescription":"e2020JG005924, 20 p.","ipdsId":"IP-108485","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":455072,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1664387","text":"External Repository"},{"id":381100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"East River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.061767578125,\n 38.50626606567193\n ],\n [\n -106.82968139648436,\n 38.50626606567193\n ],\n [\n -106.82968139648436,\n 38.922023851268925\n ],\n [\n -107.061767578125,\n 38.922023851268925\n ],\n [\n -107.061767578125,\n 38.50626606567193\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Winnick, Mathew","contributorId":245458,"corporation":false,"usgs":false,"family":"Winnick","given":"Mathew","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":806219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":806220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, Maeve","contributorId":245459,"corporation":false,"usgs":false,"family":"McCormick","given":"Maeve","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Druhan, Jennifer","contributorId":245460,"corporation":false,"usgs":false,"family":"Druhan","given":"Jennifer","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":806222,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maher, Kate","contributorId":245461,"corporation":false,"usgs":false,"family":"Maher","given":"Kate","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806223,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218020,"text":"70218020 - 2020 - The role of pre-magmatic rifting in shaping a volcanic continental margin: An example from the Eastern North American Margin","interactions":[],"lastModifiedDate":"2021-02-12T13:31:09.605389","indexId":"70218020","displayToPublicDate":"2020-10-12T07:27:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7585,"text":"Journal of Geophysical Research-- Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"The role of pre-magmatic rifting in shaping a volcanic continental margin: An example from the Eastern North American Margin","docAbstract":"Both magmatic and tectonic processes contribute to the formation of volcanic continental margins. Such margins are thought to undergo extension across a narrow zone of lithospheric thinning (~100 km). New observations based on existing and reprocessed data from the Eastern North American Margin contradict this hypothesis. With ~64,000 km of 2‐D seismic data tied to 40 wells combined with published refraction, deep reflection, receiver function, and onshore drilling efforts, we quantified along‐strike variations in the distribution of rift structures, magmatism, crustal thickness, and early post‐rift sedimentation under the shelf of Baltimore Canyon Trough (BCT), Long Island Platform, and Georges Bank Basin (GBB). Results indicate that BCT is narrow (80–120 km) with a sharp basement hinge and few rift basins. The seaward dipping reflectors (SDR) there extend ~50 km seaward of the hinge line. In contrast, the GBB is wide (~200 km), has many syn‐rift structures, and the SDR there extend ~200 km seaward of the hinge line. Early post‐rift depocenters at the GBB coincide with thinner crust suggesting “uniform” thinning of the entire lithosphere. Models for the formation of volcanic margins do not explain the wide structure of the GBB. We argue that crustal thinning of the BCT was closely associated with late syn‐rift magmatism, whereas the broad thinning of the GBB segment predated magmatism. Correlation of these variations to crustal terranes of different compositions suggests that the inherited rheology determined the premagmatic response of the lithosphere to extension.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB019576","usgsCitation":"Lang, G., ten Brink, U., Hutchinson, D., Mountain, G., and Schattner, U., 2020, The role of pre-magmatic rifting in shaping a volcanic continental margin: An example from the Eastern North American Margin: Journal of Geophysical Research-- Solid Earth, v. 125, no. 11, e2020JB019576, 33 p., https://doi.org/10.1029/2020JB019576.","productDescription":"e2020JB019576, 33 p.","ipdsId":"IP-121253","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":455078,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2020jb019576","text":"External Repository"},{"id":383254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Lang, G. 0000-0002-6505-5163","orcid":"https://orcid.org/0000-0002-6505-5163","contributorId":250704,"corporation":false,"usgs":false,"family":"Lang","given":"G.","email":"","affiliations":[{"id":50227,"text":"Dr. Moses Strauss Department of Marine Geosciences, Charney School of Marine Sciences, University of Haifa, Mt. Carmel, Haifa, 31905, Israel","active":true,"usgs":false}],"preferred":false,"id":810237,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"ten Brink, Uri S. 0000-0001-6858-3001 utenbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":127560,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri S.","email":"utenbrink@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":false,"id":810238,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hutchinson, Deborah 0000-0002-2544-5466 dhutchinson@usgs.gov","orcid":"https://orcid.org/0000-0002-2544-5466","contributorId":174836,"corporation":false,"usgs":true,"family":"Hutchinson","given":"Deborah","email":"dhutchinson@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":810239,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mountain, G.S. 0000-0001-5221-0278","orcid":"https://orcid.org/0000-0001-5221-0278","contributorId":250705,"corporation":false,"usgs":false,"family":"Mountain","given":"G.S.","affiliations":[{"id":50229,"text":"Department of Earth and Planetary Sciences, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway, New Jersey","active":true,"usgs":false}],"preferred":false,"id":810240,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schattner, U. 0000-0002-4453-4552","orcid":"https://orcid.org/0000-0002-4453-4552","contributorId":174637,"corporation":false,"usgs":false,"family":"Schattner","given":"U.","affiliations":[{"id":27488,"text":"Dr. Mosses Straus Dept of Marine Geosciences, Leon H. Charney School of Marine Sciences, University of Haifa","active":true,"usgs":false}],"preferred":false,"id":810241,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260189,"text":"70260189 - 2020 - Evidence for primitive magma storage and eruption following prolonged equilibration in thickened crust","interactions":[],"lastModifiedDate":"2024-10-30T13:48:22.975458","indexId":"70260189","displayToPublicDate":"2020-10-09T08:38:46","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":"Evidence for primitive magma storage and eruption following prolonged equilibration in thickened crust","docAbstract":"In continental arcs, the exposure of primitive eruptive products at the surface is typically a result of rapid magmatic transfer through the crust. As a result, the initially primitive magma experiences minimal crustal residence and thus insignificant differentiation towards more evolved products. This rapid transfer of primitive magma through thickened crust is commonly recorded from smaller, monogenetic cinder cones. Manantial Pelado (35.5° S) is a long-lived stratocone in the Southern Andean Volcanic Zone (SVZ) overlying thick continental crust (45–50 km) that produces almost exclusively mafic material. As Manantial Pelado is surrounded by extensive silicic volcanism, the study of its mafic exposure as a stratocone can be used to further understand magmatic origins of long-lived volcanic systems. Our study uses textural, geochemical, and geochronological data from lavas collected from Manantial Pelado to characterize its magmatic petrogenesis, assess the primitive nature, and explain processes in the crust within the SVZ. A geologic description of the volcano reveals a mostly monotonous eruptive history of basaltic andesites that are now accessible through glacially carved valleys. New 40Ar/39Ar dating constrains most of the volcano’s cone constructing phase to last from ~ 220 to 190 ka. At ~ 30 ka, small-volume activity and different petrography of more intermediate magmas were present reflecting a change in the volcano’s character. A combination of the whole-rock and mineral-scale data reveals that basaltic andesites at Manantial Pelado are among the most primitive magmas in the thickened crust of the SVZ. Evidence for this primitive signature consists of textural and zonation patterns in olivine, the presence of Cr-spinel in olivine cores, and elevated Fo and Ni content within olivine cores. This data combined with elemental diffusion modeling provides evidence for a primitive signature for these lavas. Intermediate Fo olivines with uniform core compositions (Fo80–84) suggest that basaltic andesites reside in the crust in quasi-closed system environments for extended storage prior to eruption (~ 25–6000 years). Diffusive equilibration in those intermediate Fo olivines masks the primitive nature of the magmas. These results suggest that mafic magmas can have a protracted storage history in the crust that does not significantly alter their primitive bulk composition before reaching the surface. We argue that these are important processes in understanding the magmatic origin of long-lived systems and the presence of compositionally homogenous olivines at intermediate Fo content may represent cryptic evidence for recharge with primitive magmas that experienced prolonged crustal storage.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-020-01406-3","usgsCitation":"Winslow, H., Ruprecht, P., Stelten, M.E., and Amigo, A., 2020, Evidence for primitive magma storage and eruption following prolonged equilibration in thickened crust: Bulletin of Volcanology, v. 82, 69, 24 p., https://doi.org/10.1007/s00445-020-01406-3.","productDescription":"69, 24 p.","ipdsId":"IP-120597","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":463429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","otherGeospatial":"Manantial Pelado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.12460848108275,\n -35.48782312280931\n ],\n [\n -71.12460848108275,\n -35.86478726958381\n ],\n [\n -70.51553281855436,\n -35.86478726958381\n ],\n [\n -70.51553281855436,\n -35.48782312280931\n ],\n [\n -71.12460848108275,\n -35.48782312280931\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2020-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Winslow, Heather 0000-0001-6664-6339","orcid":"https://orcid.org/0000-0001-6664-6339","contributorId":345733,"corporation":false,"usgs":false,"family":"Winslow","given":"Heather","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":917374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruprecht, Philipp","contributorId":199796,"corporation":false,"usgs":false,"family":"Ruprecht","given":"Philipp","email":"","affiliations":[{"id":7135,"text":"Lamont Doherty Earth Observatory, Columbia University, Palisades, NY","active":true,"usgs":false},{"id":35453,"text":"University of Leeds, UK","active":true,"usgs":false}],"preferred":false,"id":917375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stelten, Mark E. 0000-0002-5294-3161 mstelten@usgs.gov","orcid":"https://orcid.org/0000-0002-5294-3161","contributorId":145923,"corporation":false,"usgs":true,"family":"Stelten","given":"Mark","email":"mstelten@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Amigo, Alvaro","contributorId":173513,"corporation":false,"usgs":false,"family":"Amigo","given":"Alvaro","affiliations":[{"id":27236,"text":"SERNAGEOMIN","active":true,"usgs":false}],"preferred":false,"id":917377,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215356,"text":"70215356 - 2020 - Determining habitat limitations of Maumee River walleye production to western Lake Erie fish stocks: Documenting a spawning ground barrier","interactions":[],"lastModifiedDate":"2020-11-30T16:39:00.408384","indexId":"70215356","displayToPublicDate":"2020-10-09T08:22:22","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":"Determining habitat limitations of Maumee River walleye production to western Lake Erie fish stocks: Documenting a spawning ground barrier","docAbstract":"Tributaries provide spawning habitat for three of four major sub-stocks of Lake Erie walleye (Sander vitreus). Despite anthropogenic degradation and the extirpation of other potamodromous species, the Maumee River, Ohio, USA continues to support one of the largest fish migrations in the Laurentian Great Lakes. To determine if spawning habitat availability and quality could limit production of Maumee River walleye, two habitat suitability models were created for the lower 51 km of the Maumee River and the distribution and numbers of walleye eggs deposited in a 25 km stretch of river were assessed. Walleye eggs were collected using a diaphragm pump at 7 and 10 sites from March/April to May 2014 and 2015. The habitat suitability models showed that <3% of the river yielded ‘good’ walleye spawning habitat and 11–38% yielded ‘moderate’ walleye spawning habitat, depending on the model. However, a large set of rapids at river kilometer 28 and more than five river kilometers of less suitable habitat separated areas of ‘good’ habitat. The rapids may present a migratory barrier for many spawning walleye, as modeled water velocities exceed maximum estimated walleye swim speeds 71–100% of days during pre-spawn migration and spawning during the study period. In both study years, there was a sharp decline in mean egg numbers from spawning sites downstream of the rapids (439.7 eggs/2 min tow ± 990.6 SD) to upstream sites (5.9 eggs/2 min tow ± 19.4 SD). Physical barriers like rapids may reduce spawning habitat connectivity and could limit walleye production in the Maumee River.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.08.022","usgsCitation":"Schmidt, B., Tucker, T., Collier, J., Mayer, C., Roseman, E., Stott, W., and Pritt, J., 2020, Determining habitat limitations of Maumee River walleye production to western Lake Erie fish stocks: Documenting a spawning ground barrier: Journal of Great Lakes Research, v. 46, no. 6, p. 1661-1673, https://doi.org/10.1016/j.jglr.2020.08.022.","productDescription":"13 p.","startPage":"1661","endPage":"1673","ipdsId":"IP-115670","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":436758,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9214IQU","text":"USGS data release","linkHelpText":"Walleye (Sander vitreus) egg deposition and spawning habitat suitability in the Maumee River, OH (2014-2015)"},{"id":379460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Maumee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.36975097656249,\n 41.68111756290652\n ],\n [\n -83.47412109375,\n 41.75492216766298\n ],\n [\n -84.232177734375,\n 41.47977575214487\n ],\n [\n -84.638671875,\n 41.31082388091818\n ],\n [\n -84.5947265625,\n 41.08763212467916\n ],\n [\n -83.81469726562499,\n 41.33970040774419\n ],\n [\n -83.5015869140625,\n 41.51269075845857\n ],\n [\n -83.36975097656249,\n 41.68111756290652\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schmidt, Brian 0000-0001-7067-6194","orcid":"https://orcid.org/0000-0001-7067-6194","contributorId":242674,"corporation":false,"usgs":false,"family":"Schmidt","given":"Brian","affiliations":[{"id":13589,"text":"Ohio DNR","active":true,"usgs":false}],"preferred":false,"id":801850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, Taaja 0000-0003-1534-4677","orcid":"https://orcid.org/0000-0003-1534-4677","contributorId":217908,"corporation":false,"usgs":true,"family":"Tucker","given":"Taaja","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":801851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collier, Jessica","contributorId":242677,"corporation":false,"usgs":false,"family":"Collier","given":"Jessica","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":801852,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mayer, Christine","contributorId":237769,"corporation":false,"usgs":false,"family":"Mayer","given":"Christine","affiliations":[{"id":47604,"text":"University of Toledo, Lake Erie Center","active":true,"usgs":false}],"preferred":false,"id":801853,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":801854,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stott, Wendylee 0000-0002-5252-4901 wstott@usgs.gov","orcid":"https://orcid.org/0000-0002-5252-4901","contributorId":191249,"corporation":false,"usgs":true,"family":"Stott","given":"Wendylee","email":"wstott@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":801855,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pritt, Jeremy J.","contributorId":138591,"corporation":false,"usgs":false,"family":"Pritt","given":"Jeremy J.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":801856,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216162,"text":"70216162 - 2020 - Imaging the tectonic grain of the Northern Cordillera orogen using Transportable Array receiver functions","interactions":[],"lastModifiedDate":"2020-11-09T21:26:07.128755","indexId":"70216162","displayToPublicDate":"2020-10-09T07:36:34","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":"Imaging the tectonic grain of the Northern Cordillera orogen using Transportable Array receiver functions","docAbstract":"Azimuthal variations in receiver function conversions can image lithospheric structural contrasts and anisotropic fabrics that together compose tectonic grain. We apply this method to data from EarthScope Transportable Array in Alaska and additional stations across the northern Cordillera. The best‐resolved quantities are the strike and depth of dipping fabric contrasts or interfaces. We find a strong geographic gradient in such anomalies, with large amplitudes extending inboard from the present‐day subduction margin, the Aleutian arc, and an influence of flat‐slab subduction of the Yakutat microplate north of the Denali fault. An east–west band across interior Alaska shows low‐amplitude crustal anomalies. Anomaly amplitudes correlate with structural intensity (density of aligned geological elements), but are the highest in areas of strong Cenozoic deformation, raising the question of an influence of current stress state. Imaged subsurface strikes show alignment with surface structures. We see concentric strikes around arc volcanoes implying dipping magmatic structures and fabric into the middle crust. Regions with present‐day weaker deformation show lower anomaly amplitudes but structurally aligned strikes, suggesting pre‐Cenozoic fabrics may have been overprinted or otherwise modified. We observe general coherence of the signal across the brittle‐plastic transition. Imaged crustal fabrics are aligned with major faults and shear zones, whereas intrafault blocks show imaged strikes both parallel to and at high angles to major block‐bounding faults. High‐angle strikes are subparallel to neotectonic deformation, seismicity, fault lineaments, and prominent metallogenic belts, possibly due to overprinting and/or co‐evolution with fault‐parallel fabrics. We suggest that the underlying tectonic grain in the northern Cordillera is broadly distributed rather than strongly localized. Receiver functions thus reveal key information about the nature and continuity of tectonic fabrics at depth and can provide unique insights into the deformation history and distribution of regional strain in complex orogenic belts.
The Portland-Vancouver-Hillsboro Metropolitan Area (metro area) has great scenic, natural, and cultural resources and is the major economic hub of Oregon. The metro area is subject to a variety of geologic hazards. Underthrusting of the oceanic plate along the Cascadia plate boundary fault, or megathrust, deforms the leading edge of North America and produces earthquakes on the megathrust and in the overlying plate. Rising magma from the deeper parts of the subduction zone produces active volcanoes that form the Cascades Arc, including Mount Hood and Mount St. Helens visible from Portland. Both volcanism and strong ground-shaking from earthquakes have impacted the metro area, most recently in the 1980 eruptions of Mount St. Helens and the 1993 magnitude (M) 5.7 Scotts Mills earthquake. Great offshore earthquakes as large as M 9 on the Cascadia megathrust have shaken the metro area every 500 years or so, most recently in 1700. Giant floods have inundated the metro area, from the ice age Missoula floods about 20,000 to 15,000 years ago to the flood generated by collapse of the Bridge of the Gods landslide dam on the Columbia River around 1421–1447 A.D.
Geologic resources of the metro area include the southern part of the Mist Natural Gas Storage Field in the northwest corner of the map area, the Columbia South Shore Well Field aquifer in the Portland Basin, the Columbia River Basalt aquifer of the Tualatin Basin, and the Tualatin Basin Aquifer Storage and Recovery projects. The metro area includes several well-known American Viticultural Areas in the western part of the map area and numerous transportation, electrical transmission, and pipeline corridors.
We created this map to provide a uniform, modern geologic database for the greater Portland metro area to better understand its tectonic setting, active faults, volcanoes, landslide hazards, and distribution of geologic materials and resources. Information in this database will be used to improve seismic hazard and resource assessments in this economically important region.
NOTE: The sheet 1 map was divided into two parts—sheet 1 (north) and sheet 1 (south)—to facilitate printing and plotting the map.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3443","collaboration":"Prepared in Cooperation with Oregon Department of Geology and Mineral Industries and Washington Geological Survey","usgsCitation":"Wells, R.E., Haugerud, R.A., Niem, A.R., Niem, W.A., Ma, L., Evarts, R.C., O’Connor, J.E., Madin, I.P., Sherrod, D.R., Beeson, M.H., Tolan, T.L., Wheeler, K.L., Hanson, W.B., and Sawlan, M.G., 2020, Geologic map of the greater Portland metropolitan area and surrounding region, Oregon and Washington: U.S. Geological Survey Scientific Investigations Map 3443, pamphlet 55 p., 2 sheets, scale 1:63,360, https://doi.org/10.3133/sim3443.","productDescription":"Pamphlet: iv, 55 p.; 2 Sheets: 58.43 x 60.16 inches and 38.76 x 30.86 inches; Table 3; Database; Metadata; Read Me","numberOfPages":"55","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081424","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":396997,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_sheet1_south.pdf","text":"Sheet 1 South","size":"55 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- NOTE: The sheet 1 map was divided into two parts—sheet 1 (north) and sheet 1 (south)—to facilitate printing and plotting the map."},{"id":396996,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_sheet1_north.pdf","text":"Sheet 1 North","size":"55 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- NOTE: The sheet 1 map was divided into two parts—sheet 1 (north) and sheet 1 (south)—to facilitate printing and plotting the map."},{"id":376987,"rank":8,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3443/database","text":"Database directory"},{"id":376984,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3443/metadata","text":"Metadata directory"},{"id":376983,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_table3.xlsx","text":"Table 3","size":"110 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":376982,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_sheet2.pdf","text":"Sheet 2","size":"13 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":376981,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_sheet1.pdf","text":"Sheet 1","size":"80 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":376980,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_readme.txt","size":"5 KB","linkFileType":{"id":2,"text":"txt"}},{"id":376979,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3443/sim3443_pamphlet.pdf","text":"Pamphlet","size":"28 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":376953,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3443/covrthb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Greater Portland metropolitan area and surrounding region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.20617675781251,\n 44.95702412512118\n ],\n [\n -122.0855712890625,\n 44.95702412512118\n ],\n [\n -122.0855712890625,\n 46.145588688591964\n ],\n [\n -123.20617675781251,\n 46.145588688591964\n ],\n [\n -123.20617675781251,\n 44.95702412512118\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
The state of an ecosystem is governed by dynamic biotic and abiotic processes, which can only be partially observed. Costs associated with measuring each component limit the feasibility of comprehensive assessments of target ecosystems. Instead, indicator species are recommended as a surrogate index. While this is an attractive concept, indicator species have rarely proven to be an effective tool for monitoring ecosystems and informing management decisions. One deficiency in the existing theoretical development of indicator species may be overcome with the incorporation of latent (i.e. unobservable) states. Advancements in quantitative ecological models allow for latent‐state models to be tested empirically, facilitating the robust evaluation and practical use of indicator species for ecosystem science and management. Here, we extend the existing conceptual models of indicator species to include a direct relationship between an indicator species, ecosystem change drivers and latent processes and variables. Our approach includes explicit consideration of important estimation uncertainty and narrows the range of values a latent variable may take by relating it to measurable attribute(s) of an indicator species. We demonstrate the utility of this approach by relating a commonly cited indicator species, the red‐backed salamander Plethodon cinereus, to a typical latent process of interest – ecosystem health.
The U.S. Geological Survey, in cooperation with the U.S. Air Force Academy (USAFA), carried out bathymetric and topographic surveys to characterize the volume of Deadmans Lake, Golf Course Reservoir 9, Ice Lake, Kettle Lakes 1–3, and Non-Potable Reservoirs 1–4 at the U.S. Air Force Academy, Colorado. Bathymetric maps of each lake and reservoir are presented with figures of the elevation-volume curves. The bathymetric surveys were carried out from October 15, 2019, to December 12, 2019, using a manually operated, boat-mounted, single-beam echo sounder integrated with a Real-Time Kinematic Global Navigation Satellite Systems receiver. Topographic surveys were carried out during the same time period using Real-Time Kinematic Global Navigation Satellite System to collect elevation data at and above the water surface and up to the elevation of the dam or spillway at the time of the surveys. The topographic and bathymetric datasets were imported into Esri ArcMap 10.7.1. The combined survey points were then interpolated into digital elevation models, which were used to determine lake or reservoir volumes that correspond to water-surface elevations between the lakebed and the approximate top of the dam or spillway.
This report provides an updated characterization of storage capacity and improved understanding of present (2019) water capacity in the lakes and reservoirs at the USAFA. In addition, these surveys serve as a baseline that could be compared with future surveys of the lakes and reservoirs. The differences in these and future surveys could then be used to determine sedimentation infill rates and provide estimates of the lifespan of the lakes and reservoirs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3463","collaboration":"Prepared in cooperation with the U.S. Air Force Academy","usgsCitation":"Kohn, M.S., and Hempel, L.A., 2020, Bathymetry of Deadmans Lake, Golf Course Reservoir 9, Ice Lake, Kettle Lakes 1–3, and Non-Potable Reservoirs 1–4 at the U.S. Air Force Academy, Colorado, 2019: U.S. Geological Survey Scientific Investigations Map 3463, pamphlet 12 p., https://doi.org/10.3133/sim3463.","productDescription":"Pamphlet: vi, 12 p.; 1 Sheet: 36.00 x 32.00 inches; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-114390","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":378914,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3463/coverthb.jpg"},{"id":378915,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3463/sim3463_map.pdf","text":"Map","size":"9.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3463"},{"id":378917,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LTH0RO","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Survey and Bathymetric Data of Deadmans Lake, Golf Course Reservoir 9, Ice Lake, Kettle Lakes 1-3, and Non-Potable Reservoirs 1-4 at the U.S. Air Force Academy, Colorado, 2019 (ver. 1.1, June 2020)"},{"id":378916,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3463/sim3463_pamphlet.pdf","text":"Pamphlet","size":"1.17 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Colorado","city":"Colorado Springs","otherGeospatial":"U.S. Airforce Academy","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.91188049316406,\n 38.91561302513129\n ],\n [\n -104.77867126464842,\n 38.93163900447185\n ],\n [\n -104.8267364501953,\n 39.03731965210478\n ],\n [\n -104.92767333984374,\n 39.03731965210478\n ],\n [\n -104.91188049316406,\n 38.91561302513129\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
To characterize eruption activity of the iconic Old Faithful Geyser in Yellowstone National Park over past centuries, we obtained 41 new radiocarbon dates of mineralized wood preserved in the mound of silica that precipitated from erupted waters. Trees do not grow on active geyser mounds, implying that trees grew on the Old Faithful Geyser mound during a protracted period of eruption quiescence. Rooted stumps and root crowns located on higher parts of the mound are evidence that at the time of tree growth, the geyser mound closely resembled its current appearance. The range of calibrated radiocarbon dates (1233–1362 CE) is coincident with a series of severe multidecadal regional droughts toward the end of the Medieval Climate Anomaly, prior to the onset of the Little Ice Age. Climate models project increasingly severe droughts by mid‐21st century, suggesting that geyser eruptions could become less frequent or completely cease.
The endangered Silver Chub (Macrhybopsis storeriana, Kirtland 1844) is native to North America and primarily riverine, with the only known large‐lake population in Lake Erie. Once a major component of the Lake Erie fish community, it declined and became nearly extirpated in the mid‐1900s. Recent collections in western Lake Erie suggest that Silver Chub may be able to recover, but their habitat and distribution are poorly known. A recent work showed an extensive area of western Lake Erie with the potential to support large numbers of Silver Chub, but was based on a geographically limited dataset. We developed a neural network‐based species distribution model for the Silver Chub in western Lake Erie, improved by new synoptic data and using habitat variables resistant to anthropogenic activities. The Potential model predictions were compared with a model that included anthropogenic‐sensitive variables. The Potential model used 10 habitat variables and performed well, explaining > 99% of data variation and had generally low error rates. Predictions indicated that a large area of the waters approximately 2–9 m deep contained Appropriate habitat and the highest abundances should be supported by habitat in a wide arc through the western end of the basin. The model indicated that Appropriate Silver Chub habitat was associated with relatively deep water, near coastal wetlands, where effective fetch is less than average. Disturbance model predictions were similar, but predicted poorer Silver Chub habitat in more areas than that predicted by the Potential model. Our Potential model reveals Appropriate habitat conditions for Silver Chub and its spatial distribution, indicating that extensive areas of western Lake Erie could support Silver Chub. Comparisons with Disturbance model predictions demonstrate that Potential model predictions may be used in conjunction with analyses of degrading conditions in the system to better conserve and manage for this endangered species.
Evapotranspiration (ET) is needed in a range of applications in hydrology, climatology, ecology, and agriculture. Remote sensing-based estimation is the only viable and economical method for ET estimation over large areas. The current Landsat satellites provide images every 16 days limiting the ability to capture biophysical changes affecting ET. Thus, we explored the potential integration of Landsat 8 and Sentinel-2 data for estimating ET using a surface energy balance model. The results indicate the proposed Landsat-Sentinel data fusion approach substantially reduced relative errors from 48% to 10% on area-wide and from 49% to 17% on pixel-wide compared to linear interpolation between two Landsat images. The proposed approach had a better agreement with expected actual ET maps across high-vegetation conditions than in low-vegetation conditions. The finer temporal resolution and better accuracy of ET maps based on Landsat-Sentinel integration is of great importance in managing limited water resources.
In 2018, the U.S. Geological Survey (USGS) published an Open-File Report (Tracey and others, 2018) presenting a Bayesian habitat selection model for golden eagles (Aquila chrysaetos) in San Diego County, California. The model used telemetry data to examine the effects of urban development, exurban development, and topography (characterized by a topographic position index and a vector ruggedness measure, TPI and VRM respectively) on golden eagle habitat selection probability. Based on figures 3 and 6 of Tracey and others (2018), we received inquiries from cooperators (U.S. Fish and Wildlife Service and California Department of Fish and Wildlife) about how the probability of eagle use declines with decreasing distance to the urban edge. Here, we clarify our results by addressing that question.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201110","collaboration":"Prepared in cooperation with San Diego Association of Governments, U.S. Fish and Wildlife Service, Bureau of Land Management, and California Department of Fish and Wildlife","usgsCitation":"Tracey, J.A., Madden, M.C., Bloom, P.H., and Fisher, R.N., 2020, A clarification on the effects of urbanization on Golden Eagle (Aquila chrysaetos) habitat selection: U.S. Geological Survey Open-File Report 2020–1110, 7 p., https://doi.org/10.3133/ofr20201110.","productDescription":"iv, 7 p.","numberOfPages":"7","onlineOnly":"Y","ipdsId":"IP-121710","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":379081,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1110/covrthb.jpg"},{"id":379082,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1110/ofr20201110.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":379083,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181067","text":"Open-File Report 2018-1067","linkHelpText":"- Golden eagle (Aquila chrysaetos) habitat selection as a function of land use and terrain, San Diego County, California"}],"contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
We infer a history of three great megathrust earthquakes during the past 2000 years at the Nehalem River estuary based on the lateral extent of sharp (≤3 mm) peat-mud stratigraphic contacts in cores and outcrops, coseismic subsidence as interpreted from fossil diatom assemblages and reconstructed with foraminiferal assemblages using a Bayesian transfer function, and regional correlation of 14C-modeled ages for the times of subsidence. A subsidence contact from 1700 CE (contact A), sometimes overlain by tsunami-deposited sand, can be traced over distances of 7 km. Contacts B and D, which record subsidence during two earlier megathrust earthquakes, are much less extensive but are traced across a 700-m by 270-m tidal marsh. Although some other Cascadia studies report evidence for an earthquake between contacts B and D, our lack of extensive evidence for such an earthquake may result from the complexities of preserving identifiable evidence of it in the rapidly shifting shoreline environments of the lower river and bay. Ages (95% intervals) and subsidence for contacts are: A, 1700 CE (1.1 ± 0.5 m); B, 942–764 cal a BP (0.7 ± 0.4 m and 1.0 m ± 0.4 m); and D, 1568–1361 cal a BP (1.0 m ± 0.4 m). Comparisons of contact subsidence and the degree of overlap of their modeled ages with ages for other Cascadia sites are consistent with megathrust ruptures many hundreds of kilometers long. But these data cannot conclusively distinguish among different types or lengths of ruptures recorded by the three great earthquake contacts at the Nehalem River estuary.
","language":"English","publisher":"Ubiquity Press","doi":"10.5334/oq.70","usgsCitation":"Nelson, A.R., Hawkes, A.D., Sawai, Y., Engelhart, S.E., Witter, R., Grant-Walter, W.C., Bradley, L., Dura, T., Cahill, N., and Horton, B.P., 2020, Identifying the greatest earthquakes of the past 2000 years at the Nehalem River Estuary, Northern Oregon Coast, USA: Open Quaternary, v. 6, no. 2, p. 1-30, https://doi.org/10.5334/oq.70.","productDescription":"30 p.","startPage":"1","endPage":"30","ipdsId":"IP-112611","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":455108,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5334/oq.70","text":"Publisher Index Page"},{"id":379088,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","state":"California, Oregon, Washington, British Columbia","otherGeospatial":"Cascadia subduction zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.81591796875,\n 40.64730356252251\n ],\n [\n -123.77197265625,\n 43.723474896114794\n ],\n [\n -123.662109375,\n 45.82879925192134\n ],\n [\n -123.46435546875,\n 47.84265762816538\n ],\n [\n -122.93701171874999,\n 49.1242192485914\n ],\n [\n -126.7822265625,\n 51.0275763378024\n ],\n [\n -128.56201171875,\n 50.86144411058924\n ],\n [\n -127.28759765624999,\n 49.31079887964633\n ],\n [\n -124.45312499999999,\n 46.619261036171515\n ],\n [\n -124.67285156250001,\n 42.66628070564928\n ],\n [\n -123.81591796875,\n 40.64730356252251\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nelson, Alan R. 0000-0001-7117-7098 anelson@usgs.gov","orcid":"https://orcid.org/0000-0001-7117-7098","contributorId":812,"corporation":false,"usgs":true,"family":"Nelson","given":"Alan","email":"anelson@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":800608,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawkes, Andrea D.","contributorId":192811,"corporation":false,"usgs":false,"family":"Hawkes","given":"Andrea","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":800555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sawai, Yuki","contributorId":127509,"corporation":false,"usgs":false,"family":"Sawai","given":"Yuki","email":"","affiliations":[{"id":6981,"text":"National Institute of Advanced Industrial Science and Technology, AIST, Japan","active":true,"usgs":false}],"preferred":false,"id":800556,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engelhart, Simon E.","contributorId":60104,"corporation":false,"usgs":false,"family":"Engelhart","given":"Simon","email":"","middleInitial":"E.","affiliations":[{"id":6923,"text":"University of Rhode Island, Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":800557,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","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":800558,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grant-Walter, Wendy C.","contributorId":242632,"corporation":false,"usgs":false,"family":"Grant-Walter","given":"Wendy","email":"","middleInitial":"C.","affiliations":[{"id":48492,"text":"P.O. Box 800, Harwich Port, MA 02646 USA","active":true,"usgs":false}],"preferred":false,"id":800559,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bradley, Lee-Ann","contributorId":193406,"corporation":false,"usgs":false,"family":"Bradley","given":"Lee-Ann","affiliations":[],"preferred":false,"id":800560,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dura, Tina","contributorId":195530,"corporation":false,"usgs":false,"family":"Dura","given":"Tina","email":"","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":800561,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cahill, Niamh","contributorId":150754,"corporation":false,"usgs":false,"family":"Cahill","given":"Niamh","email":"","affiliations":[{"id":18091,"text":"University College Dublin","active":true,"usgs":false},{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":800562,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Horton, Benajamin P.","contributorId":192918,"corporation":false,"usgs":false,"family":"Horton","given":"Benajamin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":800563,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70215443,"text":"70215443 - 2020 - The eruptive history, magmatic evolution, and influence of glacial ice at long-lived Akutan volcano, eastern Aleutian Islands, Alaska, USA","interactions":[],"lastModifiedDate":"2020-10-20T13:57:30.629194","indexId":"70215443","displayToPublicDate":"2020-10-06T08:49:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"The eruptive history, magmatic evolution, and influence of glacial ice at long-lived Akutan volcano, eastern Aleutian Islands, Alaska, USA","docAbstract":"New 40Ar/39Ar and whole-rock geochemical data are used to develop a detailed eruptive chronology for Akutan volcano, Akutan Island, Alaska, USA, in the eastern Aleutian island arc. Akutan Island (166°W, 54.1°N) is the site of long-lived volcanism and the entire island comprises volcanic rocks as old as 3.3 Ma. Our current study is on the 225 km2 western half of the island, where our results show that the focus of volcanism has shifted over the last ∼700 k.y., and that on occasion, multiple volcanic centers have been active over the same period, including within the Holocene. Incremental heating experiments resulted in 56 40Ar/39Ar plateau ages and span 2.3 Ma to 9.2 ka.
Eruptive products of all units are primarily tholeiitic and medium-K, and range from basalt to dacite. Rare calc-alkaline lavas show evidence suggesting their formation via mixing of mafic and evolved magmas, not via crystallization-derived differentiation through the calc-alkaline trend. Earliest lavas are broadly dispersed and are almost exclusively mafic with high and variable La/Yb ratios that are likely the result of low degrees of partial mantle melting. Holocene lavas all fall along a single tholeiitic, basalt-to-dacite evolutionary trend and have among the lowest La/Yb ratios, which favors higher degrees of mantle melting and is consistent with the increased magma flux during this time. A suite of xenoliths, spanning a wide range of compositions, are found in the deposits of the 1.6 ka caldera-forming eruption. They are interpreted to represent completely crystallized liquids or the crystal residuum from tholeiitic fractional crystallization of the active Akutan magma system.
The new geochronologic and geochemical data are used along with existing geodetic and seismic interpretations from the island to develop a conceptual model of the active Akutan magma system. Collectively, these data are consistent with hot, dry magmas that are likely stored at 5−10 km depth prior to eruption. The prolonged eruptive activity at Akutan has also allowed us to evaluate patterns in lava-ice interactions through time as our new data and observations suggest that the influence of glaciation on eruptive activity, and possible magma composition, is more pronounced at Akutan than has been observed for other well-studied Aleutian volcanoes to the west.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35667.1","usgsCitation":"Coombs, M.L., and Brian Jicha, 2020, The eruptive history, magmatic evolution, and influence of glacial ice at long-lived Akutan volcano, eastern Aleutian Islands, Alaska, USA: GSA Bulletin, 29 p., https://doi.org/10.1130/B35667.1.","productDescription":"29 p.","ipdsId":"IP-116599","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":379541,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -169.62890625,\n 50.62507306341435\n ],\n [\n -152.9296875,\n 50.62507306341435\n ],\n [\n -152.9296875,\n 58.90464570302001\n ],\n [\n -169.62890625,\n 58.90464570302001\n ],\n [\n -169.62890625,\n 50.62507306341435\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2020-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Coombs, Michelle L. 0000-0002-6002-6806 mcoombs@usgs.gov","orcid":"https://orcid.org/0000-0002-6002-6806","contributorId":2809,"corporation":false,"usgs":true,"family":"Coombs","given":"Michelle","email":"mcoombs@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":802217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brian Jicha","contributorId":243421,"corporation":false,"usgs":false,"family":"Brian Jicha","affiliations":[{"id":34113,"text":"University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":802218,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70215375,"text":"70215375 - 2020 - Water balance as an indicator of natural resource condition: Case studies from Great Sand Dunes National Park and Preserve","interactions":[],"lastModifiedDate":"2020-10-16T12:56:39.896421","indexId":"70215375","displayToPublicDate":"2020-10-06T07:53:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Water balance as an indicator of natural resource condition: Case studies from Great Sand Dunes National Park and Preserve","docAbstract":"Managing climate impacts to natural resources in protected areas can be hampered by lack of monitoring data, poor understanding of natural resource responses to climate, or lack of timely condition assessments that can inform management actions. Here we demonstrate the utility of water balance as a tool for understanding natural resource responses to climate by developing case studies focused on stream flow, vegetation production, and wildfire ignition at Great Sand Dunes National Park and Preserve (GSDNP), U.S.A. The efficacy of water balance to predict these responses stems from the explicit integration of climate with site conditions that modify the effects of climate. This in turn results in estimates of water availability, water use, and water need that are proximal drivers of aquatic and terrestrial natural resource conditions. The water balance model successfully forecasted stream flow (r2 = 0.69, P < 0.001); determined the critical water needs for maintaining annual vegetation production in different vegetation types spanning a large environmental gradient (r2 = 0.18–0.71); and predicted proportion of historic wildfire ignitions in forest (r2 = 0.96–0.99) and non-forest (r2 = 0.96–0.97) vegetation types. Collectively, these case studies demonstrate practical approaches to translate climate data into assessments of natural resource condition that inform long-term planning and near-term strategic actions needed for conservation of protected areas.