Hurricane Irma skirted the northern coasts of the U.S. Virgin Islands and Puerto Rico, with maximum sustained winds of 185 miles per hour (mi/h) on September 6, 2017. The hurricane first made landfall in Florida near Cudjoe Key, in the lower Florida Keys, with maximum sustained winds of 130 mi/h on September 10, 2017. The hurricane made a second Florida landfall on Marco Island, Florida, with maximum sustained winds of 115 mi/h on September 10, 2017. The U.S. Geological Survey (USGS), in cooperation with Federal Emergency Management Agency, deployed a temporary monitoring network of water-level and barometric pressure sensors at 249 locations along the Puerto Rico, Florida, Georgia, and South Carolina coasts to record the timing, areal extent, and magnitude of hurricane storm tide and coastal flooding generated by the hurricane. Immediately following the passage of Hurricane Irma, the sensors were retrieved, and the data were disseminated on the USGS Flood Event Viewer (https://stn.wim.usgs.gov/FEV/#IrmaSeptember2017). The storm-tide peak data values were verified by comparing data from hydrologic recorders and nearby high-water marks (HWMs). Following the hurricane, 508 independent HWM locations were flagged and surveyed relative to the North American Vertical Datum of 1988, National Geodetic Vertical Datum of 1929, or a local datum along the southeastern U.S. coast, and to Puerto Rico Vertical Datum of 2002 in Puerto Rico. Most HWMs were in Florida because of the path of the hurricane. The data from the Hurricane Irma storm-tide network are available on a provisional basis in tab-delimited, American Standard Code for Information Interchange (ASCII) format and Network Common Data Form (NetCDF) format by site for each sensor by using the USGS Flood Event Viewer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191013","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Byrne, M.J., Sr., and Dickman, M.R., 2019, Monitoring storm tide and flooding from Hurricane Irma along the U.S. Virgin Islands, Puerto Rico, and the Southeastern United States, September 2017 (ver. 1.1, July 2019): U.S. Geological Survey Open-File Report 2019–1013, 35 p., https://doi.org/10.3133/ofr20191013.","productDescription":"vi, 35 p.","numberOfPages":"46","onlineOnly":"N","ipdsId":"IP-095711","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":365693,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1013/ofr20191013.pdf","text":"Report","size":"9.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1013"},{"id":365694,"rank":2,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2019/1013/versionHist.txt","text":"Version History","size":"1.00 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2019–1013 Version History"},{"id":365697,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1013/coverthb2.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico, U.S. Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.9892578125,\n 24.00632619875113\n ],\n [\n -79.4970703125,\n 24.00632619875113\n ],\n [\n -79.4970703125,\n 32.0639555946604\n ],\n [\n -88.9892578125,\n 32.0639555946604\n ],\n [\n -88.9892578125,\n 24.00632619875113\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.02734375,\n 16.04581345375217\n ],\n [\n -63.45703124999999,\n 16.04581345375217\n ],\n [\n -63.45703124999999,\n 20.96143961409684\n ],\n [\n -68.02734375,\n 20.96143961409684\n ],\n [\n -68.02734375,\n 16.04581345375217\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: April 16, 2019; Version 1.1: July 25, 2019 ","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Agricultural runoff from the Mississippi‐Atchafalaya River Basin delivers nitrogen (N) and phosphorus (P) to the Gulf of Mexico, causing hypoxia, and climate drives interannual variation in nutrient loads. Climate phenomena such as El Niño–Southern Oscillation may influence nutrient export through effects on river flow, nutrient uptake, or biogeochemical transformation, but landscape variation at smaller spatial scales can mask climate signals in load or discharge time series within large river networks. We used multivariate autoregressive state‐space modeling to investigate climate signals in the long‐term record (1979–2014) of discharge, N, P, and SiO2 loads at three nested spatial scales within the Mississippi‐Atchafalaya River Basin. We detected significant signals of El Niño–Southern Oscillation and land‐surface temperature anomalies in N loads but not discharge, SiO2, or P, suggesting that large‐scale climate phenomena contribute to interannual variation in nutrient loads through biogeochemical mechanisms beyond simple discharge‐load relationships.
Exotic annual grasses are transforming native arid and semi-arid ecosystems globally by accelerating fire cycles that drive vegetation state changes. Cheatgrass (Bromus tectorum), a particularly widespread and aggressive exotic annual grass, is a key management target in national parks of the western United States due to its impacts on wildfire and biodiversity loss. Cheatgrass is known for its high interannual variability and can grow in a wide range of conditions.
Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 1.2 billion barrels of tight oil and 29.1 trillion cubic feet of tight gas in Mesozoic formations in the Sichuan Basin of China.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193010","usgsCitation":"Potter, C.J., Schenk, C.J., Mercier, T.J., Tennyson, M.E., Finn, T.M., Woodall, C.A., Leathers-Miller, H.M., Marra, K.R., Le, P.A., Drake, R.M., II, Brownfield, M.E., and Pitman, J.K., 2019, Assessment of Mesozoic tight-oil and tight-gas resources in the Sichuan Basin of China, 2018: U.S. Geological Survey Fact Sheet 2019–3010, 2 p., https://doi.org/10.3133/fs20193010. ","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-102499","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":362861,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3010/coverthb.jpg"},{"id":362862,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3010/fs20193010.pdf","text":"Report","size":"527 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019–3010"}],"country":"China","otherGeospatial":"Sichuan basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 103.304443359375,\n 29.075375179558346\n ],\n [\n 107.193603515625,\n 29.075375179558346\n ],\n [\n 107.215576171875,\n 32.40779154205701\n ],\n [\n 103.73291015625,\n 32.35212281198644\n ],\n [\n 103.304443359375,\n 29.075375179558346\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS–939
Denver, CO 80225–0046
Golden Tegus (Tupinambis teguixin sensu lato) are native to South America and have established a reproducing population in Miami-Dade County, Florida. Recent work divided the Golden Tegu into four separate species, leaving the specific identity of Golden Tegus in Florida unknown. We used morphometric and mitochondrial data to determine the species identity and likely area of geographic origin for a specimen of Golden Tegu collected in Miami-Dade County, Florida. Our results indicate Cryptic Golden Tegus (Tupinambis cryptus) are the species established in Florida. Geographic origin is likely mainland Guyana or Venezuela.
","language":"English","doi":"10.3391/bir.2019.8.2.30","usgsCitation":"Pyron, R.A., Reed, R., Colston, T.J., and Rochford, M.R., 2019, Morphology and molecular data reveal invasion of cryptic golden tegus Tupinambis cryptus Murphy et al., 2016) in Florida: BioInvasions Records, v. 8, no. 2, p. 465-470, https://doi.org/10.3391/bir.2019.8.2.30.","productDescription":"6 p.","startPage":"465","endPage":"470","ipdsId":"IP-103042","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":467704,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/bir.2019.8.2.30","text":"Publisher Index Page"},{"id":363052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":363051,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.reabic.net/journals/bir/2019/Accepted.aspx"}],"country":"United States","state":"Florida","county":"Miami-Dade County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.782470703125,\n 25.22978942503438\n ],\n [\n -80.09033203125,\n 25.22978942503438\n ],\n [\n -80.09033203125,\n 26.10118797369925\n ],\n [\n -80.782470703125,\n 26.10118797369925\n ],\n [\n -80.782470703125,\n 25.22978942503438\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pyron, R. Alexander","contributorId":214888,"corporation":false,"usgs":false,"family":"Pyron","given":"R.","email":"","middleInitial":"Alexander","affiliations":[{"id":34680,"text":"George Washington University","active":true,"usgs":false}],"preferred":false,"id":761085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":214887,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":761084,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colston, Timothy J.","contributorId":214889,"corporation":false,"usgs":false,"family":"Colston","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":34680,"text":"George Washington University","active":true,"usgs":false}],"preferred":false,"id":761086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rochford, Michael R.","contributorId":200644,"corporation":false,"usgs":false,"family":"Rochford","given":"Michael","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":761087,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204945,"text":"70204945 - 2019 - The circumtropical swarm population of the longspined porcupinefish (Diodon holocanthus Linnaeus)","interactions":[],"lastModifiedDate":"2019-08-26T10:24:00","indexId":"70204945","displayToPublicDate":"2019-04-15T10:23:50","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5854,"text":"Aqua","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The circumtropical swarm population of the longspined porcupinefish (Diodon holocanthus Linnaeus)","title":"The circumtropical swarm population of the longspined porcupinefish (Diodon holocanthus Linnaeus)","docAbstract":"Evidence is presented that Diodon holocanthus is a circumtropical swarm (not a hybrid swarm because the individuals are not hybrids). Some individuals are so different
from one another in both color and morphology that they appear to be different species. Thirty undersea and aquarium photographs from different global localities are provided to demonstrate the variability. The worldwide distribution is achieved by the juvenile that has been found more than 1,000 km offshore as large as 90 mm SL. How can it feed on zooplankton with jaws and dentition designed to crush shelled invertebrates? We believe it draws the prey into the mouth with the same mechanism that it uses to expand its body when threatened; the water with prey is diverted to the pharyngeal cavity, then released from the gill opening on each side. Larger juveniles may seek concentrations of zooplankton for feeding, perhaps collectively. A confirming experiment in an aquarium is advised. Aggregations of pelagic juveniles have been observed at the surface outside barrier reefs and found inshore the following morning, indicating that settlement took place at night to minimize predation. The juveniles soon disperse to inshore habitats of mangrove and sea grass to coral reef. The hybrid Diodon holocanthusx D. hystrix from South Africa is illustrated. The narrative for the present research on D. holocanthus is presented chronologically to show how increasing evidence failed to support the multitude of apparent new species of Diodon, leading to the conclusion of a swarm.
Eruptions of Kīlauea Volcano, Hawaiʻi, USA, can be more powerful than previously recognized. The Kulanaokuaiki-3 (K-3) eruption, ca. 900 CE, consisted of two episodes that dispersed lithic wall-rock clasts (Episode 1) and dominantly scoria (Episode 2; VEI-3) across >65 km2 southeast of the summit. Dense 12 cm blocks of Episode 1 fell 8–10 km from the summit vent, and 2–4 cm lithic lapilli reached the coastline, 17 km from the vent. The Episode 2 deposit is chemically zoned, indicating orderly eruption from a layered magma body analogous to the 1959 Kīlauea Iki lava lake. Olivine-hosted melt inclusions suggest a magma body within 1 km of the surface. Some Episode 1 lithic clasts have magmatic rinds chemically similar to the early Episode 2 scoria, suggesting a genetic link, although each had a distinct eruption mechanism. Southeastward tephra dispersal counter to NE trade winds implies dispersal by jet-stream winds. The dispersal of lithic clasts in Episode 1 cannot be explained by ballistic trajectories or by transport in a buoyant plume. Calculations instead indicate that a jet from a vent with a minimum diameter of 50 m, a velocity of at least 300 m/s, and a duration of ∼60 s could have lifted the lithic clasts into the jet stream. Isopach and isopleth maps for Episode 2 indicate a subplinian column height of 14–18 km and a duration of 2–3 h, assuming constant flux. The Episode 1 conduit probably intersected or otherwise lowered pressure within a compositionally zoned magma body, triggering eruption of the Episode 2 scoria.
Analysis of pollen provisions in Xylocopa virginica (L.) nests in southern Rhode Island showed that this species produced pollen loaves from 21 different genera of plants in 2016, 19 in 2017, and 39 in 2018. Antirrhinium majus L. (garden snapdragon) pollen was the most common type collected in all three years (21.4%). Overall, wind-pollinated tree pollen comprised 22.1% of all pollen loaves. Blueberry pollen was a minor component of pollen loaves (0.1%), despite abundant blueberry plants nearby. Mean values of X. virginica nest measurements (tunnel length 15.4 ± 1.2 cm, width 15.0 ± 0.5 mm, and cell length 17.7 ± 0.3 mm) were similar to those reported in previous studies. Only 2 of the 216 trap nests deployed in 2017 were occupied by 11 X. virginica bees (9 females and 2 males). However, 17 nests contained 230 Osmia taurus Smith, 6 nests contained 73 O. cornifrons (Radoszkowski), and 1 nest contained 8 O. lignaria Say. Thirty-four nests (15.7%) were occupied by 151 grass-carrying wasps, Isodontia sp. and 6 vespid wasps occupied three nests (1.4%) in 2017. In 2018, 4 of 96 trap nests were occupied by carpenter bees. Understanding the nesting and foraging habits of X. virginica will help us to manage natural populations for pollination services.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/ee/nvz032","usgsCitation":"Tucker, S.K., Ginsberg, H., and Alm, S.R., 2019, Eastern Carpenter Bee (Hymenoptera: Apidae): Nest structure, nest cell provisions, and trap nest acceptance in Rhode Island: Environmental Entomology, v. 48, no. 3, p. 702-710, https://doi.org/10.1093/ee/nvz032.","productDescription":"9 p.","startPage":"702","endPage":"710","ipdsId":"IP-104447","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":490061,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/pls_facpubs/47","text":"External Repository"},{"id":364523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Rode 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regulation: Wyoming case study","docAbstract":"Many streams are experiencing increased average temperatures due to anthropogenic activity and climate change. As a result, surface water temperature regulation is critical for preserving a diverse stream fish species assemblage. The development of temperature regulations has generally been based on laboratory measurements of individual species' thermal tolerances rather than community response to temperature in the field, despite multiple limitations of using laboratory data for this purpose. Using field data to develop temperature regulations may avoid some of the limitations of laboratory data, but the use of field data comes with additional challenges that prevent its widespread adoption. We used Wyoming stream fish assemblages as a case study to examine the feasibility of addressing the limitations of field and laboratory data through a hybrid approach that integrates both types of data to classify species into thermal guilds that can potentially inform regulatory standards. We identified coldwater, coolwater, and warmwater classes of sites with modeled mean August temperatures of <15.5, 15.5–19.9, and >19.9°C, respectively. We used species' associations with these temperature classes to place species into site‐groups. Finally, we used standardized laboratory measures of species' upper acute and chronic thermal tolerances to identify and reclassify species with unusual thermal distributions. Through this process we classified species into five thermal guilds that may be useful for surface water temperature regulation in Wyoming. Our approach addresses the limitations identified for field and laboratory data and demonstrates a framework that could be used for incorporating multiple types of data to develop temperature standards.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10169","usgsCitation":"Mandeville, C.P., Rahel, F.J., Patterson, L.S., and Walters, A.W., 2019, Integrating fish assemblage data, modeled stream temperatures, and thermal tolerance metrics to develop thermal guilds for water temperature regulation: Wyoming case study: Transactions of the American Fisheries Society, v. 148, no. 4, p. 739-754, https://doi.org/10.1002/tafs.10169.","productDescription":"15 p.","startPage":"739","endPage":"754","ipdsId":"IP-098236","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":379546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.0498046875,\n 40.88029480552824\n ],\n [\n -104.0185546875,\n 40.88029480552824\n ],\n [\n -104.0185546875,\n 44.933696389694674\n ],\n [\n -111.0498046875,\n 44.933696389694674\n ],\n [\n -111.0498046875,\n 40.88029480552824\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"148","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-05-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Mandeville, Caitlin P. 0000-0002-1361-607X","orcid":"https://orcid.org/0000-0002-1361-607X","contributorId":243378,"corporation":false,"usgs":false,"family":"Mandeville","given":"Caitlin","email":"","middleInitial":"P.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":802164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rahel, Frank J.","contributorId":171824,"corporation":false,"usgs":false,"family":"Rahel","given":"Frank","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":802165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patterson, Lindsay S.","contributorId":243379,"corporation":false,"usgs":false,"family":"Patterson","given":"Lindsay","email":"","middleInitial":"S.","affiliations":[{"id":48707,"text":"Wyoming Dept of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":802166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":802167,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203200,"text":"70203200 - 2019 - Quantifying ecological integrity of terrestrial systems to inform management of multiple-use public lands in the United States","interactions":[],"lastModifiedDate":"2020-09-01T13:57:44.453274","indexId":"70203200","displayToPublicDate":"2019-04-13T08:46:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying ecological integrity of terrestrial systems to inform management of multiple-use public lands in the United States","docAbstract":"The concept of ecological integrity has been applied widely to management of aquatic systems, but still is considered by many to be too vague and difficult to quantify to be useful for managing terrestrial systems, particularly across broad areas. Extensive public lands in the western United States are managed for diverse uses such as timber harvest, livestock grazing, energy development, and wildlife conservation, some of which may degrade ecological integrity. We propose a method for assessing ecological integrity on multiple-use lands that identifies the components of integrity and levels in the ecological hierarchy where the assessment will focus, and considers existing policies and management objectives. Both natural reference and societally desired environmental conditions are relevant comparison points. We applied the method to evaluate the ecological integrity of shrublands in Nevada, yielding an assessment based on six indicators of ecosystem structure, function, and composition, including resource- and stressor-based indicators measured at multiple scales. Results varied spatially and among indicators. Invasive plant cover and surface development were highest in shrublands in northwest and southeast Nevada. Departure from reference conditions of shrubland area, composition, patch size, and connectivity was highest in central and northern Nevada. Results may inform efforts to control invasive species and restore shrublands on federal lands in Nevada. We suggest that ecological integrity assessments for multiple-use lands be grounded in existing policies and monitoring programs, incorporate resource- and stressor-based metrics, rely on publicly available data collected at multiple spatial scales, and quantify both natural reference and societally desired resource conditions.","language":"English","publisher":"Springer","doi":"10.1007/s00267-019-01163-w","usgsCitation":"Carter, S.K., Fleishman, E., Leinwand, I., Flather, C.H., Carr, N.B., Fogarty, F.A., Leu, M., Noon, B.R., Wohlfeil, M., and Wood, D.J., 2019, Quantifying ecological integrity of terrestrial systems to inform management of multiple-use public lands in the United States: Environmental Management, v. 64, no. 1, p. 1-19, https://doi.org/10.1007/s00267-019-01163-w.","productDescription":"19 p.","startPage":"1","endPage":"19","ipdsId":"IP-088250","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell 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A. 0000-0003-4315-5160 dwood@usgs.gov","orcid":"https://orcid.org/0000-0003-4315-5160","contributorId":177588,"corporation":false,"usgs":true,"family":"Wood","given":"David","email":"dwood@usgs.gov","middleInitial":"J. A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":761625,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70203056,"text":"70203056 - 2019 - Satellite tracking of gulls and genomic characterization of fecal bacteria reveals environmentally mediated acquisition and dispersal of antimicrobial resistant Escherichia coli on the Kenai Peninsula, Alaska","interactions":[],"lastModifiedDate":"2019-07-23T13:33:36","indexId":"70203056","displayToPublicDate":"2019-04-13T08:04:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Satellite tracking of gulls and genomic characterization of fecal bacteria reveals environmentally mediated acquisition and dispersal of antimicrobial resistant Escherichia coli on the Kenai Peninsula, Alaska","docAbstract":"Gulls (Larus spp.) have frequently been reported to carry Escherichia coli exhibiting antimicrobial resistance (AMR E. coli); however, the pathways governing the acquisition and dispersal of such bacteria are not well-described. We equipped 17 landfill-foraging gulls with satellite transmitters and collected gull fecal samples longitudinally from four locations on the Kenai Peninsula, Alaska to assess: 1) gull attendance and transitions between sites, 2) spatiotemporal prevalence of fecally-shed AMR E. coli, and 3) genomic relatedness of AMR E. coli isolates among sites. We also sampled Pacific salmon (Oncorhynchus spp.) harvested as part of personal-use dipnet fisheries at two sites to assess potential contamination with AMR E. coli. Among our study sites, marked gulls most commonly occupied the lower Kenai River (61% of site locations) followed by the Soldotna landfill (11%), lower Kasilof River (5%), and upper Kenai River (<1%). Gulls primarily moved between the Soldotna landfill and the lower Kenai River (94% of transitions among sites), which were also the two locations with the highest prevalence of AMR E. coli. There was relatively high spatial and temporal variability in AMR E. coli prevalence in gull feces and there was no evidence of contamination on salmon harvested in personal-use fisheries. We identified E. coli sequence types and AMR genes of clinical importance, with some isolates possessing genes associated with resistance to as many as eight antibiotic classes. Our findings suggest that gulls acquire AMR E. coli at habitats with anthropogenic inputs and subsequent movements may represent pathways through which AMR is dispersed.","language":"English","doi":"10.1111/mec.15101","usgsCitation":"Ahlstrom, C., Bonnedahl, J., Woksepp, H., Hernandez, J., Reed, J., Tibbitts, T.L., Olsen, B., Douglas, D., and Ramey, A.M., 2019, Satellite tracking of gulls and genomic characterization of fecal bacteria reveals environmentally mediated acquisition and dispersal of antimicrobial resistant Escherichia coli on the Kenai Peninsula, Alaska: Molecular Ecology, v. 28, no. 10, p. 2531-2545, https://doi.org/10.1111/mec.15101.","productDescription":"15 p.","startPage":"2531","endPage":"2545","ipdsId":"IP-104186","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":437499,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FZ4OJW","text":"USGS data release","linkHelpText":"Tracking Data for Three Large-bodied Gull Species and Hybrids (Larus spp.)"},{"id":437498,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D72Q3W","text":"USGS data release","linkHelpText":"Sampling, antimicrobial resistance testing, and genomic typing of E. coli in gulls (Larus spp.) on the Kenai Peninsula, Alaska, 2016"},{"id":362968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kenai Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -151.5509033203125,\n 60.06209914960289\n ],\n [\n -149.76013183593747,\n 60.06209914960289\n ],\n [\n -149.76013183593747,\n 60.576174726269265\n ],\n [\n -151.5509033203125,\n 60.576174726269265\n ],\n [\n -151.5509033203125,\n 60.06209914960289\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Ahlstrom, Christina 0000-0001-5414-8076","orcid":"https://orcid.org/0000-0001-5414-8076","contributorId":214540,"corporation":false,"usgs":true,"family":"Ahlstrom","given":"Christina","email":"","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":760970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonnedahl, Jonas","contributorId":181800,"corporation":false,"usgs":false,"family":"Bonnedahl","given":"Jonas","email":"","affiliations":[],"preferred":false,"id":760971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woksepp, Hanna","contributorId":207263,"corporation":false,"usgs":false,"family":"Woksepp","given":"Hanna","email":"","affiliations":[],"preferred":false,"id":760972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hernandez, Jorge","contributorId":203652,"corporation":false,"usgs":false,"family":"Hernandez","given":"Jorge","affiliations":[{"id":36674,"text":"Department of Microbiology, Kalmar County Hospital, Kalmar, Sweden","active":true,"usgs":false}],"preferred":false,"id":760973,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, John 0000-0002-3239-6906","orcid":"https://orcid.org/0000-0002-3239-6906","contributorId":214852,"corporation":false,"usgs":true,"family":"Reed","given":"John","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":760974,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tibbitts, T. Lee 0000-0002-0290-7592 ltibbitts@usgs.gov","orcid":"https://orcid.org/0000-0002-0290-7592","contributorId":102185,"corporation":false,"usgs":true,"family":"Tibbitts","given":"T.","email":"ltibbitts@usgs.gov","middleInitial":"Lee","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":760975,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Olsen, Bjorn","contributorId":214853,"corporation":false,"usgs":false,"family":"Olsen","given":"Bjorn","email":"","affiliations":[{"id":39125,"text":"Uppsala University, Uppsala, Sweden","active":true,"usgs":false}],"preferred":false,"id":760976,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":150115,"corporation":false,"usgs":true,"family":"Douglas","given":"David C.","email":"ddouglas@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":760977,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":760978,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70217883,"text":"70217883 - 2019 - A framework for characterising and evaluating the effectiveness of environmental modelling","interactions":[],"lastModifiedDate":"2021-02-09T13:22:03.223877","indexId":"70217883","displayToPublicDate":"2019-04-13T07:20:32","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A framework for characterising and evaluating the effectiveness of environmental modelling","docAbstract":"Environmental modelling is transitioning from the traditional paradigm that focuses on the model and its quantitative performance to a more holistic paradigm that recognises successful model-based outcomes are closely tied to undertaking modelling as a social process, not just as a technical procedure. This paper redefines evaluation as a multi-dimensional and multi-perspective concept, and proposes a more complete framework for identifying and measuring the effectiveness of modelling that serves the new paradigm. Under this framework, evaluation considers a broader set of success criteria, and emphasises the importance of contextual factors in determining the relevance and outcome of the criteria. These evaluation criteria are grouped into eight categories: project efficiency, model accessibility, credibility, saliency, legitimacy, satisfaction, application, and impact. Evaluation should be part of an iterative and adaptive process that attempts to improve model-based outcomes and foster pathways to better futures.
This report provides trench photomosaics, logs and related site information, age data, and earthquake event evidence from three paleoseismic trench sites on the Bear River Fault Zone. Our motivation for studying the Bear River Fault Zone—a nascent normal fault in the Rocky Mountains east of the Basin and Range physiographic province—is twofold: (1) the intriguing conclusion from previous work that the neotectonic history of the fault may have begun in the middle to late Holocene and consists of only two surface-rupturing earthquakes and (2) the question of whether large scarps (>10 meters in height) observed along the fault represent net tectonic displacement, which, given a two-event history, would put the displacements among the largest in the Basin and Range region. In presenting our trench and initial geomorphic interpretations, this report lays the groundwork for further exploration of these issues.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3430","usgsCitation":"Hecker, S., DuRoss, C.B., Schwartz, D.P., Cinti, F.R., Civico, R., Lund, W.R., Hiscock, A.I., West, M.W., Wilcox, T., and Stoller, A.R., 2019, Stratigraphic and structural relations in trench exposures and geomorphology at the Big Burn, Lily Lake, and Lester Ranch sites, Bear River Fault Zone, Utah and Wyoming: U.S. Geological Survey Scientific Investigations Map 3430, 8 p., 3 sheets, https://doi.org/10.3133/sim3430.","productDescription":"Report: 13 p.; Sheet 1: 58.03 x 27.83 in.; Sheet 2: 48.68 x 29.19 in.; Sheet 3: 52.58 x 28.94 in.","ipdsId":"IP-087181","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":362927,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3430/sim3430_sheet1.pdf","text":"Sheet 1","size":"30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigations Map 3430 Sheet 1"},{"id":362928,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3430/sim3430_sheet2.pdf","text":"Sheet 2","size":"45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigations Map 3430 Sheet 2"},{"id":362929,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3430/sim3430_sheet3.pdf","text":"Sheet 3","size":"50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigations Map 3430 Sheet 3"},{"id":362930,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3430/coverthb.jpg"},{"id":362926,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3430/sim3430_pamphlet.pdf","text":"Pamphlet","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Utah, Wyoming","otherGeospatial":"Bear River Fault Zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.92483520507812,\n 40.69001034095325\n ],\n [\n -110.60211181640624,\n 40.69001034095325\n ],\n [\n -110.60211181640624,\n 41.20345619205131\n ],\n [\n -110.92483520507812,\n 41.20345619205131\n ],\n [\n -110.92483520507812,\n 40.69001034095325\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Earthquake Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
Sea otters (Enhydra lutris) are an apex predator of the nearshore marine community and nearly went extinct at the turn of the 20th century. Reintroductions and legal protection allowed sea otters to re‐colonize much of their former range. Our objective was to chronicle the colonization of this apex predator in Glacier Bay, Alaska, to help understand the mechanisms that governed their successful colonization.
Glacier Bay is a tidewater glacier fjord in southeastern Alaska that was entirely covered by glaciers in the mid‐18th century. Since then, it has endured the fastest tidewater glacier retreat in recorded history.
We collected and analysed several data sets, spanning 20 years, to document the spatio‐temporal dynamics of an apex predator expanding into an area where they were formerly absent. We used novel quantitative tools to model the occupancy, abundance and colonization dynamics of sea otters, while accounting for uncertainty in the data collection process, the ecological process and model parameters.
Twenty years after sea otters were first observed colonizing Glacier Bay, they became one of the most abundant and widely distributed marine mammal. The population grew exponentially at a rate of 20% per year. They colonized Glacier Bay at a maximum rate of 6 km per year, with faster colonization rates occurring early in the colonization process. During colonization, sea otters selected shallow areas, close to shore, with a steep bottom slope, and a relatively simple shoreline complexity index.
The growth and expansion of sea otters in Glacier Bay demonstrate how legal protection and translocation of apex predators can facilitate their successful establishment into a community in which they were formerly absent. The success of sea otters was, in part, a consequence of habitat that was left largely unperturbed by humans for the past 250 years. Further, sea otters and other marine predators, whose distribution is limited by ice, have the potential to expand in distribution and abundance, reshaping future marine communities in the wake of deglaciation and global loss of sea ice.