The health and well-being of plants and soil is crucial for all life on Earth. It is well-known that vegetation cover follows climatic zones, and plants respond to climatic drivers such as temperature and precipitation (Seddon et al., 2016; Kattge et al., 2020). It is also well-known that plant health depends on the properties and health of the soil (Ephrath et al., 2020), and that strong interactions among biota above and belowground dictate the functioning of both realms (Van der Putten et al., 2013). Yet, soils and the processes occurring belowground are often considered a “black box,” and are treated very simplistically in our efforts to understand, quantify, and model the future of the planet. Our understanding of the interactions between plants and soils is also far from complete and offers some of the most important research frontiers in community ecology, biogeochemistry, and global change science.
","language":"English","publisher":"Frontiers","doi":"10.3389/fpls.2020.621235","usgsCitation":"Sevanto, S., Grossiord, C., Klein, T., and Reed, S., 2020, Editorial: Plant-soil interactions under changing climate: Frontiers in Plant Science, v. 11, 621235, 2 p., https://doi.org/10.3389/fpls.2020.621235.","productDescription":"621235, 2 p.","ipdsId":"IP-124196","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":454637,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fpls.2020.621235","text":"Publisher Index Page"},{"id":382085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2020-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Sevanto, Sanna","contributorId":150845,"corporation":false,"usgs":false,"family":"Sevanto","given":"Sanna","email":"","affiliations":[],"preferred":false,"id":807980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grossiord, Charlotte","contributorId":207749,"corporation":false,"usgs":false,"family":"Grossiord","given":"Charlotte","email":"","affiliations":[{"id":37625,"text":"Earth and Environmental Sciences Division, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":807981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klein, Tamir","contributorId":181981,"corporation":false,"usgs":false,"family":"Klein","given":"Tamir","email":"","affiliations":[],"preferred":false,"id":807982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":807983,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216898,"text":"sim3458 - 2020 - Geologic map and borehole stratigraphy of Hinkley Valley and vicinity, San Bernardino County, California","interactions":[],"lastModifiedDate":"2021-01-04T19:40:40.811178","indexId":"sim3458","displayToPublicDate":"2020-12-18T06:45:39","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":"3458","displayTitle":"Geologic Map and Borehole Stratigraphy of Hinkley Valley and Vicinity, San Bernardino County, California","title":"Geologic map and borehole stratigraphy of Hinkley Valley and vicinity, San Bernardino County, California","docAbstract":"Hinkley Valley, in the central to western Mojave Desert of southeastern California, has a long historical record owing to its position as a crossroads for rail and road traffic and its position adjacent to the Mojave River. Subflow in the Mojave River provided groundwater recharge that maintained water consumption and demand by way of shallow wells for local agriculture in the valley. Its crossroads position led to construction of several power-transmission lines, pipeline, and communications cable routes that transect Hinkley Valley. One of these, a natural gas pipeline and its associated compressor station, was the locus of hexavalent chromium, Cr(VI), released into, and consequent contamination of, groundwater. Understanding the movement and fate of the contaminants is a complex hydrologic and geochemical problem. Geologic mapping of the Hinkley Valley area provides framework elements for use in resolving this problem. This report provides new information on surface and subsurface geology to better constrain the origin and geometry of hydrologically important deposits in the Hinkley Valley area and describes youthful faults that may control sediment distribution and groundwater flow. The geologic map (sheet 1) presents substantial new information on surficial geology, including Pliocene deposits, but does not contain significant new work on bedrock. Bedrock investigations were specific to identifying youthful faults and representative outcrops for rocks that were penetrated by boreholes in the valley. Special attention was placed on locating and describing youthful faults. In addition, we analyzed gravity data to (1) map horizontal gradients that we interpret to reflect long-term fault traces and to (2) estimate the depth to bedrock, which is defined as Miocene and older intrusive and metamorphic rocks for the purposes of this report. The subsurface geology of Hinkley Valley was investigated by examining borehole sediment cores and rock encountered at the base of the sediment section. We analyzed the core to determine depositional environments, provenance, and age of the sediment that infilled the valley. Valleys, mountains, and basins in the Hinkley Valley area are topographically complex and incompletely named. The nearly flat floored Hinkley Valley slopes gently northward. It is framed by Mount General and the informally named “Hinkley hills” (southeast of Mount General) on the northeast and by Iron Mountain and Lynx Cat Mountain on the southwest, although breaks in the western mountains allow stream connections between Hinkley Valley and another valley to the west that is herein referred to as Hawes valley. At its south end, Hinkley Valley is traversed by the entrenched Mojave River, which passes east out of the valley past Barstow. North of Hinkley Valley, a few low hills (including Red Hill) separate the valley from a broad west-sloping piedmont that is part of the physiographic Harper Basin (of which the Harper Lake playa is the center). The lower part of this piedmont, however, is referred to as Water Valley, although it is not a distinct valley. The name derives from groundwater sourced from subflow in the Mojave River, which caused shallow water and even artesian flow in Water Valley but not in other parts of the Harper Basin. When water filled the Harper Basin to form Pleistocene Lake Harper it not only submerged Water Valley but also northern Hinkley Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3458","collaboration":"Prepared in cooperation with the Lahontan Regional Water Quality Control Board and the State Water Resources Control Board","usgsCitation":"Miller, D.M., Langenheim, V.E., and Haddon, E.K., 2020, Geologic map and borehole stratigraphy of Hinkley Valley and vicinity, San Bernardino County, California: U.S. Geological Survey Scientific Investigations Map 3458, pamphlet 23 p., 2 sheets, scale 1:24,000, https://doi.org/10.3133/sim3458.","productDescription":"Pamphlet,: iv, 23 p.; 2 Sheets ; 2 Tables; Database; Data Release; Metadata","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-102109","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":381271,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_sheet2.pdf","text":"Sheet 2","size":"32 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381270,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_sheet1.pdf","text":"Sheet 1","size":"40 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381269,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_database.zip","text":"Database","size":"7.5 MB","linkFileType":{"id":6,"text":"zip"}},{"id":381268,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_base.zip","text":"Base","size":"1.25 GB","linkFileType":{"id":6,"text":"zip"}},{"id":381267,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_metadata.txt","size":"10 KB","linkFileType":{"id":2,"text":"txt"}},{"id":381266,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_pamphlet.pdf","text":"Pamphlet","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381451,"rank":10,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FV5LG5","linkHelpText":"Gravity data of the Hinkley area, southern California"},{"id":381273,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_table_7.xlsx","text":"Table 7","size":"60 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":381265,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3458/covrthb.jpg"},{"id":381272,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_table_3.xlsx","text":"Table 3","size":"20 KB","linkFileType":{"id":3,"text":"xlsx"}}],"country":"United States","state":"California","county":"San Bernadino County","otherGeospatial":"Hinkley Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.26257324218749,\n 34.80647431931937\n ],\n [\n -117.06619262695312,\n 34.80647431931937\n ],\n [\n -117.06619262695312,\n 35.060352812431496\n ],\n [\n -117.26257324218749,\n 35.060352812431496\n ],\n [\n -117.26257324218749,\n 34.80647431931937\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
Surface-based 2D electrical resistivity tomography (ERT) surveys were used to characterize permafrost distribution at wetland sites on the alluvial plain north of the Tanana River, 20 km southwest of Fairbanks, Alaska, in June and September 2014. The sites were part of an ecologically-sensitive research area characterizing biogeochemical response of this region to warming and permafrost thaw, and the site contained landscape features characteristic of interior Alaska, including thermokarst bog, forested permafrost plateau, and a rich fen. The results show how vegetation reflects shallow (0–10 m depth) permafrost distribution. Additionally, we saw shallow (0–3 m depth) low resistivity areas in forested permafrost plateau potentially indicating the presence of increased unfrozen water content as a precursor to ground instability and thaw. Time-lapse study from June to September suggested a depth of seasonal influence extending several meters below the active layer, potentially as a result of changes in unfrozen water content. A comparison of several electrode geometries (dipole-dipole, extended dipole-dipole, Wenner-Schlumberger) showed that for depths of interest to our study (0–10 m) results were similar, but data acquisition time with dipole-dipole was the shortest, making it our preferred geometry. The results show the utility of ERT surveys to characterize permafrost distribution at these sites, and how vegetation reflects shallow permafrost distribution. These results are valuable information for ecologically sensitive areas where ground-truthing can cause excessive disturbance. ERT data can be used to characterize the exact subsurface geometry of permafrost such that over time an understanding of changing permafrost conditions can be made in great detail. Characterizing the depth of thaw and thermal influence from the surface in these areas also provides important information as an indication of the depth to which carbon storage and microbially-mediated carbon processing may be affected.
","language":"English","publisher":"Environmental & Engineering Geophysical Society","doi":"10.2113/JEEG19-091","usgsCitation":"Conaway, C., Johnson, C., Lorenson, T., Turetsky, M.R., Euskirchen, E., Waldrop, M., and Swarzenski, P.W., 2020, Permafrost mapping with electrical resistivity tomography in two wetland systems north of the Tanana River, Interior Alaska: Journal of Environmental & Engineering Geophysics, v. 2, no. 25, p. 199-209, https://doi.org/10.2113/JEEG19-091.","productDescription":"11 p.","startPage":"199","endPage":"209","ipdsId":"IP-102186","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":436695,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KTHH8X","text":"USGS data release","linkHelpText":"Permafrost Mapping in Two Wetland Systems North of the Tanana River in Interior Alaska 2014"},{"id":381485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Tanana River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -148.19732666015625,\n 64.72374428370091\n ],\n [\n -148.4197998046875,\n 64.86527470612393\n ],\n [\n -149.117431640625,\n 64.83959712503844\n ],\n [\n -149.095458984375,\n 64.63564536799623\n ],\n [\n -149.07073974609375,\n 64.57321597426092\n ],\n [\n -148.7274169921875,\n 64.59561280029605\n ],\n [\n -148.66973876953125,\n 64.63917482390902\n ],\n [\n -148.392333984375,\n 64.66621875267623\n ],\n [\n -148.19732666015625,\n 64.72374428370091\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","issue":"25","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Conaway, Christopher H. 0000-0002-0991-033X","orcid":"https://orcid.org/0000-0002-0991-033X","contributorId":201932,"corporation":false,"usgs":true,"family":"Conaway","given":"Christopher H.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":807080,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Cordell 0000-0001-8353-8030","orcid":"https://orcid.org/0000-0001-8353-8030","contributorId":212817,"corporation":false,"usgs":true,"family":"Johnson","given":"Cordell","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807081,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorenson, Thomas 0000-0001-7669-2873 tlorenson@usgs.gov","orcid":"https://orcid.org/0000-0001-7669-2873","contributorId":174599,"corporation":false,"usgs":true,"family":"Lorenson","given":"Thomas","email":"tlorenson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807082,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Turetsky, Merritt R.","contributorId":169398,"corporation":false,"usgs":false,"family":"Turetsky","given":"Merritt","email":"","middleInitial":"R.","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":807083,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Euskirchen, Eugénie S.","contributorId":83378,"corporation":false,"usgs":false,"family":"Euskirchen","given":"Eugénie S.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":807084,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216758,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[],"preferred":true,"id":807085,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":189823,"corporation":false,"usgs":false,"family":"Swarzenski","given":"Peter","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":807086,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70218740,"text":"70218740 - 2020 - Book review of \"Plant anatomy—A concept based approach to the structure of seed plants\"","interactions":[],"lastModifiedDate":"2021-03-10T14:29:15.726312","indexId":"70218740","displayToPublicDate":"2020-12-17T08:21:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7750,"text":"Plant Science Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Book review of \"Plant anatomy—A concept based approach to the structure of seed plants\"","docAbstract":"Plant Anatomy: A Concept-Based Approach to the Structure of Seed Plants by Crang, Lyons-Sobaski, and Wise is a beautifully-illustrated, 600+ page textbook highlighting the wonderful diversity of anatomical form in plants. The layout of the chapters follows many traditional plant anatomy textbooks. Plant Anatomy begins with an overview of plant morphology and proceeds through evolutionary time and across systems (Chapter 1. The Nature of Plants) before zooming into the microscopic, internal world of plant structures and their function (Chapter 2. Microscopy and Imaging through Chapter 8. Phloem). Quite fortunately, historical context is described throughout these sections, highlighting seminal studies that have shaped the plant sciences over the past 300+ years.
","language":"English","publisher":"Botanical Society of America","usgsCitation":"Winkler, D.E., 2020, Book review of \"Plant anatomy—A concept based approach to the structure of seed plants\": Plant Science Bulletin, v. 66, no. 3, p. 261-262.","productDescription":"2 p.","startPage":"261","endPage":"262","ipdsId":"IP-124238","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":384277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":384254,"type":{"id":15,"text":"Index Page"},"url":"https://cms.botany.org/home/publications/plant-science-bulletin.html"}],"volume":"66","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":811575,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70216972,"text":"70216972 - 2020 - Reestablishing a stepping-stone population of the threatened elkhorn coral Acropora palmata to aid regional recovery","interactions":[],"lastModifiedDate":"2020-12-21T13:59:32.421478","indexId":"70216972","displayToPublicDate":"2020-12-17T07:56:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Reestablishing a stepping-stone population of the threatened elkhorn coral Acropora palmata to aid regional recovery","docAbstract":"Recovery of the elkhorn coral Acropora palmata is critical to reversing coral reef ecosystem collapse in the western Atlantic, but the species is severely threatened. To gauge potential for the species’ restoration in Florida, USA, we conducted an assisted migration experiment where 50 coral fragments of 5 nursery-raised genetic strains (genets) from the upper Florida Keys were moved to 5 sites across 350 km of the offshore reef. Additionally, 4 fragments from the 1 remaining colony of A. palmata in Dry Tortugas National Park (DRTO) were added to the 2 DRTO experimental sites to test for local adaptation. To measure coral performance, we tracked coral survival, calcification, growth, and condition from May 2018 to October 2019. All 24 corals relocated to the DRTO sites survived and calcified ~85% faster than the fewer surviving corals transplanted to the 2 upper Keys sites. While coral survival across the entire experiment did not depend on genet, there was a weak but statistically significant genetic effect on calcification rate among the corals relocated to DRTO. The DRTO native genet was among the fastest growing genets, but it was not the fastest, suggesting a lack of local adaptation at this scale. Our results indicate that DRTO, a remote reef system inhabited by the species during the Holocene and located at the nexus of major ocean currents, may be a prime location for reestablishing A. palmata. Assisted migration of A. palmata to DRTO could restore a sexually reproducing population in <10 yr, thereby promoting the species’ regional recovery.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01083","usgsCitation":"Kuffner, I.B., Stathakopoulos, A., Toth, L., and Bartlett, L., 2020, Reestablishing a stepping-stone population of the threatened elkhorn coral Acropora palmata to aid regional recovery: Endangered Species Research, v. 43, p. 461-473, https://doi.org/10.3354/esr01083.","productDescription":"13 p.","startPage":"461","endPage":"473","ipdsId":"IP-119764","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454641,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01083","text":"Publisher Index Page"},{"id":436696,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KZEGXY","text":"USGS data release","linkHelpText":"Experimental coral-growth data and time-series imagery for Acropora palmata in the Florida Keys, U.S.A."},{"id":381533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Keys","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.93603515625,\n 24.337086982410497\n ],\n [\n -81.090087890625,\n 24.557116164309626\n ],\n [\n -80.211181640625,\n 24.836595553891183\n ],\n [\n -80.145263671875,\n 25.27450351782018\n ],\n [\n -80.2880859375,\n 25.41350860804229\n ],\n [\n -81.002197265625,\n 25.15522939494057\n ],\n [\n -81.76025390625,\n 24.766784522874453\n ],\n [\n -82.100830078125,\n 24.637031353509528\n ],\n [\n -82.078857421875,\n 24.367113562651262\n ],\n [\n -81.93603515625,\n 24.337086982410497\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kuffner, Ilsa B. 0000-0001-8804-7847 ikuffner@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7847","contributorId":3105,"corporation":false,"usgs":true,"family":"Kuffner","given":"Ilsa","email":"ikuffner@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stathakopoulos, Anastasios 0000-0002-4404-035X astathakopoulos@usgs.gov","orcid":"https://orcid.org/0000-0002-4404-035X","contributorId":147744,"corporation":false,"usgs":true,"family":"Stathakopoulos","given":"Anastasios","email":"astathakopoulos@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bartlett, Lucy 0000-0001-6603-7090","orcid":"https://orcid.org/0000-0001-6603-7090","contributorId":214863,"corporation":false,"usgs":true,"family":"Bartlett","given":"Lucy","email":"","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807133,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217102,"text":"70217102 - 2020 - Diet and bathymetric distribution of juvenile Lake Trout Salvelinus namaycush in Lake Huron","interactions":[],"lastModifiedDate":"2021-01-06T13:22:37.723352","indexId":"70217102","displayToPublicDate":"2020-12-17T07:18:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":865,"text":"Aquatic Ecosystem Health & Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Diet and bathymetric distribution of juvenile Lake Trout Salvelinus namaycush in Lake Huron","title":"Diet and bathymetric distribution of juvenile Lake Trout Salvelinus namaycush in Lake Huron","docAbstract":"Rehabilitation efforts for Lake Trout Salvelinus namaycush in Lake Huron have resulted in increased capture of young wild Lake Trout in annual bottom trawl surveys conducted by the U.S. Geological Survey. To better understand the ecology of juvenile (<400mm) Lake Trout, we summarized the spatial distribution of their capture in bottom trawls at six ports in Lake Huron during October/November 20082017 and analyzed diets of wild (n = 306 of 337 total) and hatchery-origin (n = 18 of 30 total) fish captured. Lake Trout ranged in size from 27 to 399mm, representing at least three age-classes, and 92% were wild origin. Most wild juvenile Lake Trout (83%) were captured at 4664 m depths at the two northernmost ports, typically below the thermocline. Mysis diluviana was the most prevalent prey type, found in 75% of wild fish with non-empty stomachs, followed by two non-native species: Spiny Water Flea Bythotrephes longimanus (31%) and Round Goby Neogobius melanostomus (12%). Small Lake Trout (<185mm) consumed invertebrates but transitioned to mostly fish-based diets by >185mm (age 2). The variety of taxa consumed by young Lake Trout increased with length. Further declines in Mysis populations due to increased predation pressure after the loss of Diporeia from the system may hinder the recovery of wild Lake Trout, and although they have been able to utilize invasive species as prey, impacts to Lake Trout growth remain unknown. Additional research on the habitat use and diets of wild juvenile Lake Trout may provide insight into the reasons behind the recent successful natural reproduction and recruitment of Lake Trout in Lake Huron.","language":"English","publisher":"Taylor Francis","doi":"10.1080/14634988.2020.1826158","usgsCitation":"Roseman, E., Riley, S., Tucker, T., Farha, S., Jackson, S., and Bowser, D., 2020, Diet and bathymetric distribution of juvenile Lake Trout Salvelinus namaycush in Lake Huron: Aquatic Ecosystem Health & Management, v. 23, no. 3, p. 350-365, https://doi.org/10.1080/14634988.2020.1826158.","productDescription":"16 p.","startPage":"350","endPage":"365","ipdsId":"IP-113585","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":381942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.0673828125,\n 46.34692761055676\n ],\n [\n -84.72656249999999,\n 46.057985244793024\n ],\n [\n -84.72656249999999,\n 45.79816953017265\n ],\n [\n -83.69384765625,\n 43.5326204268101\n ],\n [\n -82.37548828125,\n 43.052833917627936\n ],\n [\n -81.67236328125,\n 43.42100882994726\n ],\n [\n -80.0244140625,\n 44.62175409623324\n ],\n [\n -79.8046875,\n 44.824708282300236\n ],\n [\n -80.70556640625,\n 46.057985244793024\n ],\n [\n -84.0673828125,\n 46.34692761055676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":807613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riley, Stephen 0000-0002-8968-8416 sriley@usgs.gov","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":169479,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen","email":"sriley@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":807615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farha, Steve A. 0000-0001-9953-6996 sfarha@usgs.gov","orcid":"https://orcid.org/0000-0001-9953-6996","contributorId":5170,"corporation":false,"usgs":true,"family":"Farha","given":"Steve A.","email":"sfarha@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807616,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, Scott 0000-0003-1272-9918","orcid":"https://orcid.org/0000-0003-1272-9918","contributorId":208420,"corporation":false,"usgs":false,"family":"Jackson","given":"Scott","affiliations":[],"preferred":false,"id":807617,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bowser, Dustin 0000-0001-5674-8016 dbowser@usgs.gov","orcid":"https://orcid.org/0000-0001-5674-8016","contributorId":223117,"corporation":false,"usgs":true,"family":"Bowser","given":"Dustin","email":"dbowser@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807618,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70219575,"text":"70219575 - 2020 - Assessing contributions of cold-water refuges to reproductive migration corridor conditions for adult salmon and steelhead trout in the Columbia River, USA","interactions":[],"lastModifiedDate":"2021-04-14T12:03:12.831455","indexId":"70219575","displayToPublicDate":"2020-12-17T06:59:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5513,"text":"Journal of Ecohydraulics","active":true,"publicationSubtype":{"id":10}},"title":"Assessing contributions of cold-water refuges to reproductive migration corridor conditions for adult salmon and steelhead trout in the Columbia River, USA","docAbstract":"Diadromous fish populations face multiple challenges along their migratory routes. These challenges include suboptimal water quality, harvest, and barriers to longitudinal and lateral connectivity. Interactions among factors influencing migration success make it challenging to assess management options for improving migratory fish conditions along riverine migration corridors. We describe a spatially explicit simulation model that integrates complex individual behaviors of fall-run Chinook Salmon (Oncorhynchus tshawytscha) and summer-run steelhead trout (O. mykiss) during migration, responds to variable habitat conditions over a large extent of the Columbia River, and links migration corridor conditions to fish condition outcomes. The model is built around a mechanistic behavioral decision tree that drives individual interactions of fish within their simulated environments. By simulating several thermalscapes with alternative scenarios of thermal refuge availability, we examined how behavioral thermoregulation in cold-water refuges influenced migrating fish conditions. Outcomes of the migration corridor simulation model show that cold-water refuges can provide relief from exposure to high water temperatures, but do not substantially contribute to energy conservation by migrating adults. Simulated cooling of the Columbia River decreased reliance on cold-water refuges and there were slight reductions in migratory energy expenditure. This modeling of simulated thermalscapes provides a framework for assessing the contribution of cold-water refuges to the success of migrating fishes, but any final determination will depend on analyzing fish survival and health for their entire migration, water temperature management goals and species recovery targets.
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Head-starting—the captive rearing of offspring to a size where they are presumably more likely to survive post-release—is being explored as a potential recovery tool. Previous Desert Tortoise head-starting programs have reared neonates exclusively outdoors. Here, we explore using a combination of indoor and outdoor captive rearing to maximize post-release success and rearing efficiency. We assigned 68 neonates (2016 cohort) to one of two treatments: Outdoor HS (n = 38), where neonates were reared exclusively in outdoor predator-proof enclosures, and Combo HS (n = 30), where neonates were reared indoors for 1 y followed by outdoor rearing for 1 y. After 2 y of captive rearing, we randomly selected 24 Outdoor HS and 24 Combo HS juveniles for release in the Mojave National Preserve, CA on 25 September 2018. We compare pre-release size, body condition, and shell hardness as well as first year post-release movement and survival between the treatment groups. Pre-release body condition was not significantly different between groups. Outdoor HS tortoises, however, were significantly smaller and had significantly softer shells than Combo HS tortoises. Excluding two missing animals, released head-starts experienced 78.2% survival through their first year after release. Combo HS tortoises on average dispersed significantly shorter distances after 1 y than Outdoor HS animals. Our findings that Combo HS animals were larger and had harder shells at release, and exhibited high survival but low dispersal following release, support the implementation of combination head-starting as part of the recovery effort for the Mojave Desert Tortoise.
","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"McGovern, P., Buhlmann, K.A., Todd, B.D., Moore, C.T., Peaden, J.M., Hepinstall-Cymerman, J., Daly, J.A., and Tuberville, T.D., 2020, Comparing husbandry techniques for optimal head-starting of the Mojave desert tortoise (Gopherus agassizii): Herpetological Conservation and Biology, v. 15, no. 3, p. 626-641.","productDescription":"16 p.","startPage":"626","endPage":"641","ipdsId":"IP-115675","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395787,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/contents_vol15_issue3.html"}],"country":"United States","state":"California","otherGeospatial":"Ivanpah Valley, Mojave National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.4608154296875,\n 35.110921809704756\n ],\n [\n -115.10925292968749,\n 35.110921809704756\n ],\n [\n -115.10925292968749,\n 35.50987173838399\n ],\n [\n -115.4608154296875,\n 35.50987173838399\n ],\n [\n -115.4608154296875,\n 35.110921809704756\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McGovern, P. A.","contributorId":275620,"corporation":false,"usgs":false,"family":"McGovern","given":"P. A.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buhlmann, K. A.","contributorId":275621,"corporation":false,"usgs":false,"family":"Buhlmann","given":"K.","email":"","middleInitial":"A.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Todd, B. D.","contributorId":275623,"corporation":false,"usgs":false,"family":"Todd","given":"B.","email":"","middleInitial":"D.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":834179,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834180,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peaden, J. M.","contributorId":275626,"corporation":false,"usgs":false,"family":"Peaden","given":"J.","email":"","middleInitial":"M.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":834181,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hepinstall-Cymerman, J.","contributorId":275628,"corporation":false,"usgs":false,"family":"Hepinstall-Cymerman","given":"J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834182,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Daly, J. A.","contributorId":275632,"corporation":false,"usgs":false,"family":"Daly","given":"J.","email":"","middleInitial":"A.","affiliations":[{"id":56868,"text":"Directorate of Public Works, Environmental Division, Dublin, CA","active":true,"usgs":false}],"preferred":false,"id":834183,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tuberville, T. D.","contributorId":275634,"corporation":false,"usgs":false,"family":"Tuberville","given":"T.","email":"","middleInitial":"D.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834184,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70218474,"text":"70218474 - 2020 - Stony coral tissue loss disease in Florida is associated with disruption of host–zooxanthellae physiology","interactions":[],"lastModifiedDate":"2021-03-01T15:53:30.188709","indexId":"70218474","displayToPublicDate":"2020-12-16T09:44:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Stony coral tissue loss disease in Florida is associated with disruption of host–zooxanthellae physiology","docAbstract":"Samples from eight species of corals (Colpophyllia natans, Dendrogyra cylindrus, Diploria labyrinthiformis, Meandrina meandrites, Montastraea cavernosa, Orbicella faveolata, Pseudodiploria strigosa, and Siderastrea siderea) that exhibited gross clinical signs of acute, subacute, or chronic tissue loss attributed to stony coral tissue loss disease (SCTLD) were collected from the Florida Reef Tract during 2016–2018 and examined histopathologically. The hallmark microscopic lesion seen in all eight species was focal to multifocal lytic necrosis (LN) originating in the gastrodermis of the basal body wall (BBW) and extending to the calicodermis, with more advanced lesions involving the surface body wall. This was accompanied by other degenerative changes in host cells such as mucocyte hypertrophy, degradation and fragmentation of gastrodermal architecture, and disintegration of the mesoglea. Zooxanthellae manifested various changes including necrosis (cytoplasmic hypereosinophilia, pyknosis); peripheral nuclear chromatin condensation; cytoplasmic vacuolation accompanied by deformation, swelling, or atrophy; swollen accumulation bodies; prominent pyrenoids; and degraded chloroplasts. Polyhedral intracytoplasmic eosinophilic periodic acid–Schiff-positive crystalline inclusion bodies (∼1–10 μm in length) were seen only in M. cavernosa and P. strigosa BBW gastrodermis in or adjacent to active lesions and some unaffected areas (without surface lesions) of diseased colonies. Coccoidlike or coccobacilloidlike structures (Gram-neutral) reminiscent of microorganisms were occasionally associated with LN lesions or seen in apparently healthy tissue of diseased colonies along with various parasites and other bacteria all considered likely secondary colonizers. Of the 82 samples showing gross lesions of SCTLD, 71 (87%) were confirmed histologically to have LN. Collectively, pathology indicates that SCTLD is the result of a disruption of host–symbiont physiology with lesions originating in the BBW leading to detachment and sloughing of tissues from the skeleton. Future investigations could focus on identifying the cause and pathogenesis of this process.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2020.576013","usgsCitation":"Landsberg, J., Kiryu, Y., Peters, E., Wilson, P., Waters, Y., Maxwell, K., Huebner, L., and Work, T.M., 2020, Stony coral tissue loss disease in Florida is associated with disruption of host–zooxanthellae physiology: Frontiers in Marine Science, v. 7, 576013, 24 p., https://doi.org/10.3389/fmars.2020.576013.","productDescription":"576013, 24 p.","ipdsId":"IP-122466","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":454646,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2020.576013","text":"Publisher Index Page"},{"id":383688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.167236328125,\n 27.371767300523047\n ],\n [\n -80.386962890625,\n 27.225325836903373\n ],\n [\n -80.15625,\n 26.470573022375085\n ],\n [\n -80.26611328125,\n 25.839449402063185\n ],\n [\n -80.44189453125,\n 25.27450351782018\n ],\n [\n -80.716552734375,\n 24.91633140459907\n ],\n [\n -82.08984375,\n 24.627044746156027\n ],\n [\n -81.88110351562499,\n 24.37712083961039\n ],\n [\n -80.760498046875,\n 24.647017162630366\n ],\n [\n -80.035400390625,\n 25.334096684794456\n ],\n [\n -79.9365234375,\n 26.56887654795065\n ],\n [\n -79.95849609375,\n 27.00040800352175\n ],\n [\n -80.167236328125,\n 27.371767300523047\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","noUsgsAuthors":false,"publicationDate":"2020-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Landsberg, Jan","contributorId":252919,"corporation":false,"usgs":false,"family":"Landsberg","given":"Jan","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiryu, Yasu","contributorId":252920,"corporation":false,"usgs":false,"family":"Kiryu","given":"Yasu","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peters, Esther","contributorId":252921,"corporation":false,"usgs":false,"family":"Peters","given":"Esther","affiliations":[{"id":50470,"text":"George Masson University","active":true,"usgs":false}],"preferred":false,"id":811124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Patrick","contributorId":252922,"corporation":false,"usgs":false,"family":"Wilson","given":"Patrick","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waters, Yvonne","contributorId":252923,"corporation":false,"usgs":false,"family":"Waters","given":"Yvonne","email":"","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811126,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maxwell, Kerry","contributorId":252924,"corporation":false,"usgs":false,"family":"Maxwell","given":"Kerry","email":"","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811127,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huebner, Lindsay","contributorId":252925,"corporation":false,"usgs":false,"family":"Huebner","given":"Lindsay","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811128,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":811129,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216871,"text":"sir20205091 - 2020 - Simulation of groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15","interactions":[],"lastModifiedDate":"2021-04-08T21:42:55.915848","indexId":"sir20205091","displayToPublicDate":"2020-12-16T09:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5091","displayTitle":"Simulation of Groundwater Flow in the Regional Aquifer System on Long Island, New York, for Pumping and Recharge Conditions in 2005–15","title":"Simulation of groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15","docAbstract":"A three-dimensional groundwater-flow model was developed for the aquifer system of Long Island, New York, to evaluate (1) responses of the hydrologic system to changes in natural and anthropogenic hydraulic stresses, (2) the subsurface distribution of groundwater age, and (3) the regional-scale distribution of groundwater travel times and the source of water to fresh surface waters and coastal receiving waters. The model also provides the groundwater flow components used to define model boundaries for possible inset models used for local-scale analyses.
The three-dimensional, groundwater flow model developed for this investigation uses the numerical code MODFLOW–NWT to represent steady-state conditions for average groundwater pumping and aquifer recharge for 2005–15. The particle-tracking algorithm MODPATH, which simulates advective transport in the aquifer, was used to estimate groundwater age, delineate the areas at the water table that contribute recharge to coastal and freshwater bodies, and estimate total travel times of water from the water table to discharge locations.
A three-dimensional, 1-meter (3.3-foot) topobathymetric model was used to determine land-surface altitudes for the island and seabed altitudes for the surrounding coastal waters. The mapped extents and surface altitudes of major geologic units were compiled and used to develop a three-dimensional hydrogeologic framework of the aquifer system, including aquifers and confining units. Lithologic data from deep boreholes and previous aquifer-test results were used to estimate the three-dimensional distribution of hydraulic conductivity in principal aquifers. Natural recharge from precipitation was estimated for 2005–15 using a modified Thornthwaite-Mather methodology as implemented in a soil-water balance model. Components of anthropogenic recharge—wastewater return flow, storm water inflow, and inflow from leaky infrastructure—also were estimated for 2005–15. Groundwater withdrawals for various sources, including public water supply, industrial, remediation, and agricultural, were compiled or estimated for the same period.
These data were incorporated into the model development to represent the aquifer system geometry, boundaries, and initial hydraulic properties of the regional aquifers and confining units within the Long Island aquifer system. Average hydraulic conditions—water levels and streamflows—for 2005–15 were estimated using existing data from the U.S. Geological Survey National Water Information System database. Model inputs were adjusted to best match average hydrologic conditions using inverse methods as implemented in the parameter-estimating software PEST. The calibrated model was used to simulate average hydrologic conditions in the aquifer system for 2005–15.
About 656 cubic feet per second of water was withdrawn on average annually for 2005–15 for water supply and an average of about 349 cubic feet per second of water recharged the aquifer annually from return flow and leaky infrastructure. Parts of New York City have drawdowns exceeding 25 feet, mostly because of urbanization and associated large decreases in recharge rates. Large areas in the western part of the island have drawdowns exceeding 10 feet, mostly from large groundwater withdrawals and sewering, which largely eliminates wastewater return flow. Water-table altitudes in eastern parts of the island increased by more than 2 feet in some areas as a result of wastewater return flow in unsewered areas and changes in land use. Changes in streamflows show a similar pattern as water-table altitudes. Streamflows generally decrease in western parts of the island where there are large drawdowns and increase in eastern parts of the island where water-table altitudes increase.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205091","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Walter, D.A., Masterson, J.P., Finkelstein, J.S., Monti, J., Jr., Misut, P.E., and Fienen, M.N., 2020, Simulation of groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15: U.S. Geological Survey Scientific Investigations Report 2020–5091, 75 p., https://doi.org/10.3133/sir20205091.","productDescription":"Report: ix, 75 p.; 3 Data Releases","numberOfPages":"75","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-112206","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":381521,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2020/5091/images/"},{"id":381195,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5091/sir20205091.pdf","text":"Report","size":"35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5091"},{"id":381194,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5091/coverthb2.jpg"},{"id":381192,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P954DLLC","text":"USGS data release","linkHelpText":"Aquifer texture data describing the Long Island aquifer system"},{"id":381191,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KWQSEJ","text":"USGS data release","linkHelpText":"MODFLOW–NWT and MODPATH6 used to simulate groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15"},{"id":381190,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90B6OTX","text":"USGS data release","linkHelpText":"Time domain electromagnetic surveys collected to estimate the extent of saltwater intrusion in Nassau and Queens Counties, New York, October-November 2017"},{"id":381520,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2020/5091/sir20205091.XML"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.102783203125,\n 40.55554790286311\n ],\n [\n -73.7017822265625,\n 40.49709237269567\n ],\n [\n -72.8778076171875,\n 40.65147128144057\n ],\n [\n -72.037353515625,\n 40.91351257612758\n ],\n [\n -71.6143798828125,\n 41.16211393939692\n ],\n [\n -71.9384765625,\n 41.178653972331674\n ],\n [\n -72.191162109375,\n 41.236511201246216\n ],\n [\n -72.65808105468749,\n 41.11660732012896\n ],\n [\n -73.4490966796875,\n 40.967455873296714\n ],\n [\n -73.751220703125,\n 40.89275342420696\n ],\n [\n -74.0203857421875,\n 40.718119379753446\n ],\n [\n -74.102783203125,\n 40.55554790286311\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
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10 Bearfoot Road
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Subduction zones drive plate tectonics on Earth, yet subduction initiation and the related upper plate depositional and structural kinematics remain poorly understood because upper plate records are rare and often strongly overprinted by magmatism and deformation. During the late Paleozoic time, Laurentia’s western margin was truncated by a sinistral strike-slip fault that transformed into a subduction zone. Thick Permian strata in the Inyo Mountains of central-eastern California record this transition. Two basins that were separated by a transpressional antiform contain sedimentary lithofacies that record distinct patterns of shoaling and deepening conditions before and during tectonism associated with subduction initiation. Sandstone petrography and lithofacies analysis show that rocks in a southeastern basin are dominated by carbonate grains derived from adjacent carbonate shelves, whereas sandstones in a northwestern basin are predominantly quartzose with likely derivation from distant ergs or underlying strata. Detrital zircon spectra from all but the youngest strata in both basins are typical of Laurentian continent spectra with prominent peaks that indicate ultimate sources in Appalachia, Grenville, Yavapai/Mazatzal, and the Wyoming or Superior cratons. The first Cordilleran arc-derived detrital zircon grains appear in the uppermost strata of the northwestern basin and record Late Permian (ca. 260 Ma) Cordilleran arc magmatism at this approximate latitude, and a possible source area is suggested by geochemical similarities between these detrital zircons and broadly coeval magmatic zircons in the El Paso Mountains to the southwest. Deformation responsible for basin partitioning is consistent with sinistrally oblique contraction in the earliest Permian time. The data presented from the Inyo Mountains shed more light on the nature of Cordilleran subduction initiation and the upper-crustal response to this transition.
Inlet-interrupted sandy coasts are dynamic and complex coastal systems with continuously evolving geomorphological behaviors under the influences of both climate change and human activities. These coastal systems are of great importance to society (e.g., providing habitats, navigation, and recreational activities) and are affected by both oceanic and terrestrial processes. Therefore, the evolution of these inlet-interrupted coasts is better assessed by considering the entirety of the Catchment-Estuary-Coastal (CEC) systems, under plausible future scenarios for climate change and increasing pressures due to population growth and human activities. Such a holistic assessment of the long-term evolution of CEC systems can be achieved via reduced-complexity modeling techniques, which are also ably quantifying the uncertainties associated with the projections due to their lower simulation times. Here, we develop a novel probabilistic modeling framework to quantify the input-driven uncertainties associated with the evolution of CEC systems over the 21st century. In this new approach, probabilistic assessment of the evolution of inlet-interrupted coasts is achieved by (1) probabilistically computing the exchange sediment volume between the inlet-estuary system and its adjacent coast, and (2) distributing the computed sediment volumes along the inlet-interrupted coast. The model is applied at three case study sites: Alsea estuary (United States), Dyfi estuary (United Kingdom), and Kalutara inlet (Sri Lanka). Model results indicate that there are significant uncertainties in projected volume exchange at all the CEC systems (min-max range of 2.0 million cubic meters in 2100 for RCP 8.5), and the uncertainties in these projected volumes illustrate the need for probabilistic modeling approaches to evaluate the long-term evolution of CEC systems. A comparison of 50th percentile probabilistic projections with deterministic estimates shows that the deterministic approach overestimates the sediment volume exchange in 2100 by 15–30% at Alsea and Kalutara estuary systems. Projections of coastline change obtained for the case study sites show that accounting for all key processes governing coastline change along inlet-interrupted coasts in computing coastline change results in projections that are between 20 and 134% greater than the projections that would be obtained if only the Bruun effect were taken into account, underlining the inaccuracies associated with using the Bruun rule at inlet-interrupted coasts.
Effective volcanic hazard management in regions where populations live in close proximity to persistent volcanic activity involves understanding the dynamic nature of hazards, and associated risk. Emphasis until now has been placed on identification and forecasting of the escalation phase of activity, in order to provide adequate warning of what might be to come. However, understanding eruption hiatus and post-eruption unrest hazards, or how to quantify residual hazard after the end of an eruption, is also important and often key to timely post-eruption recovery. Unfortunately, in many cases when the level of activity lessens, the hazards, although reduced, do not necessarily cease altogether. This is due to both the imprecise nature of determination of the “end” of an eruptive phase as well as to the possibility that post-eruption hazardous processes may continue to occur. An example of the latter is continued dome collapse hazard from lava domes which have ceased to grow, or sector collapse of parts of volcanic edifices, including lava dome complexes. We present a new probabilistic model for forecasting pyroclastic density currents (PDCs) from lava dome collapse that takes into account the heavy-tailed distribution of the lengths of eruptive phases, the periods of quiescence, and the forecast window of interest. In the hazard analysis, we also consider probabilistic scenario models describing the flow’s volume and initial direction. Further, with the use of statistical emulators, we combine these models with physics-based simulations of PDCs at Soufrière Hills Volcano to produce a series of probabilistic hazard maps for flow inundation over 5, 10, and 20 year periods. The development and application of this assessment approach is the first of its kind for the quantification of periods of diminished volcanic activity. As such, it offers evidence-based guidance for dome collapse hazards that can be used to inform decision-making around provisions of access and reoccupation in areas around volcanoes that are becoming less active over time.
This paper provides an overview of past, present and future themes for research and management of riparian zones, often relating to papers within this Wetlands Special Feature. Riparian research expanded in the United States around 1980 with themes that recognized (1) damage from excessive livestock, or (2) damage from river damming and diversion, and (3) the beneficial capacity of riparian buffers to intercept and assimilate nutrients and other water contaminants. Research expanded globally in the 1990s, with themes including (4) plant life history requirements and (5) reliance on fluvial geomorphic dynamics that enable riparian rejuvenation. Resource managers recognized that riparian areas provide (6) rich wildlife habitats (7) along with valued ecosystem services, (8) which encouraged conservation and restoration initiatives, (9) including environmental flow regimes. Floodplains are (10) vulnerable to invasive plants and management has included biocontrol such as for Tamarix in the American Southwest. Into the twenty-first century, (11) climate change is advancing, and riparian ecosystems may be especially impacted due to the compound challenges from increasing water demand and declining summer flows. As an emerging opportunity, (12) while reservoirs submerge floodplain vegetation, reservoir deltas may support compensatory riparian wetlands. (13) Studies increasingly utilize remote sensing tools including satellite imagery, LiDAR and unmanned aircraft systems, and (14) the coordination of large data sets invites digital ecology, including artificial intelligence and machine learning. Since riparian zones are centres for human activities, (15) there are opportunities for citizen science, social media and internet applications, which will increasingly democratize riparian research and management.
The maps and graphs in this summary describe national streamflow conditions for water year 2019 (October 1, 2018, to September 30, 2019) in the context of streamflow ranks relative to the 90-year period of water years 1930–2019. Annual runoff in the Nation’s rivers and streams during water year 2019 (13.62 inches) was much higher than the long-term (1930–2019) mean annual runoff of 9.37 inches for the contiguous United States. Nationwide, the 2019 streamflow ranked the highest out of the 90 years.
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415 National Center
Reston, VA 20192
About one-quarter of the water supply for the Village of Ruidoso, New Mexico, is from groundwater pumped from wells located along North Fork Eagle Creek in the National Forest System lands of the Lincoln National Forest near Alto, New Mexico. Because of concerns regarding the effects of groundwater pumping on surface-water hydrology in the North Fork Eagle Creek Basin and the effects of the 2012 Little Bear Fire, which resulted in substantial loss of vegetation in the basin, the U.S. Department of Agriculture Forest Service, Lincoln National Forest, has required monitoring of a portion of North Fork Eagle Creek for short-term geomorphic change as part of the permitting decision that allows for the continued pumping of the production wells. The objective of this study is to address the geomorphic monitoring requirements of the permitting decision by conducting annual geomorphic surveys of North Fork Eagle Creek along the stream reach between the North Fork Eagle Creek near Alto, New Mexico, streamflow-gaging station (U.S. Geological Survey [USGS] site 08387550) and the Eagle Creek below South Fork near Alto, New Mexico, streamflow-gaging station (USGS site 08387600). The monitoring of short-term geomorphic change in the stream reach began in June 2017 with surveys of select cross sections and surveys of all woody debris accumulations and pools found in the channel. In June 2018, the monitoring of short-term geomorphic change continued with another geomorphic survey of the stream reach (with some modification to the monitoring methods).
The 2017 and 2018 surveys were conducted by the USGS, in cooperation with the Village of Ruidoso, and were the first two in a planned series of five annual geomorphic surveys. The results of the 2017 geomorphic survey were summarized and interpreted in a previous USGS Open-File Report, and the data were published in the companion data release of that report. In this report, the results of the 2018 geomorphic survey are summarized, interpreted, and compared to the results of the 2017 survey. The data from the 2018 geomorphic survey are published in the companion data release of this report.
The study reach surveyed in June 2018 is 1.89 miles long, beginning about 260 feet upstream from the North Fork Eagle Creek near Alto, New Mexico, streamflow-gaging station and ending at the Eagle Creek below South Fork near Alto, New Mexico, streamflow-gaging station. Large sections of the study reach are characterized by intermittent streamflow, and where streamflow is normally continuous (including at the upper and lower portions of the study reach, near the streamflow-gaging stations), the streamflow typically remains less than 2 cubic feet per second throughout the year except during seasonal high flows, which most often result from rainfall during the North American monsoon months of July, August, and September or from snowmelt runoff in March, April, and May. Between the 2017 and 2018 surveys, high-flow events resulting from both rainfall (during the North American monsoon season) and snowmelt runoff (during the winter) occurred in the study reach, and those high-flow events appeared to have caused some minor and localized geomorphic changes in the study reach, which were evaluated through comparison of the 2017 and 2018 survey results.
For the 2017 geomorphic survey of North Fork Eagle Creek, cross sections were established and surveyed at 14 locations along the study reach, and in 2018, those same 14 cross sections were resurveyed. Comparisons of the cross-section survey results indicated that minor observable geomorphic changes had occurred in 3 of the 14 cross sections. These minor observable geomorphic changes included aggradation or degradation of surface materials by about 1–2 feet in some parts of the affected cross sections.
To further assess geomorphic changes within the study reach, other features, including woody debris accumulations and pools, were surveyed in both 2017 and 2018. During the 2018 geomorphic survey, 112 distinct accumulations of woody debris and 71 pools were identified in the study reach. Charred wood or burn-marked wood was present in at least 17 of the identified woody debris accumulations (and was present in some of the woody debris accumulations identified during the 2017 survey), indicating that some of the woody debris in the channel may have been sourced from trees or forest litter that had burned during 2012 Little Bear Fire. Only 22 of the 112 woody debris accumulations identified during the 2018 survey were certain to have also been present during the 2017 survey (when 58 woody debris accumulations were identified), indicating that most of the woody debris accumulations surveyed in 2017 were likely transported during the high-flow events between the 2017 and 2018 surveys but also indicating that the flows during those events were not high enough to remove some of the more firmly anchored woody debris accumulations. Most woody debris accumulations identified in 2018 did not appear to have substantially influenced geomorphic change in the locations where they were found. However, the formation of 10 of the 71 pools identified in the study reach in 2018 appeared to have been influenced by the presence of woody debris, indicating that some woody debris accumulations may have driven local geomorphic changes. Notably, pool totals from the 2017 survey could not be accurately compared to the pool totals from the 2018 survey because of differences between the two surveys in the methods used to identify pools.
Because the study began 5 years after the 2012 Little Bear Fire, and because the period and geomorphic scope of the study have so far been limited, it cannot be said that the geomorphic changes observed between the 2017 and 2018 surveys are representative of a pattern of geomorphic change following the 2012 Little Bear Fire. Though, once geomorphic changes between the 2017 and 2018 surveys can be compared with results from geomorphic surveys planned for 2019, 2020, and 2021, it may be possible to develop an understanding of the patterns in geomorphic change following the 2012 Little Bear Fire.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201121","collaboration":"Prepared in cooperation with the Village of Ruidoso, New Mexico","usgsCitation":"Graziano, A.P., 2020, Geomorphic survey of North Fork Eagle Creek, New Mexico, 2018: U.S. Geological Survey Open-File Report 2020–1121, 37 p., https://doi.org/10.3133/ofr20201121.","productDescription":"Report: v, 37 p.; Data Release","numberOfPages":"47","onlineOnly":"Y","ipdsId":"IP-112737","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":381235,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1121/ofr20201121.pdf","text":"Report","size":"16.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1121"},{"id":381236,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94ZQHKU","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data supporting the 2018 geomorphic survey of North Fork Eagle Creek, New Mexico"},{"id":381234,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1121/coverthb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"North Fork Eagle Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.5621337890625,\n 32.99023555965106\n ],\n [\n -104.7930908203125,\n 32.99023555965106\n ],\n [\n -104.7930908203125,\n 33.770015152780125\n ],\n [\n -105.5621337890625,\n 33.770015152780125\n ],\n [\n -105.5621337890625,\n 32.99023555965106\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Management of stressors requires an understanding of how multiple stressors interact, how different species respond to those interactions and the underlying mechanisms driving observed patterns in species' responses. Salinization and rising temperatures are two pertinent stressors predicted to intensify in freshwater ecosystems, posing concern for how susceptible organisms achieve and maintain homeostasis (i.e. allostasis). Here, glucocorticoid hormones (e.g. cortisol), responsible for mobilizing energy (e.g. glucose) to relevant physiological processes for the duration of stressors, are liable to vary in response to the duration and severity of salinization and temperature rises. With field and laboratory studies, we evaluated how both salinity and temperature influence basal and stress-reactive cortisol and glucose levels in age 1+ mottled sculpin (Cottus bairdii), mountain sucker (Catostomus platyrhynchus) and Colorado River cutthroat trout (Oncorhynchus clarki pleuriticus). We found that temperature generally had the greatest effect on cortisol and glucose concentrations and the effect of salinity was often temperature dependent. We also found that when individuals were chronically exposed to higher salinities, baseline concentrations of cortisol and glucose usually declined as salinity increased. Reductions in baseline concentrations facilitated stronger stress reactivity for cortisol and glucose when exposed to additional stressors, which weakened as temperatures increased. Controlled temperatures near the species' thermal maxima became the overriding factor regulating fish physiology, resulting in inhibitory responses. With projected increases in freshwater salinization and temperatures, efforts to reduce the negative effects of increasing temperatures (i.e. increased refuge habitats and riparian cover) could moderate the inhibitory effects of temperature-dependent effects of salinization for freshwater fishes.
","language":"English","publisher":"Springer","doi":"10.1093/conphys/coaa107","usgsCitation":"Walker, R.H., Smith, G.D., Hudson, S.B., Susannah S. French, S.S., and Walters, A.W., 2020, Warmer temperatures interact with salinity to weaken physiological facilitation to stress in freshwater fishes: Conservation Physiology, v. 8, no. 1, coaa107, 18 p., https://doi.org/10.1093/conphys/coaa107.","productDescription":"coaa107, 18 p.","ipdsId":"IP-109141","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":454658,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coaa107","text":"Publisher Index Page"},{"id":436697,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IBV1RJ","text":"USGS data release","linkHelpText":"Salinity-temperature Interactions on Freshwater Fish Physiology (2015-2018)"},{"id":395556,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Upper Green River basin, Wyoming Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.73556518554688,\n 42.703632059618045\n ],\n [\n -109.8193359375,\n 42.67536823702857\n ],\n [\n -109.90859985351561,\n 42.62385465855651\n ],\n [\n -110.07064819335938,\n 42.53689200787317\n ],\n [\n -110.14068603515625,\n 42.48728928565912\n ],\n [\n -110.12763977050781,\n 42.407234661551875\n ],\n [\n -110.14892578125,\n 42.36158819524629\n ],\n [\n -110.2313232421875,\n 42.259016415705766\n ],\n [\n -110.20111083984375,\n 42.18579390537848\n ],\n [\n -110.20523071289061,\n 42.12674735753131\n ],\n [\n -110.14892578125,\n 41.98603585974727\n ],\n [\n -109.92095947265625,\n 41.90636538970964\n ],\n [\n -109.77539062499999,\n 41.72828028223453\n ],\n [\n -109.5391845703125,\n 41.45301999377133\n ],\n [\n -109.54193115234374,\n 41.3500103516271\n ],\n [\n -109.4073486328125,\n 41.29431726315258\n ],\n [\n -109.28375244140625,\n 41.413895564677304\n ],\n [\n -109.5611572265625,\n 41.84910468610387\n ],\n [\n -110.04180908203124,\n 42.338244963350846\n ],\n [\n -109.86328125,\n 42.559149812115876\n ],\n [\n -109.6490478515625,\n 42.68041629144619\n ],\n [\n -109.73556518554688,\n 42.703632059618045\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Walker, Richard H.","contributorId":274736,"corporation":false,"usgs":false,"family":"Walker","given":"Richard","email":"","middleInitial":"H.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":833270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Geoffrey D.","contributorId":274737,"corporation":false,"usgs":false,"family":"Smith","given":"Geoffrey","email":"","middleInitial":"D.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":833271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hudson, Spencer B","contributorId":274740,"corporation":false,"usgs":false,"family":"Hudson","given":"Spencer","email":"","middleInitial":"B","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":833272,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Susannah S. French, Susannah S.","contributorId":274743,"corporation":false,"usgs":false,"family":"Susannah S. French","given":"Susannah","email":"","middleInitial":"S.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":833273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833269,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70225719,"text":"70225719 - 2020 - Density dependence and adult survival drive the dynamics in two high elevation amphibian populations","interactions":[],"lastModifiedDate":"2021-11-04T14:37:39.384923","indexId":"70225719","displayToPublicDate":"2020-12-15T09:25:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Density dependence and adult survival drive the dynamics in two high elevation amphibian populations","docAbstract":"Amphibian conservation has progressed from the identification of declines to mitigation, but efforts are hampered by the lack of nuanced information about the effects of environmental characteristics and stressors on mechanistic processes of population regulation. Challenges include a paucity of long-term data and scant information about the relative roles of extrinsic (e.g., weather) and intrinsic (e.g., density dependence) factors. We used a Bayesian formulation of an open population capture-recapture model and >30 years of data to examine intrinsic and extrinsic factors regulating two adult boreal chorus frogs (Pseudacris maculata) populations. We modelled population growth rate and apparent survival directly, assessed their temporal variability, and derived estimates of recruitment. Populations were relatively stable (geometric mean population growth rate >1) and regulated by negative density dependence (i.e., higher population sizes reduced population growth rate). In the smaller population, density dependence also acted on adult survival. In the larger population, higher population growth was associated with warmer autumns. Survival estimates ranged from 0.30–0.87, per-capita recruitment was <1 in most years, and mean seniority probability was >0.50, suggesting adult survival is more important to population growth than recruitment. Our analysis indicates density dependence is a primary driver of population dynamics for P. maculata adults.
","language":"English","publisher":"MDPI","doi":"10.3390/d12120478","usgsCitation":"Kissel, A.M., Tenan, S., and Muths, E.L., 2020, Density dependence and adult survival drive the dynamics in two high elevation amphibian populations: Diversity, v. 12, no. 12, 478, 15 p., https://doi.org/10.3390/d12120478.","productDescription":"478, 15 p.","ipdsId":"IP-122660","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":454660,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d12120478","text":"Publisher Index Page"},{"id":436698,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9229ZLM","text":"USGS data release","linkHelpText":"Chorus frog density and population growth, Cameron Pass, Colorado, 1986-2020"},{"id":391386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Lily Pond, Matthews Pond","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.86,\n 40.6\n ],\n [\n -105.82,\n 40.6\n ],\n [\n -105.82,\n 40.56\n ],\n [\n -105.86,\n 40.56\n ],\n [\n -105.86,\n 40.6\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kissel, Amanda M.","contributorId":211917,"corporation":false,"usgs":false,"family":"Kissel","given":"Amanda","email":"","middleInitial":"M.","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":826397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tenan, Simone","contributorId":177519,"corporation":false,"usgs":false,"family":"Tenan","given":"Simone","email":"","affiliations":[],"preferred":false,"id":826398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":826396,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228740,"text":"70228740 - 2020 - Use of remote sensing tools to predict focal areas for sea turtle conservation in the Southwestern Atlantic","interactions":[],"lastModifiedDate":"2022-02-17T15:10:38.050995","indexId":"70228740","displayToPublicDate":"2020-12-15T09:05:47","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Use of remote sensing tools to predict focal areas for sea turtle conservation in the Southwestern Atlantic","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Soil and water conservation: A celebration of 75 years","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Soil and Water Conservation Society","usgsCitation":"Mushet, D.M., and Aram Calhoun, 2020, Wetland conservation in the United States: A swinging pendulum, chap. 14 of Soil and water conservation: A celebration of 75 years, p. 162-171.","productDescription":"10 p.","startPage":"162","endPage":"171","ipdsId":"IP-115447","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":381440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381426,"type":{"id":15,"text":"Index Page"},"url":"https://www.swcs.org/resources/publications/soil-and-water-conservation-a-celebration-of-75-years"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":807027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aram Calhoun","contributorId":245784,"corporation":false,"usgs":false,"family":"Aram Calhoun","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":807028,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216899,"text":"ofr20201140 - 2020 - Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2019","interactions":[],"lastModifiedDate":"2020-12-15T19:44:17.549778","indexId":"ofr20201140","displayToPublicDate":"2020-12-15T08:17:17","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":"2020-1140","displayTitle":"Continuous Stream Discharge, Salinity, and Associated Data Collected in the Lower St. Johns River and Its Tributaries, Florida, 2019","title":"Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2019","docAbstract":"The U.S. Army Corps of Engineers, Jacksonville District, is deepening the St. Johns River channel in Jacksonville, Florida, from 40 to 47 feet along 13 miles of the river channel beginning at the mouth of the river at the Atlantic Ocean, in order to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, monitored stage, discharge, and (or) water temperature and salinity at 26 continuous data collection stations in the St. Johns River and its tributaries.
This is the fourth annual report by the U.S. Geological Survey on data collection for the Jacksonville Harbor deepening project. The report contains information pertinent to data collection during the 2019 water year, from October 2018 to September 2019. No changes to the previously installed data collection network were made during this period.
Discharge and salinity varied widely during the data collection period, which included above-average rainfall for all counties in the study area over the 3-month period from November to January, below-average annual rainfall for all counties, and effects from Hurricane Dorian in September 2019. Total annual rainfall for all counties ranked third among the annual totals computed for the 4 years considered for this study. Annual mean discharge at Durbin Creek was highest among the tributaries, followed by Trout River, Ortega River, Julington Creek, Pottsburg Creek, Broward River, Cedar River, Clapboard Creek, and Dunn Creek. The annual mean discharge for each of the main-stem sites was lower for the 2019 water year than for the 2018 water year. Since the beginning of the study in 2016, the St. Johns River at Astor station computed its lowest annual mean discharge, the Jacksonville station recorded its second lowest, and the Buffalo Bluff station recorded its second highest in 2019.
Among the tributary sites, annual mean salinity was highest at Clapboard Creek, the site closest to the Atlantic Ocean, and was lowest at Durbin Creek, the site farthest from the ocean. Annual mean salinity data from the main-stem sites on the St. Johns River indicate that salinity decreased with distance upstream from the ocean, which was expected. Relative to annual mean salinity calculated for the 2018 water year, annual mean salinity at all monitoring locations was higher for the 2019 water year except at the main-stem site below Shands Bridge and at the tributary sites of Durbin Creek and Julington Creek, which remained the same. The 2019 annual mean salinity at Dunn Creek was the highest on record for that site, and Clapboard Creek and Trout River were the second highest on record for those sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201140","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Ryan, P.J., 2020, Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2019: U.S. Geological Survey Open-File Report 2020–1140, 48 p., https://doi.org/10.3133/ofr20201140.","productDescription":"ix, 48 p.","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-118214","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":381275,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1140/coverthb.jpg"},{"id":381276,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1140/ofr20201140.pdf","text":"Report","size":"7.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1140"}],"country":"United States","state":"Florida","otherGeospatial":"St John's River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.93878173828125,\n 29.1161749329972\n ],\n [\n -81.4691162109375,\n 29.1161749329972\n ],\n [\n -81.4691162109375,\n 30.545704405480997\n ],\n [\n -81.93878173828125,\n 30.545704405480997\n ],\n [\n -81.93878173828125,\n 29.1161749329972\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559