Since 2014, corals throughout Florida’s Coral Reef have been plagued by an epizootic of unknown etiology, colloquially termed stony coral tissue loss disease (SCTLD). Although in Florida the movement of this waterborne coral disease has been consistent with natural transport via water currents, outbreaks in the Caribbean have been more sporadic, with infections occurring in locations inconsistent with spread via natural means. Often Caribbean outbreaks have been clustered near ports, potentially implicating ships as mediators of SCTLD into new regions. Biofilms attached to ship hulls, ballast tank walls, or other surfaces could represent a possible vector for the disease. We investigated whether bacteria shed by healthy and SCTLD-diseased corals would form distinct biofilms, and whether a SCTLD signal would be detectable within biofilm bacterial communities. Stainless steel plates serving as proxies for ship hulls, ballast tank walls, and other colonizable surfaces were incubated for three days in filtered seawater mesocosms containing healthy or SCTLD-infected corals. Resulting biofilm bacterial communities were characterized through sequencing of the V4 region of the 16S rRNA gene. We determined that bacteria shed by healthy and diseased corals formed significantly different biofilms consisting of highly diverse taxa. Comparison with 16S data from previous SCTLD investigations spanning different coral species, collection locations, years, and source material revealed the presence of numerous genetically identical sequences within the biofilm bacterial communities formed during exposure to SCTLD-infected corals, including several previously identified as possible SCTLD bioindicators. These results suggest ship-associated biofilms may have the potential to be vectors for the transmission of SCTLD into new regions.
Recent studies have documented benefits of small, prescribed fire and wildfire for grassland-dependent wildlife, such as lesser prairie-chickens (Tympanuchus pallidicintus), but wildlife demographic response to the scale and intensity of megafire (wildfire >40,000 ha) in modern, fragmented grasslands remains unknown. Limited available grassland habitat makes it imperative to understand if increasing frequency of megafires could further reduce already declining lesser prairie-chicken populations, or if historical evolutionary interactions with fire make lesser prairie-chickens resilient. To evaluate lesser prairie-chicken demographic response to megafires, we compared lek counts, nest density, and survival rates of adults, nests, and chicks before (2014–2016) and after (2018–2020) a 2017 megafire in the mixed-grass prairie of Kansas, USA (Starbuck fire ~254,000 ha). There was a 67% decline in attending males on leks post-fire and a 57% decline in occupied leks post-fire. Despite population declines as indicated by lek counts, adult female breeding season survival (Ŝ) was similar pre- (Ŝ = 0.65 ± 0.08 [SE]) and post-fire (0.61 ± 0.08), as was chick survival (pre-fire: 0.23 ± 0.07; post-fire: 0.27 ± 0.11). Nest survival appeared lower post-fire (pre-fire: 0.38 ± 0.06; post-fire: 0.20 ± 0.06), but did not differ at the 95% confidence interval. Nest density of marked females declined 73% in areas burned by megafire. Although lesser prairie-chickens persisted in the study area and we documented minimal effects on most demographic rates, reduced lesser prairie-chicken abundance and reproductive output suggests full recovery may take >3 years. Increased propensity for megafire resulting from suppression of smaller fires, compounded by climate change and woody encroachment, may impose a short-term (3–5 year) threat to already declining lesser prairie-chicken populations.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.9544","usgsCitation":"Parke, N.J., Sullin, D.S., Haukos, D.A., Fricke, K., Hagen, C., and Ahlers, A.A., 2022, Demographic effects of a megafire on a declining prairie grouse in the mixed-grass prairie: Ecology and Evolution, v. 12, no. 12, e9544, 16 p., https://doi.org/10.1002/ece3.9544.","productDescription":"e9544, 16 p.","ipdsId":"IP-142934","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445778,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.9544","text":"Publisher Index Page"},{"id":432681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -101.54073970102226,\n 37.75193745545033\n ],\n [\n -101.54073970102226,\n 36.24283843115835\n ],\n [\n -98.50851313852192,\n 36.24283843115835\n ],\n [\n -98.50851313852192,\n 37.75193745545033\n ],\n [\n -101.54073970102226,\n 37.75193745545033\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Parke, Nicholas J.","contributorId":341309,"corporation":false,"usgs":false,"family":"Parke","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullin, Daniel S.","contributorId":341310,"corporation":false,"usgs":false,"family":"Sullin","given":"Daniel","email":"","middleInitial":"S.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":908217,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fricke, Kent A.","contributorId":341311,"corporation":false,"usgs":false,"family":"Fricke","given":"Kent A.","affiliations":[{"id":81167,"text":"Kansas Department of Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":908218,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hagen, Christian A.","contributorId":341312,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian A.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":908219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ahlers, Adam A.","contributorId":341313,"corporation":false,"usgs":false,"family":"Ahlers","given":"Adam","email":"","middleInitial":"A.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908220,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238360,"text":"sir20225096 - 2022 - Hydrology, water quality, and biological characteristics of Levittown Lake, Toa Baja, Puerto Rico, April 2010–June 2011","interactions":[],"lastModifiedDate":"2023-03-01T14:02:20.350129","indexId":"sir20225096","displayToPublicDate":"2022-11-29T13:35:24","publicationYear":"2022","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":"2022-5096","displayTitle":"Hydrology, Water Quality, and Biological Characteristics of Levittown Lake, Toa Baja, Puerto Rico, April 2010–June 2011","title":"Hydrology, water quality, and biological characteristics of Levittown Lake, Toa Baja, Puerto Rico, April 2010–June 2011","docAbstract":"Levittown Lake is a 30-hectare, brackish waterbody located in the municipality of Toa Baja, on the northern coast of Puerto Rico. The lake is a small, man-made feature formed by draining the marshland over which the Levittown community was built. Levittown Lake has an average depth of about 5 meters and a water level at/near mean sea level. Tidal oscillations within the lake were minimal during the study, about 10 centimeters regardless of ocean tides, and the daily flushing rate of the lake was about 2 percent of its entire water volume.
Hydrologic, water-quality, and biological data were collected in Levittown Lake and adjacent areas (specifically, the inlet/outlet channel and Caño El Hato drainage canal) between April 2010 and June 2011 (1) to establish baseline conditions and determine the water quality of the lake on the basis of preestablished standards and (2) for contrast with other, more healthy coastal lagoons. The study provides a baseline for an assessment of the potential of Levittown Lake to function as a coastal lagoon.
Water-quality properties measured onsite (temperature, pH, dissolved oxygen concentration, specific conductance, salinity, and water transparency) varied diurnally and seasonally. In general, water-quality properties were in compliance with current regulatory Class SB standards established by the Puerto Rico Environmental Quality Board, except for some dissolved oxygen concentration and pH measurements. Some dissolved oxygen concentration measurements at the water surface and all dissolved oxygen concentration measurements at the lake bottom were lower than the values recommended by the Puerto Rico Environmental Quality Board. The pH of the water at the lake surface ranged from 7.3 to 9.1, with the upper value exceeding the recommended pH values. Nutrient concentrations were below the current regulatory standards of less than 5 milligrams per liter (mg/L) for total nitrogen and 1 mg/L for total phosphorus. The measured concentrations of chlorophyll a varied throughout the year of sampling and indicate that eutrophic conditions predominate in Levittown Lake.
The phytoplankton yielded an average net productivity of 0.5 milligram of oxygen per liter per hour, as determined by light and dark bottle primary productivity studies conducted on a monthly basis and measured in the early morning hours. Because these measurements were restricted to the morning hours, a qualification of the representativeness of the results to the full diurnal cycle is necessary. The measured hourly respiration rate averaged 0.39 milligram of oxygen per liter. Diel studies were planned in the lake to assess dissolved oxygen concentration diurnal curves and ultimately to compute the community net primary productivity, respiration, and gross productivity. Conditions during the diel studies were later determined to be unsuitable, limiting the assessment of community metabolism. Another biological indicator evaluated during the study was the phytoplankton biomass, and results indicated that phytoplankton biomass measured at the Levittown Lake ranged from 6.0 to 112.5 mg/L.
Fecal indicator bacteria concentrations ranged from 10 to 1,540,000 colonies per 100 milliliters of water. Concentrations generally were greatest in and near the Caño El Hato drainage canal and, during the study, exceeded current regulatory standards established for Puerto Rico.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225096","issn":"2328-0328","collaboration":"Prepared in cooperation with the Puerto Rico Department of Natural and Environmental Resources","usgsCitation":"Soler-López, L.R., Gómez-Fragoso, J.M., and Val-Merníz, N.A., 2022, Hydrology, water quality, and biological characteristics of Levittown Lake, Toa Baja, Puerto Rico, April 2010–June 2011: U.S. Geological Survey Scientific Investigations Report 2022–5096, 32 p., https://doi.org/10.3133/sir20225096.","productDescription":"Report: vii, 32 p.; Data Release; Dataset","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-064860","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":409442,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MC6JZ6","text":"USGS data release","linkHelpText":"Data for the hydrologic and water-quality characterization of Levittown Lake, Toa Baja, Puerto Rico, April 2010–June 2011"},{"id":409802,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225096/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":409439,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5096/sir20225096.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5096"},{"id":409438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5096/coverthb.jpg"},{"id":409440,"rank":2,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5096/sir20225096.XML"},{"id":409441,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5096/images"},{"id":409443,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"}],"country":"United States","state":"Puerto Rico","otherGeospatial":"Levittown Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -66.20418646107952,\n 18.468480510318614\n ],\n [\n -66.20418646107952,\n 18.43267147514682\n ],\n [\n -66.16780969765956,\n 18.43267147514682\n ],\n [\n -66.16780969765956,\n 18.468480510318614\n ],\n [\n -66.20418646107952,\n 18.468480510318614\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
More than 840 publications, 575 data releases, and 330 project web pages from the U.S. Geological Survey (USGS) pertain to the Colorado River Basin. Limited interconnections between Colorado River Basin publications, data, and web pages restrict the ability to synthesize and interpret scientific resources. Currently, these pieces are spread across multiple isolated locations, internal systems, data repositories, and local offices. The increasing size, complexity, and diversity of Colorado River Basin data creates additional need for integration. These different data types—including discrete, continuous, aerial, remote sensing, geophysical, geospatial, and other types in varied formats—are collected over numerous time and space scales and require data-intensive science and technology to integrate.
Information management technology (IMT) resources are enterprise capabilities that the USGS workforce can leverage at multiple scales with consistent interoperable solutions to better facilitate integrated science. The USGS 21st Century Science Strategy directs the USGS to establish enterprise IMT capabilities that support integrated work through interoperable software and database solutions at multiple scales. This Information Management Technology Plan identifies nine steps to leverage new and existing technologies, data, models, and scientific knowledge to support integrated science projects conducted across the Colorado River Basin. These steps are transferable to integrated-science studies in other locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223051","usgsCitation":"Anderson, E.D, Erxleben, J.R., Qi, S.L., Monroe, A.P., and Dahm, K.G., 2022, U.S. Geological Survey Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST)—Information Management Technology Plan: U.S. Geological Survey Fact Sheet 2022-3051, 4 p., https://doi.org/10.3133/fs20223051.","productDescription":"4 p.","onlineOnly":"Y","ipdsId":"IP-132808","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":64844,"text":"Rocky Mountain Region Director’s Office","active":true,"usgs":true}],"links":[{"id":409861,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20223051/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2022-3051"},{"id":409757,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3051/coverthb.jpg"},{"id":409758,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3051/fs20223051.pdf","text":"Report","size":"1.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3051"},{"id":409760,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20223010","text":"USGS Fact Sheet 2022-3010—","linkHelpText":"Addressing Stakeholder Science Needs for Integrated Drought Science in the Colorado River Basin Fact Sheet 2022-3010"},{"id":409803,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3051/images"},{"id":409804,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3051/fs20223051.xml"}],"country":"United States","state":"Arizona, Colorado, Nevada, New Mexico, Utah, Wyoming","otherGeospatial":"Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.00488281250001,\n 32.65787573695528\n ],\n [\n -114.78515624999999,\n 31.840232667909365\n ],\n [\n -113.99414062499999,\n 31.541089879585808\n ],\n [\n -113.2470703125,\n 31.015278981711266\n ],\n [\n -112.0166015625,\n 30.14512718337613\n ],\n [\n -110.654296875,\n 29.878755346037977\n ],\n [\n -109.86328125,\n 29.99300228455108\n ],\n [\n -108.720703125,\n 30.600093873550072\n ],\n [\n -108.28125,\n 31.653381399664\n ],\n [\n -108.28125,\n 32.54681317351514\n ],\n [\n -107.9736328125,\n 33.87041555094183\n ],\n [\n -107.40234375,\n 34.23451236236987\n ],\n [\n -106.9189453125,\n 35.88905007936091\n ],\n [\n -106.69921875,\n 36.35052700542763\n ],\n [\n -106.3916015625,\n 37.23032838760387\n ],\n [\n -106.3916015625,\n 38.272688535980976\n ],\n [\n -106.3916015625,\n 39.13006024213511\n ],\n [\n -106.12792968749999,\n 40.84706035607122\n ],\n [\n -106.3037109375,\n 41.47566020027821\n ],\n [\n -107.09472656249999,\n 41.96765920367816\n ],\n [\n -108.67675781249999,\n 42.32606244456202\n ],\n [\n -109.7314453125,\n 43.03677585761058\n ],\n [\n -110.654296875,\n 43.45291889355465\n ],\n [\n -111.09374999999999,\n 43.389081939117496\n ],\n [\n -111.1376953125,\n 42.61779143282346\n ],\n [\n -111.005859375,\n 42.16340342422401\n ],\n [\n -110.830078125,\n 41.376808565702355\n ],\n [\n -111.0498046875,\n 40.51379915504413\n ],\n [\n -111.4013671875,\n 39.740986355883564\n ],\n [\n -111.533203125,\n 37.68382032669382\n ],\n [\n -112.19238281249999,\n 37.43997405227057\n ],\n [\n -113.203125,\n 37.3002752813443\n ],\n [\n -114.2138671875,\n 37.37015718405753\n ],\n [\n -114.521484375,\n 38.20365531807149\n ],\n [\n -115.13671875,\n 38.51378825951165\n ],\n [\n -115.400390625,\n 37.16031654673677\n ],\n [\n -115.1806640625,\n 35.92464453144099\n ],\n [\n -114.82910156249999,\n 34.994003757575776\n ],\n [\n -114.697265625,\n 33.7243396617476\n ],\n [\n -115.00488281250001,\n 32.65787573695528\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Region 7 - Upper Colorado Basin
U.S. Geological Survey
Box 25046, MS-911
Denver, CO 80225-0046
River water temperatures are increasing globally, particularly in urban systems. In winter, wastewater treatment plant (WWTP) effluent inputs are of particular concern because they increase water temperatures from near freezing to ~7–15 °C. Recent laboratory studies suggest that warm overwinter temperatures impact the reproductive timing of some fishes. To evaluate winter water temperature’s influence in the wild, we sampled Johnny Darter Etheostoma nigrum from three urban South Platte River tributaries in Colorado upstream and downstream of WWTP effluent discharge sites. Fish were collected weekly during the spring spawning season of 2021 and reproductive development was determined from histological analysis of the gonads. Winter water temperatures were approximately 5–10 °C greater ~300 m downstream of the WWTP effluent compared to upstream sites, and approximately 3 °C warmer at sampling sites ~5000 m downstream of the effluent discharge. Females collected downstream of WWTP effluent experienced accelerated reproductive development compared to upstream by 1–2 weeks. Water quality, including total estrogenicity, and spring water temperatures did not appear to explain varying reproductive development. It appears that small increases in winter water temperature influence the reproductive timing in E. nigrum. Further investigations into how shifts in reproductive timing influence other population dynamics are warranted.
","language":"English","publisher":"MDPI","doi":"10.3390/fishes7060361","usgsCitation":"Adams, C.M., Winkelman, D.L., Schaffer, P.A., Villeneuve, D., Cavallin, J.E., Ellman, M., Santana Rodriguez, K., and Fitzpatrick, R.M., 2022, Elevated winter stream temperatures below wastewater treatment plants shift reproductive development of female Johnny Darter Etheostoma nigrum: A field and histologic approach: Fishes, v. 7, no. 6, 361, 21 p., https://doi.org/10.3390/fishes7060361.","productDescription":"361, 21 p.","ipdsId":"IP-144499","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":445780,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes7060361","text":"Publisher Index Page"},{"id":430219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Big Thompson River, Cache la Poudre River, St, Vrain Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.65453500751094,\n 40.768883536435936\n ],\n [\n -105.65453500751094,\n 40.09911106988662\n ],\n [\n -104.54071659609397,\n 40.09911106988662\n ],\n [\n -104.54071659609397,\n 40.768883536435936\n ],\n [\n -105.65453500751094,\n 40.768883536435936\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"7","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Catherine M.","contributorId":339138,"corporation":false,"usgs":false,"family":"Adams","given":"Catherine","email":"","middleInitial":"M.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":903811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaffer, Paula A.","contributorId":339141,"corporation":false,"usgs":false,"family":"Schaffer","given":"Paula","email":"","middleInitial":"A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":903813,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Villeneuve, Daniel L.","contributorId":339142,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Daniel L.","affiliations":[{"id":35215,"text":"Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":903814,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cavallin, Jenna E.","contributorId":339146,"corporation":false,"usgs":false,"family":"Cavallin","given":"Jenna","email":"","middleInitial":"E.","affiliations":[{"id":35215,"text":"Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":903815,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ellman, Michael","contributorId":339149,"corporation":false,"usgs":false,"family":"Ellman","given":"Michael","email":"","affiliations":[{"id":35215,"text":"Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":903816,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Santana Rodriguez, Kelvin","contributorId":339152,"corporation":false,"usgs":false,"family":"Santana Rodriguez","given":"Kelvin","email":"","affiliations":[{"id":35215,"text":"Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":903817,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fitzpatrick, Ryan M.","contributorId":339156,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Ryan","email":"","middleInitial":"M.","affiliations":[{"id":81245,"text":"Colorado Parks and Wildlife, Research, Policy, and Planning Section,","active":true,"usgs":false}],"preferred":false,"id":903818,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70239436,"text":"70239436 - 2022 - Regional-scale mapping of landscape response to extreme precipitation using repeat lidar and object-based image analysis","interactions":[],"lastModifiedDate":"2023-01-13T13:25:15.785359","indexId":"70239436","displayToPublicDate":"2022-11-29T07:19:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Regional-scale mapping of landscape response to extreme precipitation using repeat lidar and object-based image analysis","docAbstract":"Extreme precipitation events may cause flooding, slope failure, erosion, deposition, and damage to infrastructure over a regional scale, but the impacts of these events are often difficult to fully characterize. Regional-scale landscape change occurred during an extreme rain event in June 2012 in northeastern Minnesota. Landscape change was documented by 8,000 km2 of airborne lidar data collected before and after the event. Following improved alignment of the lidar point data and reducing error using insight from analysis of extensive stable areas, elevation differences were classified into map objects representing geomorphic change in relation to process and landscape position using object-based image analysis. This remote mapping compares favorably to field and imagery-based mapping and provides the basis for volumetric sediment budgeting. Elevation differences in these objects indicate that 4.5 × 106 ± 1.0 × 106 m3 of sediment was eroded in the study area. Of this, 2.5 × 106 ± 3.3 × 105 m3 was deposited in deposits on hillslopes and valley floors, and 2.0 × 106 ± 4.6 × 105 m3 were removed from watersheds and exported to the Saint Louis River Estuary and Lake Superior. Multivariate logistic regression analysis emphasized that topographic slope and presence of glaciolacustrine clay lithology are the primary control on landslide occurrence, and landslides occur most frequently on slopes within tens of meters of stream channels. These results provide the basis to anticipate the impacts of similar future storm events. Because precipitation events are forecast to continue to increase in frequency and intensity owing to climate change, characterizing and anticipating their effects may support hazard planning.
The U.S. Geological Survey, in cooperation with the Mississippi Band of Choctaw Indians (MBCI), conducted a baseline assessment of the physical, chemical, and biological quality of selected streams and rivers within and contiguous to the Pearl River Community (PRC) in 2017 and 2018. The MBCI is a federally recognized tribe with territories in Mississippi and Tennessee. MBCI Tribal government and communities have sovereign authority over their natural resources and are responsible for protecting the quality of waters within the Tribal lands from sources of pollution and restoring impaired waters. The quality of these surface waters has a profound effect upon the health and welfare of MBCI Tribal members. Data generated from this study may be used with other relevant water-quality data for comparison and development of Tribal water-quality standards.
The PRC territory is drained by the Pearl River and associated tributaries. Water-quality and biological samples were collected and habitat surveys were conducted at sites on the mainstem of the Pearl River and major tributaries of the Pearl River—Wolf Creek, Beasha Creek, Jones Creek, and Kentawka Creek. The selected stream sites represent a range of land use/land cover and potential sources of alteration and contamination from within their respective drainage areas. In particular, Wolf Creek watershed has the highest relative percentage of developed land.
Ambient physicochemical properties, major ions, nutrients, and organic wastewater compounds (OWCs) were analyzed quarterly from surface-water samples from October 2017 through August 2018. Physicochemical properties were also measured in June 2018 over a continuous 48-hour period. Trace elements and polycyclic aromatic hydrocarbons were analyzed from streambed sediments in August 2018. Biological samples included the collection of periphyton algae (August 2018), benthic macroinvertebrate (March 2017 and March 2018), and fish communities (April 2018). Physical stream habitat characteristics were assessed using qualitative (March 2017 and March 2018) and quantitative surveys (August 2018).
While not directly applicable, the State of Mississippi Water Quality Standards were used as reference to evaluate Tribal water quality. Physicochemical water-quality constituents—water temperature, specific conductance (SC), pH, and dissolved oxygen (DO)—were generally within natural ranges among sites and samples, with a few exceptions that exceeded existing Mississippi water-quality standards. pH and DO periodically were below the minimum State standards at some sampled sites. Specific conductance was also relatively high at both Wolf Creek sites but did not exceed the existing maximum standard for recreational waters.
The surface water among stream sites was predominantly calcium bicarbonate type, with a shift toward sodium-bicarbonate water type at the downstream Wolf Creek (Wolf DS) site. Major ion concentrations were generally highest at the Wolf Creek sites. Nutrient concentrations were also often highest at Wolf DS, but total nitrogen and total phosphorus periodically exceeded recommended State and Federal nutrient criteria thresholds among most sampled sites. Twenty-nine OWCs, including 10 known or suspected endocrine disruptors, were detected among sites. Concentrations of OWCs were relatively low, and only 19 percent of all detections were above the reporting level.
Concentrations of copper and nickel in streambed sediments were detected above consensus-based threshold-effect concentrations (TECs) at one site each, and arsenic and chromium exceeded TECs at most sites. Concentrations of all polycyclic aromatic hydrocarbons in streambed sediments were low and well below TECs at all sites.
The periphyton, macroinvertebrate, and fish communities at most sampled sites appear typical of central Mississippi streams; however, the diversity, composition, and abundance of taxa sampled from Wolf DS were particularly distinctive compared to other sampled stream sites. Periphyton taxa richness was low at both Wolf Creek sites, and both sites had greater abundances of diatom taxa, which are indicative of high nutrient concentrations, than of soft-algae taxa. Similarly, Wolf DS had relatively low macroinvertebrate diversity, the fewest Ephemeroptera, Plecoptera, and Trichoptera taxa, a high abundance of Tubificid taxa, and the lowest overall Mississippi-Benthic Index of Stream Quality score. Fish species richness was also relatively low at Wolf DS compared to some other sampled sites.
Habitat characteristics also appeared to be generally typical of most central Mississippi streams. Qualitative habitat assessment scores were at or above the regional least disturbed streams for Wolf DS, the upstream Wolf Creek (Wolf US) site, and Jones Creek. Habitat scores among the remaining sites indicate fair conditions. Quantitative and qualitative habitat characteristics indicate relatively lower habitat quality at the two Beasha Creek sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225090","collaboration":"Prepared in cooperation with the Mississippi Band of Choctaw Indians","usgsCitation":"Driver, L.J., Hicks, M.B., and Gill, A.C., 2022, Characterization of water quality, biology, and habitat of the Pearl River and selected tributaries contiguous to and within Tribal lands of the Pearl River Community of the Mississippi Band of Choctaw Indians, 2017–18: U.S. Geological Survey Scientific Investigations Report 2022–5090, 64 p., https://doi.org/10.3133/sir20225090.","productDescription":"Report: xi, 64 p.; Data Release; Dataset","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-128827","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":409703,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BX5Z48","text":"USGS data release","linkHelpText":"Habitat and biological assemblage data of streams within Tribal lands of the Pearl River Community of the Mississippi Band of Choctaw Indians, 2017–18"},{"id":409699,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5090/coverthb.jpg"},{"id":409700,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5090/sir20225090.pdf","text":"Report","size":"2.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5090"},{"id":409701,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5090/sir20225090.XML"},{"id":409702,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5090/images"},{"id":409704,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"}],"country":"United States","state":"Mississippi","otherGeospatial":"Pearl River Community","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89,\n 32.8667\n ],\n [\n -89.5,\n 32.8667\n ],\n [\n -89.5,\n 32.7333\n ],\n [\n -89,\n 32.7333\n ],\n [\n -89,\n 32.8667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
The Petro-Chemical Systems, Inc. (Turtle Bayou), Superfund site is 15 miles southeast of Liberty, Texas, in Liberty County. Improper disposal of waste oils led to contamination of soil and groundwater at the site. In cooperation with the U.S. Environmental Protection Agency, the U.S. Geological Survey collected water-quality samples from 11 monitoring wells at the site, in particular the area near well MW-109A (the MW-109 area), in August and September 2020 and compared the water-quality results to the results from previous water-quality sampling events at the site in June 2016 and August 2018 with a focus on benzene concentrations. Contours of groundwater-level altitudes in the MW-109 area indicate that groundwater-flow direction is south-southeasterly in the eastern part and south-southwesterly in the western part.
Of the 51 volatile organic compounds analyzed, 13 were detected in groundwater samples from 1 or more wells. In all but 1 well, MW-109A, concentrations of these compounds were less than 100 micrograms per liter. Benzene is still the principal contaminant of concern, as it persists at concentrations exceeding 53,000 micrograms per liter, although naphthalene also appears to be a contaminant of concern, as it was detected at the greatest concentration of any semivolatile organic compound analyte (1,100 micrograms per liter in the sample from well MW-109A).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225104","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Braun, C.L., and Becher, K.D., 2022, Groundwater-level altitudes and groundwater-flow direction and nature and extent of volatile and semivolatile organic compounds at Petro-Chemical Systems, Inc. (Turtle Bayou), Superfund site, Liberty County, Texas, 2020: U.S. Geological Survey Scientific Investigations Report 2022–5104, 17 p., https://doi.org/10.3133/sir20225104.","productDescription":"Report: v, 17 p.; Data release","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-135616","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":411892,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225104/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":409695,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5104/sir20225104.XML"},{"id":409693,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5104/coverthb.jpg"},{"id":409694,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5104/sir20225104.pdf","text":"Report","size":"1.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5104"},{"id":409697,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GX8YU7","text":"USGS data release","linkHelpText":"Groundwater-level altitudes and volatile and semivolatile organic compound concentrations at the Petro-Chemical Systems, Inc. (Turtle Bayou) Superfund site, Liberty County, Texas, 2020"},{"id":409696,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5104/images"}],"country":"United States","state":"Texas","county":"Liberty County","otherGeospatial":"Petro-Chemical Systems, Inc. (Turtle Bayou), Superfund site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.7111,\n 29.9222\n ],\n [\n -94.7111,\n 29.9167\n ],\n [\n -94.6667,\n 29.9167\n ],\n [\n -94.6667,\n 29.9222\n ],\n [\n -94.7111,\n 29.9222\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
The Conservation Reserve Enhancement Program is a program administered by the U.S. Department of Agriculture’s Farm Service Agency. The Secretary of Agriculture is required to submit an annual report to Congress on Conservation Reserve Enhancement Program agreements that, among other things, reports on the progress made towards fulfilling commitments outlined in the agreements. The U.S. Geological Survey developed an online reporting form designed to ensure that consistent information is submitted to the Farm Service Agency from Conservation Reserve Enhancement Program State partners. Combined with the automated importation of text from partner-provided forms to word-processing documents, individual State reports and annual reports to Congress can now be produced efficiently and in a standardized format. Use of a standardized reporting format will also assist the Farm Service Agency in collecting information needed to support ecosystem service quantifications that go beyond the quantifications required from partners to document progress towards meeting the specific purposes and objectives identified in each agreement. Addition of these overarching conservation effect quantifications builds upon past ecosystem services modeling efforts based on the Integrated Valuation of Ecosystem Services and Tradeoffs suite of open-source software models; these offer a spatially explicit means to quantify additional ecosystem services across diverse partners in a consistent manner. Data sources are currently available to provide much of the information needed to run these models and complete simulations that would facilitate the quantification and reporting of the societal values of conservation actions taken under the Conservation Reserve Enhancement Program. It is the aim of this report to provide the information needed to move towards widescale monitoring of the Nation’s ecosystem services in a natural accounting framework, similar to the framework used to value financial and human capital.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221104","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture’s Farm Production and Conservation Business Center and Farm Service Agency","usgsCitation":"Mushet, D.M., and McKenna, O.P., 2022, Development of an online reporting format to facilitate the inclusion of ecosystem services into Conservation Reserve Enhancement Program reports: U.S. Geological Survey Open-File Report 2022–1104, 19 p., https://doi.org/10.3133/ofr20221104.","productDescription":"Report: vi, 19 p.; 5 Appendixes","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-141507","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":409698,"rank":10,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221104/full","text":"Report"},{"id":409675,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1104/coverthb.jpg"},{"id":409676,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104.pdf","text":"Report","size":"725 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1104"},{"id":409677,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104.XML"},{"id":409678,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix1.pdf","text":"Appendix 1","description":"OFR 2022–1104, Appendix 1","linkHelpText":"—Farm Service Agency Notice Implementing Use of Online Reporting Form"},{"id":409679,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix2.pdf","text":"Appendix 2","description":"OFR 2022–1104, Appendix 2","linkHelpText":"—A Guide for Completing Conservation Reserve Enhancement Program Annual Reports Using the New Online Reporting Form"},{"id":409681,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix4.pdf","text":"Appendix 4","description":"OFR 2022–1104, Appendix 4","linkHelpText":"—Microsoft Word Mail Merge State Report Template"},{"id":409682,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix5.pdf","text":"Appendix 5","description":"OFR 2022–1104, Appendix 5","linkHelpText":"—Draft Text Produced for 2020 Report to Congress"},{"id":409683,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix6.pdf","text":"Appendix 6","description":"OFR 2022–1104, Appendix 6","linkHelpText":"—Draft Text Produced for 2021 Report to Congress"},{"id":409687,"rank":9,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1104/images"}],"contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Although there is extensive evidence of declines in the American Kestrel (Falco sparverius) population across North America, the cause of such declines remains a mystery. One hypothesized driver of decline is anticoagulant rodenticide (AR) exposure, which could potentially cause mortality or reduced fitness. We investigated AR exposure in wild American Kestrels in Utah, USA. We collected and tested for AR residues in liver samples (n = 8) from kestrels opportunistically encountered dead and in blood samples (n = 71) from live wild kestrels, both nestlings and adults. We found high detection rates in both tissues. Adult kestrels were more likely to exhibit exposure than juveniles sampled in nests. Three-quarters (six of eight) of tested liver samples from adult kestrels exhibited evidence of AR exposure. Additionally, liver samples (n = 19) opportunistically collected from seven species of raptors within our study area had detectable levels of AR residues, with seven of eight raptor species evidencing exposure; across all raptors, five ARs were detected in liver samples, with brodifacoum the most prevalent, being found in over half (14 of 27) of samples. Over half (7 of 12) of the blood samples from adult kestrels had detectible levels of ARs, while only one of 59 juvenile nest samples tested positive. The difference in exposure rates between adults and juveniles could indicate differential exposure pathways by age class. Based on these findings, we recommend that ARs be further investigated as a potential cause of kestrel declines. Future research could focus on expanding sampling to provide sufficient sample sizes to test for potential nonlethal effects of AR exposure (e.g., fecundity, nesting success), identifying potential exposure pathways, and developing methods for passive sampling of ARs in excreta.
","language":"English","publisher":"BioOne","doi":"10.3356/JRR-22-18","usgsCitation":"Buechley, E.R., Oleyar, D., Watson, J., Bridgeman, J., Volker, S., Goldade, D.A., Swift, C.E., and Rattner, B.A., 2022, Preliminary evidence of anticoagulant rodenticide exposure in American kestrels (Falco sparverius) in the western United States: Journal of Raptor Research, v. 57, no. 2, 11 p., https://doi.org/10.3356/JRR-22-18.","productDescription":"11 p.","ipdsId":"IP-137518","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":409788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.7171265349214,\n 41.72856999995494\n ],\n [\n -112.7171265349214,\n 39.7315850693289\n ],\n [\n -111.00398688405573,\n 39.7315850693289\n ],\n [\n -111.00398688405573,\n 41.72856999995494\n ],\n [\n -112.7171265349214,\n 41.72856999995494\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"57","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Buechley, Evan R.","contributorId":299452,"corporation":false,"usgs":false,"family":"Buechley","given":"Evan","email":"","middleInitial":"R.","affiliations":[{"id":64849,"text":"Smithsonian Conservaiton Biology Institute","active":true,"usgs":false}],"preferred":false,"id":857836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oleyar, Dave","contributorId":299453,"corporation":false,"usgs":false,"family":"Oleyar","given":"Dave","email":"","affiliations":[{"id":35596,"text":"HawkWatch International","active":true,"usgs":false}],"preferred":false,"id":857905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watson, Jesse","contributorId":243506,"corporation":false,"usgs":false,"family":"Watson","given":"Jesse","email":"","affiliations":[],"preferred":false,"id":857906,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bridgeman, Jennifer","contributorId":299455,"corporation":false,"usgs":false,"family":"Bridgeman","given":"Jennifer","email":"","affiliations":[{"id":35596,"text":"HawkWatch International","active":true,"usgs":false}],"preferred":false,"id":857907,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Volker, Steven","contributorId":299456,"corporation":false,"usgs":false,"family":"Volker","given":"Steven","affiliations":[{"id":64850,"text":"USDA, APHIS","active":true,"usgs":false}],"preferred":false,"id":857908,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goldade, David A.","contributorId":299457,"corporation":false,"usgs":false,"family":"Goldade","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":64850,"text":"USDA, APHIS","active":true,"usgs":false}],"preferred":false,"id":857909,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swift, Catherine E.","contributorId":299495,"corporation":false,"usgs":false,"family":"Swift","given":"Catherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":857910,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":857911,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70238753,"text":"70238753 - 2022 - Ordovician geology of Alaska","interactions":[],"lastModifiedDate":"2022-12-07T12:36:32.458661","indexId":"70238753","displayToPublicDate":"2022-11-28T06:32:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1791,"text":"Geological Society, London, Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"Ordovician geology of Alaska","docAbstract":"White-nose syndrome has been decimating populations of several bat species since its first occurrence in the Northeastern United States in the winter 2006–2007. The spread of the disease has been monitored across the continent through the collaboration of many organizations. Inferring the rate of spread of the disease and predicting its arrival at new locations is critical when assessing the current and predicting the future status and trends of bat species. We developed a model of disease spread that simultaneously achieves high-predictive performance, computational efficiency, and interpretability. We modeled white-nose syndrome spread using Gaussian process variations to infer the spread rate of the disease front, identify areas of anomalous time of arrival, and provide future forecasts of the expected time of arrival throughout North America. Cross-validation of model predictive performance identified a stationary Gaussian process without an additional residual error process as the best-supported model. Results indicated that white-nose syndrome is likely to spread throughout the entire continental United States by 2030. These annually updatable model predictions will be useful in determining the horizon over which disease management actions must take place as well as in status and trend assessments of disease-affected bats.
Management of a widely distributed species can be a challenge when management priorities, resource status, and assessment methods vary across jurisdictions. For example, restoration and preservation of coregonine species diversity is a goal of management agencies across the Laurentian Great Lakes. However, management goals and the amount of information available varies across management units, making the focus for management efforts challenging to determine. Genetic data provide a spatially consistent means to assess diversity. Therefore, we examined the genetic stock structure of cisco (Coregonus artedi) in the Great Lakes where the species is still extant. Using genotype data from 17 microsatellite DNA loci, we observed low levels of population structure among collections with most contributions to overall diversity occurring among lakes. Cisco from lakes Superior, Michigan, Ontario, and the St. Marys River could be considered single genetic populations while distinct genetic populations were observed among samples from northern Lake Huron. Significant within-lake diversity in Lake Huron is supported by populations found in embayments in northern Lake Huron. The Grand Traverse Bay population in Lake Michigan represents a distinct population with reduced levels of genetic variation when compared to other lakes. The different levels of within lake population structure we observed will be important to consider as future lake-specific management plans are developed.
It is important to routinely estimate loads from an entire watershed to describe current conditions and evaluate how watershed-wide management efforts have affected the nutrient and sediment export that affect downstream water quality. However, monitoring in most areas, including the Great Lakes watershed, consists of sampling at a limited number of sites that are only periodically used to estimate total watershed loading. Here, we describe a technique to extrapolate loads measured at a limited number of reference sites to the total load from a large watershed using load ratios between monitored sites and unmonitored areas obtained from a watershed model (i.e., model load ratio, MLR, approach). In this study, modeled nonpoint-source load ratios between monitored tributaries (reference sites) and nearby unmonitored areas and point-source delivery factors for all areas were obtained from a Spatially Referenced Regression On Watershed attributes (SPARROW) model and used to extrapolate the measured loads from an ongoing monitoring program (Great Lakes Restoration Initiative Tributary monitoring program) to the entire Great Lakes watershed. The MLR approach incorporates spatial variability in nonpoint- and point-source delivery, watershed characteristics, and hydrology that are often not considered when estimating loads from unmonitored areas, such as using the unit area load (UAL) extrapolation approach. The MLR approach provided smaller watershed loads than the UAL approach because yields from monitored sites, in general, were larger than from unmonitored areas. When both approaches were used to estimate loads at adjacent monitored sites, the MLR approach provided more accurate estimates than the UAL approach.
Stable hydrogen, carbon, nitrogen, oxygen and sulfur (HCNOS) isotope compositions expressed as isotope-delta values are typically reported relative to international standards such as Vienna Standard Mean Ocean Water (VSMOW), Vienna Peedee belemnite (VPDB) or Vienna Cañon Diablo Troilite (VCDT). These international standards are chosen by convention and the calibration methods used to realise them in practice undergo occasional changes. To ensure longevity and reusability of published data, a comprehensive description of (1) analytical procedure, (2) traceability, (3) data processing, and (4) uncertainty evaluation is required. Following earlier International Union of Pure and Applied Chemistry documents on terminology and notations, this paper proposes minimum requirements for publishing HCNOS stable-isotope delta results. Each of the requirements are presented with illustrative examples.
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In 2020 ∼70% of global tantalum supply originated in Africa, with 40% produced in the Democratic Republic of Congo alone. The United States has relied entirely on imports since the 1950s. However, quantifying total domestic consumption is problematic because refined tantalum compounds do not have unique tariff codes resulting in significant trade volumes not properly documented. Furthermore, tantalum incorporated into finished goods is not tracked as tantalum. Thus, estimates only capture a fraction of total consumption. We performed a material flow analysis to quantify total domestic tantalum consumption from 2002 to 2020. Our results indicate that consumption may be up to 250% more than previously estimated. Our detailed results allow quantification of tantalum stocks in-use as well as coming out of use any year, providing valuable insight to industry and policymakers for addressing potential supply security issues.
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Center","active":true,"usgs":true}],"preferred":true,"id":858133,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238712,"text":"70238712 - 2022 - An assessment of future tidal marsh resilience in the San Francisco Estuary through modeling and quantifiable metrics of sustainability","interactions":[],"lastModifiedDate":"2022-12-06T12:42:29.067786","indexId":"70238712","displayToPublicDate":"2022-11-25T06:34:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"An assessment of future tidal marsh resilience in the San Francisco Estuary through modeling and quantifiable metrics of sustainability","docAbstract":"Quantitative, broadly applicable metrics of resilience are needed to effectively manage tidal marshes into the future. Here we quantified three metrics of temporal marsh resilience: time to marsh drowning, time to marsh tipping point, and the probability of a regime shift, defined as the conditional probability of a transition to an alternative super-optimal, suboptimal, or drowned state. We used organic matter content (loss on ignition, LOI) and peat age combined with the Coastal Wetland Equilibrium Model (CWEM) to track wetland development and resilience under different sea-level rise scenarios in the Sacramento-San Joaquin Delta (Delta) of California. A 100-year hindcast of the model showed excellent agreement (R2 = 0.96) between observed (2.86 mm/year) and predicted vertical accretion rates (2.98 mm/year) and correctly predicted a recovery in LOI (R2 = 0.76) after the California Gold Rush. Vertical accretion in the tidal freshwater marshes of the Delta is dominated by organic production. The large elevation range of the vegetation combined with high relative marsh elevation provides Delta marshes with resilience and elevation capital sufficiently great to tolerate centenary sea-level rise (CLSR) as high as 200 cm. The initial relative elevation of a marsh was a strong determinant of marsh survival time and tipping point. For a Delta marsh of average elevation, the tipping point at which vertical accretion no longer keeps up with the rate of sea-level rise is 50 years or more. Simulated, triennial additions of 6 mm of sediment via episodic atmospheric rivers increased the proportion of marshes surviving from 51% to 72% and decreased the proportion drowning from 49% to 28%. Our temporal metrics provide critical time frames for adaptively managing marshes, restoring marshes with the best chance of survival, and seizing opportunities for establishing migration corridors, which are all essential for safeguarding future habitats for sensitive species.
Grazing represents the most extensive use of land worldwide. Yet its impacts on ecosystem services remain uncertain because pervasive interactions between grazing pressure, climate, soil properties, and biodiversity may occur but have never been addressed simultaneously. Using a standardized survey at 98 sites across six continents, we show that interactions between grazing pressure, climate, soil, and biodiversity are critical to explain the delivery of fundamental ecosystem services across drylands worldwide. Increasing grazing pressure reduced ecosystem service delivery in warmer and species-poor drylands, whereas positive effects of grazing were observed in colder and species-rich areas. Considering interactions between grazing and local abiotic and biotic factors is key for understanding the fate of dryland ecosystems under climate change and increasing human pressure.
","language":"English","publisher":"American Association for the Advancement of Science (AAAS)","doi":"10.1126/science.abq4062","usgsCitation":"Maestre, F.T., Le Bagousse-Pinguet, Y., Delgado-Baquerizo, M., Eldridge, D., Saiz, H., Berdugo, M., Gozalo, B., Ochoa, V., Guirado, E., García-Gómez, M., Valencia, E., Gaitan, J.J., Asensio, S., Mendoza, B.J., Plaza, C., Diaz-Martinez, P., Rey, A., Hu, H., He, J., Wang, J., Lehmann, A., Rillig, M., Cesarz, S., Eisenhauer, N., Martinez-Valderrama, J., Moreno-Jimenez, E., Sala, O.E., Abedi, M., Ahmadian, N., Alados, C.L., Aramayo, V., Amghar, F., Arredondo, T., Ahumada, R.J., Bahalkeh, K., Ben Salem, F., Blaum, N., Boldgiv, B., Bowker, M., Bran, D., Bu, C., Canessa, R., Castillo-Monroy, A.P., Castro, H., Castro, I., Castro-Quezada, P., Chibani, R., Conceição, A., Currier, C.M., Darrouzet-Nardi, A., Deak, B., Donoso, D.A., Dougill, A.J., Duran, J., Erdenetsetseg, B., Espinosa, C., Fajardo, A., Farzam, M., Ferrante, D., Frank, A.S., Fraser, L.H., Gherardi, L.A., Greenville, A.C., Guerra, C., Gusmán-Montalvan, E., Hernández-Hernández, R., Holzel, N., Huber-Sannwald, E., Hughes, F., Jadan-Maza, O., Jeltsch, F., Jentsch, A., Kaseke, K.F., Kobel, M., Koopman, J.E., Leder, C.V., Linstadter, A., le Roux, P.C., Li, X., Liancourt, P., Liu, J., Louw, M.A., Maggs-Kolling, G., Makhalanyane, T.P., Malam Issa, O., Manzaneda, A.J., Marais, E., Mora, J.P., Moreno, G., Munson, S.M., Nunes, A., Oliva, G., Oñatibia, G., Peter, G., Pivari, M.O., Pueyo, Y., Quiroga, R., Rahmanian, S., Reed, S., Rey, P.J., Richard, B., Rodriguez, A., Rolo, V., Rubalcaba, J.G., Puppert, J.C., Salah, A., Schuchardt, M.A., Spann, S., Stavi, I., Stephens, C.R., Swemmer, A.M., Teixido, A.L., Thomas, A.D., Throop, H.L., Tielborger, K., Travers, S.K., Val, J., Valko, O., van den Brink, L., Velasco Ayuso, S., Velbert, F., Wamiti, W., Wang, D., Wang, L., Wardle, G., Yahdjian, L., Zaady, E., Zhang, Y., Zhou, X., Singh, B.K., and Gross, N., 2022, Grazing and ecosystem service delivery in global drylands: Science, v. 378, no. 6622, p. 915-920, https://doi.org/10.1126/science.abq4062.","productDescription":"6 p.","startPage":"915","endPage":"920","ipdsId":"IP-131591","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":445813,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10486/716905","text":"External Repository"},{"id":411285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"378","issue":"6622","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maestre, Fernando T.","contributorId":207297,"corporation":false,"usgs":false,"family":"Maestre","given":"Fernando","email":"","middleInitial":"T.","affiliations":[{"id":37513,"text":"Departamento de Biología y Geología, Física y Química Inorgánica, ESCET, Universidad Rey Juan Carlos, c/ Tulipán s/n, 28933 Móstoles, Spain","active":true,"usgs":false}],"preferred":false,"id":860364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Le Bagousse-Pinguet, Yoann","contributorId":300372,"corporation":false,"usgs":false,"family":"Le Bagousse-Pinguet","given":"Yoann","email":"","affiliations":[{"id":65094,"text":"Aix Marseille Univ, CNRS, Avignon Université, IRD, IMBE, Aix-en-Provence, France.","active":true,"usgs":false}],"preferred":false,"id":860365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Delgado-Baquerizo, Manuel","contributorId":214645,"corporation":false,"usgs":false,"family":"Delgado-Baquerizo","given":"Manuel","email":"","affiliations":[{"id":39101,"text":"Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USA","active":true,"usgs":false}],"preferred":false,"id":860366,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eldridge, David J. 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Instituto de Ciencias Agrarias, Consejo Superior de Investigaciones Científicas, Madrid, Spain.","active":true,"usgs":false}],"preferred":false,"id":860371,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Guirado, Emilio","contributorId":300377,"corporation":false,"usgs":false,"family":"Guirado","given":"Emilio","email":"","affiliations":[{"id":65098,"text":"Instituto Multidisciplinar para el Estudio del Medio “Ramón Margalef,” Universidad de Alicante, Alicante, Spain.","active":true,"usgs":false}],"preferred":false,"id":860372,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"García-Gómez, Miguel","contributorId":300378,"corporation":false,"usgs":false,"family":"García-Gómez","given":"Miguel","affiliations":[{"id":65100,"text":"Departamento de Ingeniería y Morfología del Terreno, Escuela Técnica Superior de Ingenieros de Caminos, Canales y Puertos, Universidad Politécnica de Madrid, Madrid, 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Sustained eruptions have been shown to produce a low frequency (infrasonic) form of jet noise. We analyze the lava fountaining at fissure 8 during the 2018 Lower East Rift Zone eruption of Kīlauea volcano, Hawaii, and connect changes in fountain properties with recorded infrasound signals from an array about 500 m from the fountain using jet noise scaling laws and visual imagery. Video footage from the eruption reveals a change in lava fountain dynamics from a tall, distinct fountain at the beginning of June to a low fountain with a turbulent, out-pouring lava pond surrounded by a tephra cone by mid-June. During mid-June, the sound pressure level reaches a maximum, and peak frequency drops. We develop a model that uses jet noise scaling relationships to estimate changes in volcanic jet diameter and jet velocity from infrasound sound pressure levels and peak frequencies. The results of this model indicate a decrease in velocity in mid-June which coincides with the decrease in fountain height. Furthermore, the model results suggest an increase in jet diameter, which can be explained by the larger width of the fountain that resembles a turbulent lava pond compared to the distinct fountain at the beginning of June. The agreement between the infrasound-derived and visually observed changes in fountain dynamics suggests that jet noise scaling relationships can be used to monitor lava fountain dynamics using infrasound recordings.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2022.1027408","usgsCitation":"Gestrich, J., Fee, D., Matoza, R., Lyons, J.J., Dietterich, H., Cigala, V., Kueppers, U., Patrick, M.R., and Parcheta, C., 2022, Lava fountain jet noise during the 2018 eruption of fissure 8 of Kīlauea volcano: Frontiers Earth Science Journal, v. 10, 1027408, 18 p., https://doi.org/10.3389/feart.2022.1027408.","productDescription":"1027408, 18 p.","ipdsId":"IP-144544","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467142,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2022.1027408","text":"Publisher Index Page"},{"id":462663,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.40616179843389,\n 19.510647106982844\n ],\n [\n -155.40616179843389,\n 19.352324463279487\n ],\n [\n -155.20934216439622,\n 19.352324463279487\n ],\n [\n -155.20934216439622,\n 19.510647106982844\n ],\n [\n -155.40616179843389,\n 19.510647106982844\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2022-11-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Gestrich, Julia","contributorId":268787,"corporation":false,"usgs":false,"family":"Gestrich","given":"Julia","affiliations":[{"id":50446,"text":"UAF-GI","active":true,"usgs":false}],"preferred":false,"id":915202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fee, David 0000-0002-0936-9977","orcid":"https://orcid.org/0000-0002-0936-9977","contributorId":267231,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":915203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matoza, Robin","contributorId":268788,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":915204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":915205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915206,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cigala, Valerie","contributorId":344976,"corporation":false,"usgs":false,"family":"Cigala","given":"Valerie","affiliations":[{"id":62362,"text":"LMU","active":true,"usgs":false}],"preferred":false,"id":915207,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kueppers, Ulrich","contributorId":178534,"corporation":false,"usgs":false,"family":"Kueppers","given":"Ulrich","affiliations":[],"preferred":false,"id":915208,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915209,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Parcheta, Carolyn 0000-0001-6556-4630 cparcheta@usgs.gov","orcid":"https://orcid.org/0000-0001-6556-4630","contributorId":215617,"corporation":false,"usgs":true,"family":"Parcheta","given":"Carolyn","email":"cparcheta@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915210,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70238659,"text":"70238659 - 2022 - Editorial: Plant phenology shifts and their ecological and climatic consequences","interactions":[],"lastModifiedDate":"2022-12-02T13:04:45.016779","indexId":"70238659","displayToPublicDate":"2022-11-24T07:02:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5725,"text":"Frontiers in Plant Science","active":true,"publicationSubtype":{"id":10}},"title":"Editorial: Plant phenology shifts and their ecological and climatic consequences","docAbstract":"Climate change is causing plant phenology to shift, with consequences for ecosystems and the Earth’s climate. Over the last decades, the timing of many important phenological events has advanced in spring, such as leaf emergence and flowering, or been delayed in fall, such as leaf coloration and leaf fall. The consequences of such phenological shifts are still largely unknown, but are hypothesized to have cascading effects on ecosystems, carbon and water cycles, and Earths’ climate. With this research topic, we aimed to synthesize and inspire innovative research in plant phenology to address research questions and challenges on the consequences of phenological shifts on ecosystem function and local hydrology. The articles presented here improve our understanding of the physiological mechanisms responsible for the current phenological changes in spring and fall and provide insight into some of the consequences of these changes on hydrological cycles and ecosystem functioning.","language":"English","publisher":"Frontiers","doi":"10.3389/fpls.2022.1071266","usgsCitation":"Fu, Y.H., Prevey, J.S., and Vitasse, Y., 2022, Editorial: Plant phenology shifts and their ecological and climatic consequences: Frontiers in Plant Science, v. 13, 1071266, 3 p., https://doi.org/10.3389/fpls.2022.1071266.","productDescription":"1071266, 3 p.","ipdsId":"IP-146273","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":445816,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fpls.2022.1071266","text":"Publisher Index Page"},{"id":409982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2022-11-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Fu, Yongshuo H.","contributorId":299608,"corporation":false,"usgs":false,"family":"Fu","given":"Yongshuo","email":"","middleInitial":"H.","affiliations":[{"id":64905,"text":"1. College of Water Science, Beijing Normal University, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":858215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prevey, Janet S. 0000-0003-2879-6453","orcid":"https://orcid.org/0000-0003-2879-6453","contributorId":222702,"corporation":false,"usgs":true,"family":"Prevey","given":"Janet","email":"","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vitasse, Yann","contributorId":299609,"corporation":false,"usgs":false,"family":"Vitasse","given":"Yann","email":"","affiliations":[{"id":64907,"text":"3. Swiss Federal Institute for Forest, Snow and Landscape Research, Forest Dynamics, Birmensdorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":858217,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70246258,"text":"70246258 - 2022 - A reappraisal of explosive–effusive silicic eruption dynamics: Syn-eruptive assembly of lava from the products of cryptic fragmentation","interactions":[],"lastModifiedDate":"2023-06-28T11:47:35.561379","indexId":"70246258","displayToPublicDate":"2022-11-24T06:46:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"A reappraisal of explosive–effusive silicic eruption dynamics: Syn-eruptive assembly of lava from the products of cryptic fragmentation","docAbstract":"Silicic volcanic eruptions range in style from gently effusive to highly explosive, and may switch style unpredictably during a single eruption. Direct observations of subaerial rhyolitic eruptions (Chaiten 2008, Cordón Caulle 2011–2012, Chile) challenged long-standing paradigms of explosive and effusive eruptive styles and led to the formulation of new models of hybrid activity. However, the processes that govern such hybrid explosive–effusive activity remain poorly understood. Here, we bring together observations of the well-studied 2011–2012 Cordón Caulle eruption with new textural and petrologic data on erupted products, and video and still imagery of the eruption. We infer that all of the activity – explosive, effusive, and hybrid – was fed by explosive fragmentation at depth, and that effusive behaviour arose from sticking and sintering, in the shallow vent region, of the clastic products of deeper, cryptic fragmentation. We use a scaling approach to determine that there is sufficient time available, during emplacement, for diffusive pyroclast degassing and sintering to produce a degassed plug that occludes the shallow conduit, feeding clastogenic, apparently effusive, lava-like deposits. Based on evidence from Cordón Caulle, and from other similar eruptions, we further argue that hybrid explosive–effusive activity is driven by episodic gas-fracking of the occluding lava plug, fed by the underlying pressurized ash- and pyroclast-laden region. The presence of a pressurized pocket of ash-laden gas within the conduit provides a mechanism for generation of harmonic tremor, and for syn-eruptive laccolith intrusion, both of which were features of the Cordón Caulle eruption. We conclude that the cryptic fragmentation models is more consistent with available evidence than the prevailing model for effusion of silicic lava that assume coherent non-fragmental rise of magma from depth to the surface without wholesale explosive fragmentation.
The increased risk of coastal flooding associated with climate-change driven sea level rise threatens to displace communities and cause substantial damage to infrastructure. Site-specific adaptation planning is necessary to mitigate the negative impacts of flooding on coastal residents and the built environment. Cost-benefit analyses used to evaluate coastal adaption strategies have traditionally focused on economic considerations, often overlooking potential demographic impacts that can directly influence vulnerability in coastal communities. Here, we present a transferable framework that couples hydrodynamic modeling of flooding driven by sea level rise and storm scenarios with site-specific building stock and census block-level demographic data. We assess the efficacy of multiple coastal adaptation strategies at reducing flooding, economic damages, and impacts to the local population. We apply this framework to evaluate a range of engineered, nature-based, and hybrid adaptation strategies for a portion of Santa Monica Bay, California. Overall, we find that dual approaches that provide protection along beaches using dunes or seawalls and along inlets using sluice gates perform best at reducing or eliminating flooding, damages, and population impacts. Adaptation strategies that include a sluice gate and partial or no protection along the beach are effective at reducing flooding around inlets but can exacerbate flooding elsewhere, leading to unintended impacts on residents. Our results also indicate trade-offs between economic and social risk-reduction priorities. The proposed framework allows for a comprehensive evaluation of coastal protection strategies across multiple objectives. Understanding how coastal adaptation strategies affect hydrodynamic, economic, and social factors at a local scale can enable more effective and equitable planning approaches.
Nest site selection has consequences for hatching success by mediating the temperature and moisture conditions that eggs experience during the incubation period. Understanding the potentially complex pathways by which nest placement influences these abiotic mediators, and therefore hatching success, is important for predicting which nests will be successful and which may require management action. We studied the effects of loggerhead sea turtle (Caretta caretta) nest site selection on hatching success by linking nest placement characteristics to hatching success through a structural equation model. We monitored 170 nests on Ossabaw Island, Georgia, during the summers of 2017 and 2018 and tracked nest conditions throughout the incubation period. Temperature had a complex effect on hatching success—nests had higher hatching rates if they were exposed to higher mean temperatures but also if they experienced both extremely high (>34°C) and extremely low (<26.5°C) temperatures, suggesting that temperature variability plays a role in determining nest outcomes beyond the mean temperature. Likewise, hatching success declined with a higher incidence of nests being inundated by tides. We found that nests placed at the highest elevations had the highest hatching success rates, likely because those nests had a much lower chance of being washed over by high tides and had higher mean temperatures. Nests were also more successful when placed in greater amounts of vegetation, again because vegetated nests were generally warmer and were associated with fewer washover events. These results shed light on the mechanisms behind selection for certain nest site characteristics and can guide the relocation of nests as a conservation action.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps14197","usgsCitation":"Whitesell, M., Hunter, E.A., Rostal, D., and Carroll, J., 2022, Direct and indirect pathways for environmental drivers of hatching success in the loggerhead sea turtle: Marine Ecology Progress Series, v. 701, p. 119-132, https://doi.org/10.3354/meps14197.","productDescription":"14 p.","startPage":"119","endPage":"132","ipdsId":"IP-139067","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481071,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.3354/meps14197","text":"External Repository"},{"id":480923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Ossabaw Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.16544988349773,\n 31.87085846584084\n ],\n [\n -81.16544988349773,\n 31.71610084390467\n ],\n [\n -81.03274894641083,\n 31.71610084390467\n ],\n [\n -81.03274894641083,\n 31.87085846584084\n ],\n [\n -81.16544988349773,\n 31.87085846584084\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"701","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Whitesell, Mattie J.","contributorId":348695,"corporation":false,"usgs":false,"family":"Whitesell","given":"Mattie J.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":923704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rostal, David C.","contributorId":348698,"corporation":false,"usgs":false,"family":"Rostal","given":"David C.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":923706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carroll, John M.","contributorId":348701,"corporation":false,"usgs":false,"family":"Carroll","given":"John M.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":923707,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}