Opportunities for growth and survival of aquatic organisms are spatially and temporally variable as habitat conditions across watersheds respond to interacting climatic, geomorphic, and hydrologic conditions. As conservation efforts often focus on identifying and protecting critical habitats, it is important to understand how this spatial and temporal variation in habitat quality affects the production dynamics of populations. Here, we use microchemical records preserved in otoliths to reconstruct juvenile habitat‐use by sockeye salmon that survived to spawn in a single population on the Alaska Peninsula. Successful individuals demonstrated a diverse array of juvenile behavioral strategies both within and among years. Importantly, the dominant juvenile behavioral strategy used by successful individuals changed among years, suggesting shifts in the relative benefits of different rearing habitats. The growth benefits of remaining in a more productive rearing lake were greatest in warm years indicating environmental influence on relative habitat quality. However, we found no strong relationship between the amount of growth accumulated in the productive rearing lake and overall population productivity across years. These results highlight the dynamic nature of habitat conditions and the beneficial effect of maintaining connectivity between diverse habitats for population productivity. When short‐term studies are used to demonstrate the relative values of different habitats to species of conservation concern, there is a distinct risk of under‐valuing habitats that may be critically important under alternative environmental conditions. In particular, land‐use decisions that reduce the range of habitat options available to species may erode a population’s ability to withstand environmental change over the long term.
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":70215394,"text":"70215394 - 2020 - Utica shale play oil and gas brines: Geochemistry and factors influencing wastewater management","interactions":[],"lastModifiedDate":"2020-11-13T20:26:03.750261","indexId":"70215394","displayToPublicDate":"2020-10-14T10:27:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Utica shale play oil and gas brines: Geochemistry and factors influencing wastewater management","docAbstract":"The Utica and Marcellus Shale Plays in the Appalachian Basin are the fourth and first largest natural gas producing plays in the United States, respectively. Hydrocarbon production generates large volumes of brine (“produced water”) that must be disposed of, treated, or reused. Though Marcellus brines have been studied extensively, there are few studies from the Utica Shale Play. This study presents new brine chemical analyses from 16 Utica Shale Play wells in Ohio and Pennsylvania. Results from Na–Cl–Br systematics and stable and radiogenic isotopes suggest that the Utica Shale Play brines are likely residual pore water concentrated beyond halite saturation during the formation of the Ordovician Beekmantown evaporative sequence. The narrow range of chemistry for the Utica Shale Play produced waters (e.g., total dissolved solids = 214–283 g/L) over both time and space implies a consistent composition for disposal and reuse planning. The amount of salt produced annually from the Utica Shale Play is equivalent to 3.4% of the annual U.S. halite production. Utica Shale Play brines have radium activities 580 times the EPA maximum contaminant level and are supersaturated with respect to barite, indicating the potential for surface and aqueous radium hazards if not properly disposed of.
Land plays a critical role in both economic and environmental accounting. As an asset, it occupies a unique position at the intersection of the System of National Accounts (SNA), the System of Environmental-Economic Accounting Central Framework (SEEA-CF), and (as a spatial unit) SEEA Experimental Ecosystem Accounting (SEEA-EEA), making land a natural starting point for developing natural capital accounts more generally. We develop a pilot set of national and subnational land accounts for the United States that are consistent with the SEEA-CF and SNA principles, quantified in both physical and monetary terms. The physical accounts utilize detailed land use (National Land Use Database) and land cover (National Land Cover Database) datasets, which provide insights into how land cover in the U.S. is changing over time. To provide aggregate estimates of land values, we use a hedonic approach that exploits fine-grain microdata (“big data” from Zillow) that contains detailed information from hundreds of millions of property transactions and their corresponding physical characteristics covering much of the U.S. Methodologically, we show that it is feasible to produce monetary accounts for land that can be directly linked to and integrated with physical land cover/use. Overall, U.S. land cover has shown declines in forests, cropland, and pasture with increases in barren, scrub/shrub, and developed classes, which are particularly concentrated in the U.S. Southeast. Nominal land values in the U.S. fell about 28% ($7 trillion) from the boom to bust periods in the prior decade, albeit with substantial regional variation, and have subsequently experienced a nearly full recovery in recent years. We estimate private land in the contiguous 48 states to be worth approximately $25.1 trillion in 2016.
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
Close-kin mark–recapture (CKMR) is a powerful new method for the assessment of fish and wildlife population dynamics. Unlike traditional mark–recapture techniques, the use of kinship as an identifying mark is robust to many forms of capture heterogeneity including variation in gear efficiency and tagging-based effects such as loss and differential mortality. In addition, close-kin methods can be applied to a wider range of sampling designs than traditional methods (e.g., single-occasion surveys and lethal capture), can provide retrospective historical abundance estimates, and can produce survival estimates from as few as two sampling occasions. We evaluated the ability of CKMR to provide estimates of abundance and adult survival and then compared results to those from traditional mark–recapture. This analysis incorporated data from a three-year study of lake resident brook trout (Salvelinus fontinalis) where individuals were both physically (PIT) tagged and genotyped for 44 de novo developed microsatellites with high throughput sequencing. Traditional mark–recapture estimates were derived using Pollock’s Robust Design, relying upon three primary open sampling occasions and four secondary closed occasions. We found that close-kin methods produced contemporary estimates of adult abundance and survival that were similar to those produced by traditional mark–recapture in both magnitude and precision. Furthermore, CKMR provided abundance estimates for multiple years prior to sampling and, when restricted to data from a single year, still produced reliable abundance estimates for at least one and as many as three years. Retrospective abundance estimates corresponded with those from a separate historical two-sample mark–recapture dataset. This study provides support for the use of CKMR as a robust and sampling-efficient alternative to traditional mark–recapture methods of assessing population parameters.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3259","usgsCitation":"Marcy-Quay, B., Sethi, S., Therkildsen, N.O., and Kraft, C., 2020, Expanding the feasibility of fish and wildlife assessments with close-kin mark–recapture: Ecosphere, v. 11, no. 10, e3259, 14 p., https://doi.org/10.1002/ecs2.3259.","productDescription":"e3259, 14 p.","ipdsId":"IP-115671","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":455063,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3259","text":"Publisher Index Page"},{"id":395777,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Honnedaga Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.8139762878418,\n 43.5031182163569\n ],\n [\n -74.79663848876953,\n 43.514945729095245\n ],\n [\n -74.8029899597168,\n 43.52229007033024\n ],\n [\n -74.81002807617186,\n 43.52888676718944\n ],\n [\n -74.87508773803711,\n 43.53797160252612\n ],\n [\n -74.86993789672852,\n 43.530006889344705\n ],\n [\n -74.82891082763672,\n 43.52353478532976\n ],\n [\n -74.81552124023438,\n 43.51681301924114\n ],\n [\n -74.81809616088867,\n 43.50573291871012\n ],\n [\n -74.8139762878418,\n 43.5031182163569\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-10-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Marcy-Quay, Benjamin","contributorId":275703,"corporation":false,"usgs":false,"family":"Marcy-Quay","given":"Benjamin","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":834236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Therkildsen, Nina O.","contributorId":275704,"corporation":false,"usgs":false,"family":"Therkildsen","given":"Nina","email":"","middleInitial":"O.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":834237,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kraft, Clifford E.","contributorId":275705,"corporation":false,"usgs":false,"family":"Kraft","given":"Clifford E.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":834238,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215391,"text":"70215391 - 2020 - Dynamics of marsh-derived sediments in lagoon-type estuaries","interactions":[],"lastModifiedDate":"2020-11-30T16:17:53.439963","indexId":"70215391","displayToPublicDate":"2020-10-13T09:59:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics of marsh-derived sediments in lagoon-type estuaries","docAbstract":"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":70214669,"text":"sim3448 - 2020 - Surficial geologic map of the Spirit Mountain SE and part of the Spirit Mountain NE 7.5' quadrangles, Nevada and Arizona","interactions":[],"lastModifiedDate":"2025-09-08T18:48:50.963025","indexId":"sim3448","displayToPublicDate":"2020-10-13T08:37:14","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3448","displayTitle":"Surficial Geologic Map of the Spirit Mountain SE and part of the Spirit Mountain NE 7.5’ Quadrangles, Nevada and Arizona","title":"Surficial geologic map of the Spirit Mountain SE and part of the Spirit Mountain NE 7.5' quadrangles, Nevada and Arizona","docAbstract":"This geologic map includes a trove of stratigraphic and geomorphic information that chronicles the inception and evolution of the lower Colorado River. The map area is located near the south end of the Lake Mead National Recreation Area about 80 km (50 mi) downstream from Hoover Dam. It spans parts of northwestern Arizona and southern Nevada near the south end of Cottonwood Valley. The map includes the Spirit Mountain SE 7.5' quadrangle and the southern part of the Spirit Mountain NE 7.5' quadrangle. The map area contains well-exposed Neogene and Quaternary strata and associated geomorphic features that record and are critical in dating the arrival of the Colorado River in the early Pliocene and the subsequent history of the river and its landscape through the Holocene. The valley is bounded on the west by the Newberry Mountains (Nevada) and on the east by the Black Mountains (Arizona) and includes part of Lake Mohave, a reservoir created by the completion of Davis Dam in 1951. This map does not include the geology of the reservoir floor and focuses only on surficial deposits.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3448","collaboration":"Prepared in cooperation with Nevada Bureau of Mines and Geology; Arizona Geological Survey; University of Nevada, Las Vegas, Department of Geoscience; University of Oklahoma School of Geosciences; and National Park Service","usgsCitation":"House, P.K., Crow, R.S., Pearthree, P.A., Brock-Hon, A.L., Schwing, J., Thacker, J.O., and Gootee, B.F., 2020, Surficial geologic map of the Spirit Mountain SE and part of the Spirit Mountain NE 7.5' quadrangles, Nevada and Arizona: U.S. Geological Survey Scientific Investigations Map 3448, pamphlet 30 p., scale 1:24,000, https://doi.org/10.3133/sim3448.","productDescription":"Pamphlet: iv, 30 p.; 1 Sheet: 38.50 x 43.00 inches; Database; Metadata; Readme file","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-094912","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":379010,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3448/sim3448_metadata.xml","size":"18 KB","linkFileType":{"id":8,"text":"xml"},"description":"SIM 3448 metadata xml"},{"id":379009,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3448/sim3448_metadata.txt","size":"16 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3448 metadata txt"},{"id":379008,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3448/sim3448_pamphlet.pdf","text":"Pamphlet","size":"18.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3448 Pamphlet"},{"id":379007,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3448/sim3448.pdf","text":"Map","size":"22.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3448"},{"id":495225,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_110667.htm","linkFileType":{"id":5,"text":"html"}},{"id":379011,"rank":6,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3448/sim3448_readme.txt","size":"3 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3448 readme"},{"id":379012,"rank":7,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3448/sim3448_database.zip","size":"73.8 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3448 database (.zip)"},{"id":379006,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3448/coverthb.jpg"}],"country":"United States","state":"Arizona, Nevada","otherGeospatial":"Spirit Mountain quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.61212158203124,\n 35.21420969483077\n ],\n [\n -114.33197021484375,\n 35.21420969483077\n ],\n [\n -114.33197021484375,\n 35.641673184600585\n ],\n [\n -114.61212158203124,\n 35.641673184600585\n ],\n [\n -114.61212158203124,\n 35.21420969483077\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001-1600
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":70216568,"text":"70216568 - 2020 - Compounding effects of white pine blister rust, mountain pine beetle, and fire threaten four white pine species","interactions":[],"lastModifiedDate":"2020-11-25T14:59:30.635993","indexId":"70216568","displayToPublicDate":"2020-10-12T08:40:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Compounding effects of white pine blister rust, mountain pine beetle, and fire threaten four white pine species","docAbstract":"Invasive pathogens and bark beetles have caused precipitous declines of various tree species around the globe. Here, we characterized long‐term patterns of mountain pine beetle (Dendroctonus ponderosae; MPB) attacks and white pine blister rust, an infectious tree disease caused by the pathogen, Cronartium ribicola. We focused on four dominant white pine host species in Sequoia and Kings Canyon National Parks (SEKI), including sugar pine (Pinus lambertiana), western white pine (P. monticola), whitebark pine (P. albicaulis), and foxtail pine (P. balfouriana). Between 2013 and 2017, we resurveyed 152 long‐term monitoring plots that were first surveyed and established between 1995 and 1999. Overall extent (plots with at least one infected tree) of white pine blister rust (blister rust) increased from 20% to 33%. However, the infection rate across all species decreased from 5.3% to 4.2%. Blister rust dynamics varied greatly by species, as infection rate decreased from 19.1% to 6.4% in sugar pine, but increased in western white pine from 3.0% to 8.7%. For the first time, blister rust was recorded in whitebark pine, but not foxtail pine plots. MPB attacks were highest in sugar pines and decreased in the higher elevation white pine species, whitebark and foxtail pine. Both blister rust and MPB were important factors associated with elevated mortality in sugar pines. We did not, however, find a relationship between previous fires and blister rust occurrence. In addition, multiple mortality agents, including blister rust, fire, and MPB, contributed to major declines in sugar pine and western white pine; recruitment rates were much lower than mortality rates for both species. Our results highlighted that sugar pine has been declining much faster in SEKI than previously documented. If blister rust and MPB trends persist, western white pine may follow similar patterns of decline in the future. Given current spread patterns, blister rust will likely continue to increase in higher elevations, threatening subalpine white pines in the southern Sierra Nevada. More frequent long‐term monitoring efforts could inform ongoing restoration and policy focused on threats to these highly valuable and diverse white pines.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3263","usgsCitation":"Dudney, J.C., Nesmith, J.C., Cahill, M., Cribbs, J.E., Duriscoe, D.M., Das, A., Stephenson, N.L., and Battles, J.J., 2020, Compounding effects of white pine blister rust, mountain pine beetle, and fire threaten four white pine species: Ecosphere, v. 11, no. 10, e03263, 20 p., https://doi.org/10.1002/ecs2.3263.","productDescription":"e03263, 20 p.","ipdsId":"IP-119965","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":455074,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3263","text":"Publisher Index Page"},{"id":380779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Kings Canyon National Park, Sequioia National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.31427001953125,\n 35.52552053465406\n ],\n [\n -117.7679443359375,\n 35.52552053465406\n ],\n [\n -117.7679443359375,\n 37.07271048132943\n ],\n [\n -119.31427001953125,\n 37.07271048132943\n ],\n [\n -119.31427001953125,\n 35.52552053465406\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Dudney, Joan C","contributorId":245215,"corporation":false,"usgs":false,"family":"Dudney","given":"Joan","email":"","middleInitial":"C","affiliations":[{"id":33770,"text":"University of California at Berkeley","active":true,"usgs":false}],"preferred":false,"id":805640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nesmith, Jonathan C B","contributorId":245216,"corporation":false,"usgs":false,"family":"Nesmith","given":"Jonathan","email":"","middleInitial":"C B","affiliations":[{"id":49124,"text":"National Park Service, Sierra Nevada Network Inventory & Monitoring Program","active":true,"usgs":false}],"preferred":false,"id":805641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cahill, Matthew","contributorId":245219,"corporation":false,"usgs":false,"family":"Cahill","given":"Matthew","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":805642,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cribbs, Jennifer E","contributorId":245220,"corporation":false,"usgs":false,"family":"Cribbs","given":"Jennifer","email":"","middleInitial":"E","affiliations":[{"id":49124,"text":"National Park Service, Sierra Nevada Network Inventory & Monitoring Program","active":true,"usgs":false}],"preferred":false,"id":805643,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duriscoe, Dan M","contributorId":245221,"corporation":false,"usgs":false,"family":"Duriscoe","given":"Dan","email":"","middleInitial":"M","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":805644,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Das, Adrian 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":201236,"corporation":false,"usgs":true,"family":"Das","given":"Adrian","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":805645,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stephenson, Nathan L. 0000-0003-0208-7229 nstephenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0208-7229","contributorId":2836,"corporation":false,"usgs":true,"family":"Stephenson","given":"Nathan","email":"nstephenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":805646,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Battles, John J.","contributorId":102006,"corporation":false,"usgs":false,"family":"Battles","given":"John","email":"","middleInitial":"J.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":805647,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216395,"text":"70216395 - 2020 - Drivers of wildfire carbon emissions","interactions":[],"lastModifiedDate":"2020-12-14T16:52:12.468223","indexId":"70216395","displayToPublicDate":"2020-10-12T07:36:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of wildfire carbon emissions","docAbstract":"Increasing fire frequency and severity may shift boreal forests from carbon sinks to carbon sources and amplify climate warming. Analysis indicates that that fuel characteristics are important drivers of wildfire carbon emissions across a broad range of North America’s boreal forest.","language":"English","publisher":"Nature","doi":"10.1038/s41558-020-00922-6","usgsCitation":"Loehman, R.A., 2020, Drivers of wildfire carbon emissions: Nature Climate Change, v. 10, p. 1070-1071, https://doi.org/10.1038/s41558-020-00922-6.","productDescription":"2 p.","startPage":"1070","endPage":"1071","ipdsId":"IP-121883","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":380525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2020-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":804891,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"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":70217569,"text":"70217569 - 2020 - Phylogenetic escape from pests reduces pesticides on some crop plants","interactions":[],"lastModifiedDate":"2021-01-22T13:27:13.231465","indexId":"70217569","displayToPublicDate":"2020-10-12T07:25:11","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Phylogenetic escape from pests reduces pesticides on some crop plants","docAbstract":"Pesticides are a ubiquitous component of conventional crop production but come with considerable economic and ecological costs. We tested the hypothesis that variation in pesticide use among crop species is a function of crop economics and the phylogenetic relationship of a crop to native plants because unrelated crops accrue fewer herbivores and pathogens. Comparative analyses of a dataset of 93 Californian crops showed that more valuable crops and crops with close relatives in the native plant flora received greater pesticide use, explaining roughly half of the variance in pesticide use among crops against pathogens and herbivores. Phylogenetic escape from arthropod and pathogen pests results in lower pesticides, suggesting that the introduced status of some crops can be leveraged to reduce pesticides.
","language":"English","publisher":"PNAS","doi":"10.1073/pnas.2013751117","usgsCitation":"Pearse, I., and Rosenheim, J., 2020, Phylogenetic escape from pests reduces pesticides on some crop plants: Proceedings of the National Academy of Sciences, v. 117, no. 43, p. 26849-26853, https://doi.org/10.1073/pnas.2013751117.","productDescription":"5 p.","startPage":"26849","endPage":"26853","ipdsId":"IP-120433","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":455079,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7604411","text":"External Repository"},{"id":436756,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TIK3JP","text":"USGS data release","linkHelpText":"Californian crop pests, pesticide applications, and phylogenetic information of crops"},{"id":382488,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","issue":"43","noUsgsAuthors":false,"publicationDate":"2020-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":808707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenheim, Jay 0000-0002-9228-4754","orcid":"https://orcid.org/0000-0002-9228-4754","contributorId":248267,"corporation":false,"usgs":false,"family":"Rosenheim","given":"Jay","email":"","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":808708,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70215396,"text":"70215396 - 2020 - Four-dimensional thermal evolution of the East African Orogen: Accessory phase petrochronology of crustal profiles through the Tanzanian Craton and Mozambique Belt, northeastern Tanzania","interactions":[],"lastModifiedDate":"2020-10-17T15:47:10.208804","indexId":"70215396","displayToPublicDate":"2020-10-09T10:39:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1336,"text":"Contributions to Mineralogy and Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Four-dimensional thermal evolution of the East African Orogen: Accessory phase petrochronology of crustal profiles through the Tanzanian Craton and Mozambique Belt, northeastern Tanzania","docAbstract":"U–Pb petrochronology of deep crustal xenoliths and outcrops across northeastern Tanzania track the thermal evolution of the Mozambique Belt and Tanzanian Craton following the Neoproterozoic East African Orogeny (EAO) and subsequent Neogene rifting. At the craton margin, the upper–middle crust record thermal quiescence since the Archean (2.8–2.5 Ga zircon, rutile, and apatite in granite and amphibolite xenoliths). The lower crust of the craton documents thermal pulses associated with Neoarchean ultra-high temperature metamorphism (ca. 2.64 Ga, > 900 °C zircon), the EAO (600–500 Ma rutile), and fluid influx during rifting (< 5 Ma apatite). Rutile in garnet granulite xenoliths exhibits partial Pb loss related to slow cooling of the lower crust after the EAO and suggests residence at 500–600 °C prior to entrainment. In contrast to the craton, the entire crust of the Mozambique Belt underwent differential cooling following the EAO. Both the upper and middle crust record metamorphism from 640 to 560 Ma (zircon, monazite, and titanite) and rapid exhumation at 510–440 Ma (rutile and apatite). Lower crustal xenoliths contain Archean zircon, but near-zero age rutile and apatite, indicating residence > 650 °C (above Pb closure of rutile and apatite) at the time of eruption. Zoned titanite records growth during cooling of the lower crust at 550 Ma, followed by fluid influx during slow cooling and exhumation (0.1–1 °C/Myr after 450 Ma). Permissible lower-crustal temperatures for the craton and orogen suggest variable mantle heat flow through the crust and reflect differences in mantle lithosphere thickness rather than advective heating from rifting.
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":70216942,"text":"70216942 - 2020 - Comment on “Female toads engaging in adaptive hybridization prefer high-quality heterospecifics as mates”","interactions":[],"lastModifiedDate":"2020-12-17T14:11:55.656041","indexId":"70216942","displayToPublicDate":"2020-10-09T08:09:39","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Comment on “Female toads engaging in adaptive hybridization prefer high-quality heterospecifics as mates”","docAbstract":"Chen and Pfennig (Reports, 20 March 2020, p. 1377) analyze the fitness consequences of hybridization in toads but do not account for differences in survival among progeny. Apparent fitness effects depend on families with anomalously low survival, yet survival is crucial to evolutionary fitness. This and other analytical shortcomings demonstrate that a conclusion of adaptive mate choice is not yet justified.
If carbon capture and storage (CCS) needs to be deployed at basin- or larger-scale, it is likely that multiple sites will be injecting carbon dioxide (CO2) into the same geologic formation. This could lead to excessive pressure buildup, overlapping induced pressure fronts, and pressure interference with neighboring uses of the subsurface. Extracting the in situ brine from the storage formation could be necessary to relieve pressure constraints; control migration of the CO2 plume, displaced brine, and the induced pressure front; and sequester more CO2 while reducing potential risks. Such active pressure management could be very costly, and it could present a formidable economic constraint on the feasible scale of deployment of CCS. Alternatively, there may be high-injectivity zones (“storage sweet spots”) where a significant volume of CO2 could be stored without producing brine. For simulated deployment of CO2 storage sites across the Illinois Basin, the results of this study suggest that brine production could be required to sequester 20 % or more of the regional CO2 emissions of major stationary sources in the Mount Simon Sandstone saline formation. In some cases, brine production could expand pressure-limited CO2 storage capacity enough to more than compensate for the additional costs of pressure management, but only if produced brine could be cheaply reinjected onsite for disposal in an overlying geologic formation. With or without brine production, this study found that the lowest-cost deployment option was to inject CO2 only into a potential storage sweet spot of the Mount Simon Sandstone.
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.
Little has been published regarding the burrowing habits of Agassiz’s desert tortoises (Gopherus agassizii) in the Sonoran Desert of California. We monitored the interactions of tortoises with their burrows, and other tortoises, via radio-telemetry at two nearby sites between the Cottonwood and Orocopia Mountains, from 2015-2018. We examined how annual cycles of drought and non-drought years, behaviourally affected how tortoises use their burrows (i.e., burrow fidelity, cohabitation,
and location), including the timing of the tortoise brumation period. Burrow locations were strongly dependent on local geology and topography, with a tendency to orientate in conformance with the general aspect of the landscape. The timing of brumation was similar to records for G. agassizii throughout their range (with a few exceptions). There was no difference in the estimated number of burrows used per 30 days between the active seasons (2017 and 2018) at the Orocopia site, despite the occurrence of drought in 2018.