Accidental introductions of rodents present one of the greatest threats to indigenous island biota, especially seabirds. On uninhabited remote islands, such introductions are likely to come from shipwrecks. Here we use a comprehensive database of shipwrecks in Western Alaska to model the frequency of shipwrecks per Aleutian and Bering Sea island, taken as a proxy for the threat of rodent introductions, using physical variables, and the intensity of nearby fishing traffic and activity as predictors. Using data spanning from 1950 to 2013, we found that shipwrecks were particularly common in the 1980s to early 2000s, with a major peak in wrecks during the late 1980s. Amount of fishing activity within 5 km of an island was the strongest predictor of shipwrecks, followed by the strength of tidal currents and density of large-vessel traffic. Islands with the highest frequency of shipwrecks are all in the eastern Aleutians, including Unimak, Unalaska, and Akun Islands. By contrast, the largest seabird colonies are in the western Aleutian and Pribilof Islands, including Buldir, Kiska, and Saint George islands. Multiplying the frequency of a shipwreck by the number of seabirds breeding per island provides a measure of risk. The risk of rodent introductions from shipwrecks to seabirds was then greatest for Saint George (Bering Sea), Buldir (Western Aleutians) and Saint Matthew islands (Bering Sea). Keeping these high-risk islands rodent free would maintain their high a conservation value. Most islands with a high predicted frequency of shipwrecks already have established rodent populations and therefore few remaining seabirds. Of those islands with established rodent populations, Attu and Kiska Islands would make suitable targets for eradication, given their relatively low expected frequency of shipwrecks for their size. Further improvements in rat prevention on vessels and shipping safety would benefit the economy, human health and safety, and to the long-term conservation of island ecosystems.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-018-1726-z","usgsCitation":"Renner, M., Nelson, E., Watson, J., Haynie, A., Poe, A., Robards, M.D., and Hess, S.C., 2018, The risk of rodent introductions from shipwrecks to seabirds on Aleutian and Bering Sea islands: Biological Invasions, v. 20, no. 9, p. 2679-2690, https://doi.org/10.1007/s10530-018-1726-z.","productDescription":"12 p.","startPage":"2679","endPage":"2690","ipdsId":"IP-090330","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":356983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian Islands, Bering Sea Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -188.08593749999997,\n 50.62507306341435\n ],\n [\n -153.369140625,\n 50.62507306341435\n ],\n [\n -153.369140625,\n 60.80206374467983\n ],\n [\n -188.08593749999997,\n 60.80206374467983\n ],\n [\n -188.08593749999997,\n 50.62507306341435\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-12","publicationStatus":"PW","scienceBaseUri":"5b98a26ce4b0702d0e842ea2","contributors":{"authors":[{"text":"Renner, Martin","contributorId":198248,"corporation":false,"usgs":false,"family":"Renner","given":"Martin","email":"","affiliations":[],"preferred":false,"id":743980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Eric","contributorId":140476,"corporation":false,"usgs":false,"family":"Nelson","given":"Eric","affiliations":[{"id":13511,"text":"Cornell Univesity","active":true,"usgs":false}],"preferred":false,"id":743981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watson, Jordan","contributorId":198249,"corporation":false,"usgs":false,"family":"Watson","given":"Jordan","affiliations":[],"preferred":false,"id":743982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haynie, Alan","contributorId":198250,"corporation":false,"usgs":false,"family":"Haynie","given":"Alan","email":"","affiliations":[],"preferred":false,"id":743983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poe, Aaron","contributorId":198251,"corporation":false,"usgs":false,"family":"Poe","given":"Aaron","affiliations":[],"preferred":false,"id":743984,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robards, Martin D.","contributorId":40148,"corporation":false,"usgs":false,"family":"Robards","given":"Martin","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":743985,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hess, Steve C. 0000-0001-6403-9922 shess@usgs.gov","orcid":"https://orcid.org/0000-0001-6403-9922","contributorId":150366,"corporation":false,"usgs":true,"family":"Hess","given":"Steve","email":"shess@usgs.gov","middleInitial":"C.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":743979,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70198617,"text":"ofr20181131 - 2018 - Research to improve ShakeAlert earthquake early warning products and their utility","interactions":[],"lastModifiedDate":"2018-08-31T09:32:14","indexId":"ofr20181131","displayToPublicDate":"2018-08-30T14:20:57","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1131","title":"Research to improve ShakeAlert earthquake early warning products and their utility","docAbstract":"Earthquake early warning (EEW) is the rapid detection of an earthquake and issuance of an alert or notification to people and vulnerable systems likely to experience potentially damaging ground shaking. The level of ground shaking that is considered damaging is defined by the specific application; for example, manufacturing equipment may experience damage at a lower intensity ground shaking than would cause damage to a building. Along the West Coast of the United States, the warning times for ground shaking could range as high as tens of seconds for moderate levels of ground shaking, or potentially longer, if a lower ground-shaking threshold is used to issue alerts. However, it is not always possible to provide advance warning of ground shaking, particularly for locations close to an earthquake that are most likely to experience very strong ground shaking. EEW alerts may be useful to individuals who can use a few seconds to move to a safe zone and to electromechanical systems that can take automatic actions to reduce damage and injuries. An EEW system, ShakeAlert, has been under development in the United States since 2006. Federal and State governments, as well as the private sector, are now investing in the ShakeAlert prototype system that will, when completed, become an operational public system for the West Coast of the United States.
While the current prototype is delivering alerts to test users, improvements to the accuracy, timeliness, and utility of the alerts are needed. For this reason, it is essential that the ShakeAlert system be continuously improved through targeted research, involving not only the current ShakeAlert partner organizations, but also the broader scientific, engineering, and emergencyresponse communities. To this end, this report describes the opportunities for improvement that can be addressed through research and development over the next 5 years.
Our recommendations are organized into four areas: (1) understand EEW capabilities and user needs, (2) make alerts as fast and accurate as possible, (3) ensure reliability when it counts, and (4) explore the use of new instrumentation.
The first challenge is to understand EEW capabilities and user needs. EEW must deliver actionable information to people and to automated systems to mitigate short- and longterm impacts of damaging ground shaking, so development of EEW must be motivated by the needs of users. Within this challenge, we must study the technical capabilities and limitations of EEW in general, and the ShakeAlert system specifically. This includes development of performance metrics that assess the timeliness and accuracy of alerts to understand the value and utility of the ShakeAlert EEW product(s) for various user groups, including different industry sectors, emergency-management agencies, and the public. Research is needed to define the alerting choices that maximize the utility of the system for users and to determine what the available communication pathways are for providing timely alert information. Additionally, we engage users to assess how alerts will be used by different sectors to mitigate losses and to inform EEW product design. Further, social-science research is needed to develop alert messaging, including what relevant prior and follow-up information are required, to ensure effective use of alerts.
The second challenge is to make alerts as fast and as accurate as possible. The timeliness and accuracy of an EEW alert is important because it will set in motion a series of actions and downstream products. An EEW alert will trigger notification across emergency-alert systems and across multiple communication channels to populations in impacted regions. The EEW alert region may grow as the earthquake fault-rupture length increases, and the EEW system’s characterization of it, evolves. We must continue research into new or improved seismic and geodetic waveform-processing methods necessary to rapidly characterize the expected ground shaking and associated uncertainties. It is important to thoroughly evaluate whether new methods improve alerts through more accurate ground-motion estimates and (or) reduced latencies (that is, longer warning times). New methods could include tracking the extent of a large rupture in real time (known as finite-fault algorithms) and ground-motionbased EEW algorithms. Additionally, ground motion predictions could be optimized for each earthquake as the earthquake fault rupture progresses by using, for example, event terms to shift ground-motion curves for more (or less) energetic ruptures.
The third challenge is to ensure reliability when it counts. This challenge requires us to explore approaches that assess the expected performance of ShakeAlert across the range of earthquake magnitudes, locations, and depths that may occur within the alerting region. Large, damaging earthquakes and their associated aftershock sequences matter most for hazard and for EEW, but these large-earthquake sequences occur infrequently. We expect ShakeAlert to respond robustly to these large-earthquake sequences despite potentially long periods of relative seismic quiescence in the intervening years, and in spite of inevitable communication challenges that arise during and after a large earthquake. We must develop methods to utilize the broadest available datasets to test EEW performance, including ground-motion data recorded in other parts of the world. The observational period for large, damaging earthquakes in any particular region has been short in comparison to estimated large-earthquake recurrence times. Ground-motion records for very large, damaging western United States events and major aftershock sequences do not yet exist, nor do data exist for all potential sources of noise and spurious signals that ShakeAlert must be “tuned” to reject. In addition, robust synthetic data could provide the flexibility to test a wider range of earthquake magnitude, tectonic-setting, and noise scenarios than are covered by existing observational data. Synthetic ground-motion data must be thoroughly vetted against records of smaller magnitude earthquakes to ensure that they accurately capture both the onset and the amplitude of the ground shaking.
The final challenge is to explore the use of new instrumentation. The development of EEW around the world to date has focused on the use of high-quality, scientific-grade seismic and geodetic instrumentation. The use of additional types of instrumentation or information may also improve EEW products by filling gaps in sensor coverage in countries that already have dense seismic networks or enable EEW in countries without such networks. We must keep up with these developments and continuously assess their value in supplementing existing EEW systems, such as ShakeAlert, or enabling EEW where such systems do not exist. Such developments include low-cost instrumentation with microelectromechanical system (MEMS) sensors and global positioning system (GPS)/global navigation satellite system (GNSS) antennas embedded in low-cost consumer electronics, sea-floor seismometers, geodetic instrumentation deployed along the Cascadia and Alaska megathrust margins of western North America, and borehole strainmeters that are already deployed across the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181131","usgsCitation":"Cochran, E.S., Aagaard, B.T., Allen, R.M., Andrews, J., Baltay, A.S., Barbour, A.J., Bodin, P., Brooks, B.A., Chung, A., Crowell, B.W., Given, D.D., Hanks, T.C., Hartog, J.R., Hauksson, E., Heaton, T.H., McBride, S., Meier, M-A., Melgar, D., Minson, S.E., Murray, J.R., Strauss, J.A., and Toomey, D., 2018, Research to improve ShakeAlert earthquake early warning products and their utility: U.S. Geological Survey Open-File Report 2018–1131, 17 p., https://doi.org/10.3133/ofr20181131.","productDescription":"iv, 17 p.","onlineOnly":"Y","ipdsId":"IP-098968","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":356971,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1131/coverthb.jpg"},{"id":356972,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1131/ofr20181131.pdf","text":"Report","size":"600 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2018-1131"}],"contact":"Earthquake Science Center-Pasadena Field Office
U.S. Geological Survey
525 South Wilson Ave.
Pasadena, CA 91106-3212
Cold-water corals provide critical habitats for a multitude of marine species, but are understudied relative to tropical corals. Primnoa pacifica is a cold-water coral prevalent throughout Alaskan waters, while another species in the genus, Primnoa resedaeformis, is widely distributed in the Atlantic Ocean. This study examined the V4-V5 region of the 16S rRNA gene after amplifying and pyrosequencing bacterial DNA from samples of these species. Key differences between the two species’ microbiomes included a robust presence of bacteria belonging to the Chlamydiales order in most of the P. pacifica samples, whereas no more than 2% of any microbial community from P. resedaeformiscomprised these bacteria. Microbiomes of P. resedaeformis exhibited higher diversity than those of P. pacifica, and the two species largely clustered separately in a principal coordinate analysis. Comparison of P. resedaeformis microbiomes from samples collected in two submarine canyons revealed a significant difference between locations. This finding mirrored significant genetic differences among the P. resedaeformis from the two canyons based upon population genetic analysis of microsatellite loci. This study presents the first report of microbiomes associated with these two coral species.
","language":"English","publisher":"Springer","doi":"10.1038/s41598-018-30901-z","usgsCitation":"Goldsmith, D.B., Kellogg, C.A., Morrison, C.L., Gray, M.A., Stone, R.P., Waller, R.G., Brooke, S.D., and Ross, S., 2018, Comparison of microbiomes of cold-water corals Primnoa pacifica and Primnoa resedaeformis, with possible link between microbiome composition and host genotype: Scientific Reports, v. 8, 12383; 15 p., https://doi.org/10.1038/s41598-018-30901-z.","productDescription":"12383; 15 p.","ipdsId":"IP-091190","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468490,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-30901-z","text":"Publisher Index Page"},{"id":356632,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-17","publicationStatus":"PW","scienceBaseUri":"5b98a283e4b0702d0e842f13","contributors":{"authors":[{"text":"Goldsmith, Dawn B. 0000-0003-0080-5346 dgoldsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0080-5346","contributorId":191764,"corporation":false,"usgs":true,"family":"Goldsmith","given":"Dawn","email":"dgoldsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":742920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":742921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morrison, Cheryl L. 0000-0001-9425-691X cmorrison@usgs.gov","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":146488,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","email":"cmorrison@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":742927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gray, Michael A.","contributorId":200715,"corporation":false,"usgs":false,"family":"Gray","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":742922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stone, Robert P.","contributorId":190569,"corporation":false,"usgs":false,"family":"Stone","given":"Robert","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":742923,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waller, Rhian G.","contributorId":195852,"corporation":false,"usgs":false,"family":"Waller","given":"Rhian","email":"","middleInitial":"G.","affiliations":[{"id":16143,"text":"University of Hawaii at Manoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":742924,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brooke, Sandra D.","contributorId":196940,"corporation":false,"usgs":false,"family":"Brooke","given":"Sandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":742925,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ross, Steve W.","contributorId":41134,"corporation":false,"usgs":false,"family":"Ross","given":"Steve W.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":742926,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70198679,"text":"70198679 - 2018 - Flyway structure in the circumpolar greater white‐fronted goose","interactions":[],"lastModifiedDate":"2018-09-20T16:24:20","indexId":"70198679","displayToPublicDate":"2018-08-15T14:08:42","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Flyway structure in the circumpolar greater white‐fronted goose","docAbstract":"Dispersal and migratory behavior are influential factors in determining how genetic diversity is distributed across the landscape. In migratory species, genetic structure can be promoted via several mechanisms including fidelity to distinct migratory routes. Particularly within North America, waterfowl management units have been delineated according to distinct longitudinal migratory flyways supported by banding data and other direct evidence. The greater white‐fronted goose (Anser albifrons) is a migratory waterfowl species with a largely circumpolar distribution consisting of up to six subspecies roughly corresponding to phenotypic variation. We examined the rangewide population genetic structure of greater white‐fronted geese using mtDNA control region sequence data and microsatellite loci from 23 locales across North America and Eurasia. We found significant differentiation in mtDNA between sampling locales with flyway delineation explaining a significant portion of the observed genetic variation (~12%). This is concordant with band recovery data which shows little interflyway or intercontinental movements. However, microsatellite loci revealed little genetic structure suggesting a panmictic population across most of the Arctic. As with many high‐latitude species, Beringia appears to have played a role in the diversification of this species. A common Beringian origin of North America and Asian populations and a recent divergence could at least partly explain the general lack of structure at nuclear markers. Further, our results do not provide strong support for the various taxonomic proposals for this species except for supporting the distinctness of two isolated breeding populations within Cook Inlet, Alaska (A. a. elgasi) and Greenland (A. a. flavirostris), consistent with their subspecies status.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4345","usgsCitation":"Wilson, R.E., Ely, C.R., and Talbot, S.L., 2018, Flyway structure in the circumpolar greater white‐fronted goose: Ecology and Evolution, v. 8, no. 16, p. 8490-8507, https://doi.org/10.1002/ece3.4345.","productDescription":"18 p.","startPage":"8490","endPage":"8507","ipdsId":"IP-092590","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468494,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4345","text":"Publisher Index Page"},{"id":437783,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71G0JGN","text":"USGS data release","linkHelpText":"Greater White-Fronted Goose Genetic Data, Circumpolar, 1988-2009"},{"id":356520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"16","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-30","publicationStatus":"PW","scienceBaseUri":"5b98a286e4b0702d0e842f31","contributors":{"authors":[{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","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":742535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ely, Craig R. 0000-0003-4262-0892 cely@usgs.gov","orcid":"https://orcid.org/0000-0003-4262-0892","contributorId":3214,"corporation":false,"usgs":true,"family":"Ely","given":"Craig","email":"cely@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":742536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","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":742537,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198678,"text":"70198678 - 2018 - A transcriptome resource for the Arctic Cod (Boreogadus saida)","interactions":[],"lastModifiedDate":"2018-11-14T09:37:10","indexId":"70198678","displayToPublicDate":"2018-08-15T14:00:50","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5730,"text":"Marine Genomics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A transcriptome resource for the Arctic Cod (Boreogadus saida)","title":"A transcriptome resource for the Arctic Cod (Boreogadus saida)","docAbstract":"Arctic Cod (Boreogadus saida) serve as an important link in Arctic food webs and are thus considered an important species for environmental monitoring. RNA-Seq was conducted on samples from wild-collected individuals representing various age classes and tissue types to obtain as complete a transcriptome as possible on an Illumina MiSeq, which resulted in a total of 64,457 transcripts with an average length of 295 bp. We identified well-known genes that are associated with temperature change or response to pollutants. This RNA-Seq effort provides the first insight into the B. saida transcriptome, which can be a starting point for investigations identifying genes for local adaptation and genomic responses to future environmental change.
The liverwort flora of Attu Island, the westernmost Aleutian Island in the United States, was studied to assess species diversity in the hyperoceanic sector of the northern boreal subzone. The field study was undertaken in sites selected to represent a spectrum of environmental variation, primarily within the eastern part of the island. Data were analyzed using our own collections on Attu Island, supplemented with information from published reports to compare bryophyte distribution patterns at three levels, the Northern Hemisphere, North America, the Commander Islands of Russia, and Alaska. A total of 112 liverworts were identified and a substantial number, 34 species (30%), were new reports from Attu Island and one was new to Alaska. Geographic elements dominating the flora included arctomontane (26%), arctoboreomontane (23%), montane (20%), and boreal (14%) species, while arctic species were almost absent (1%). The liverworts of the Attu Island-Commander Islands region were widespread species with over 70% circumpolar, or nearly circumpolar; nevertheless large gaps were present in some of their distributions with a floristic depression in liverwort distribution between Attu and the Commander Islands.
","language":"English","publisher":"Botanica Pacifica","doi":"10.17581/bp.2018.07203","usgsCitation":"Talbot, S.S., Schofield, W.B., Vana, J., and Talbot, S.L., 2018, Liverworts from Attu Island, Near Islands, Aleutian Islands, Alaska (USA) with comparison to the Commander Islands (Russia): Botanica Pacifica, v. 7, no. 2, p. 127-141, https://doi.org/10.17581/bp.2018.07203.","productDescription":"15 p.","startPage":"127","endPage":"141","ipdsId":"IP-092332","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":460863,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.17581/bp.2018.07203","text":"Publisher Index Page"},{"id":437786,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92H3W9D","text":"USGS data release","linkHelpText":"Frullania nisquallensis Species Confirmation, Attu Island, Alaska, 2018"},{"id":361715,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","otherGeospatial":"Aleutian Islands, Attu Island, Commander Islands, Near Islands","volume":"7","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Talbot, Stephen S.","contributorId":213927,"corporation":false,"usgs":false,"family":"Talbot","given":"Stephen","email":"","middleInitial":"S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":758709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schofield, Wilfred B.","contributorId":213928,"corporation":false,"usgs":false,"family":"Schofield","given":"Wilfred","email":"","middleInitial":"B.","affiliations":[{"id":38932,"text":"Department of Botany, University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":758710,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vana, Jiri","contributorId":213929,"corporation":false,"usgs":false,"family":"Vana","given":"Jiri","email":"","affiliations":[{"id":38933,"text":"Department of Botany, Charles University","active":true,"usgs":false}],"preferred":false,"id":758711,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","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":758708,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228306,"text":"70228306 - 2018 - An interferometric synthetic aperture radar (InSAR) habitat suitability model to identify overwinter conditions for coregonine whitefishes in Arctic lagoons","interactions":[],"lastModifiedDate":"2022-02-08T17:36:12.932625","indexId":"70228306","displayToPublicDate":"2018-08-12T11:29:59","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"An interferometric synthetic aperture radar (InSAR) habitat suitability model to identify overwinter conditions for coregonine whitefishes in Arctic lagoons","docAbstract":"Lagoons provide critical habitats for many fishes, including coregonine whitefishes, which are a mainstay in many subsistence fisheries of rural communities in Arctic Alaska. Despite their importance, little is known about the overwintering habits of whitefishes in Arctic Alaska due to the challenges associated with sampling during winter. We developed a habitat suitability (HS) model to understand the potential range of physical conditions that whitefishes experience during the Arctic winter, using three indicator lagoons that represent a range of environmental characteristics. The HS model was built using a three-step approach. First, remote sensing that uses interferometric synthetic aperture radar (InSAR) identified areas of floating and bottomfast ice. Second, through in-field ground-truthing, we confirmed the presence and quality of liquid water (water depth, temperature, and dissolved oxygen) beneath the ice cover. Third, we assessed the suitability of that liquid water as habitat for whitefishes based on published literature and expert interpretation of water quality parameters. InSAR determined that 0, 65.4, and 88.2% of the three lagoons were composed of floating ice corresponding with areas of liquid water beneath a layer of ice. The HS model indicated that all three lagoons had reduced suitability as whitefish habitat in winter than in summer due to the loss of habitat because of the presence of bottomfast ice and a reduction in the quality of liquid water due to cold temperatures, high salinities, and low dissolved oxygen levels. However, only the shallowest lagoon had lethal conditions and zero suitability as whitefish habitat. The methods outlined here provide a simple, cost-effective method to identify habitats that consistently provide critical winter habitat and integrate remote sensing in a HS model framework.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10111","usgsCitation":"Tibbles, M., Falke, J.A., Mahoney, A.R., Robards, M., and Seitz, A.C., 2018, An interferometric synthetic aperture radar (InSAR) habitat suitability model to identify overwinter conditions for coregonine whitefishes in Arctic lagoons: Transactions of the American Fisheries Society, v. 147, no. 6, p. 1167-1178, https://doi.org/10.1002/tafs.10111.","productDescription":"12 p.","startPage":"1167","endPage":"1178","ipdsId":"IP-097751","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468503,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10686345","text":"External Repository"},{"id":395635,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Cape Krusenstern National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.6416015625,\n 67.08455048507471\n ],\n [\n -162.960205078125,\n 67.26779766322973\n ],\n [\n -163.19091796875,\n 67.4285812540874\n ],\n [\n -163.135986328125,\n 67.80924450600011\n ],\n [\n -164.05883789062497,\n 67.80509469602548\n ],\n [\n -164.278564453125,\n 67.64267630796034\n ],\n [\n -163.916015625,\n 67.09738040223989\n ],\n [\n -163.2568359375,\n 66.99884379185184\n ],\n [\n -162.6416015625,\n 67.08455048507471\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"147","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Tibbles, Marguerite","contributorId":275096,"corporation":false,"usgs":false,"family":"Tibbles","given":"Marguerite","email":"","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":833643,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833644,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mahoney, Andrew R.","contributorId":275097,"corporation":false,"usgs":false,"family":"Mahoney","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":833645,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robards, Martin D.","contributorId":275099,"corporation":false,"usgs":false,"family":"Robards","given":"Martin D.","affiliations":[{"id":56701,"text":"wsc","active":true,"usgs":false}],"preferred":false,"id":833646,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seitz, Andrew C.","contributorId":275102,"corporation":false,"usgs":false,"family":"Seitz","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":833647,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203008,"text":"70203008 - 2018 - Sex-specific variation in denning by brown bears","interactions":[],"lastModifiedDate":"2019-11-25T14:35:54","indexId":"70203008","displayToPublicDate":"2018-08-07T14:30:57","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2653,"text":"Mammalian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Sex-specific variation in denning by brown bears","docAbstract":"Denning characteristics of brown bears (Ursus arctos) have been described in numerous studies; however, population specific factors (i.e., landscape characteristics and climate) can greatly influence the location and timing of denning. Our objective was to evaluate den-site characteristics and denning chronology for male and female brown bears in Lake Clark National Park and Preserve, Alaska. We used maximum entropy modeling to characterize attributes of den sites and generalized linear mixed models to compare denning chronology between males and females. We located 70 den sites (19 male and 51 female) and documented den entrance (n = 61 [15 male and 46 female]) and emergence (n = 60 [13 male and 47 female]) dates for bears from fall 2014 to spring 2017. The best performing model for estimating probable male den-site use (AUC = 0.862) was most influenced by slope (79.5%). The most parsimonious female model (AUC = 0.910) included elevation (49.3%), slope (43.1%), and aspect (7.6%). Female brown bears on average denned at higher elevations (868, SE = 190 m) than males (762, SE = 195 m) (F1,73 = 4.08, P = 0.047). Additionally, female bears entered dens 8 days earlier than males (SE = 12.82; 20 and 28 October, respectively, P = 0.04), and although not significant (P = 0.09), average female den emergence dates were 7 days (SE = 15.14) later than males. With the potential for increased human activities (i.e. resource extraction and associated access), gaining an understanding of population specific denning requirements is essential for developing future management actions. Our results provide valuable information that will allow decision makers to structure future development in a way that avoids habitats important for denning, and allows for reduced disturbance of winter den sites.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.mambio.2018.08.001","usgsCitation":"Mangipane, L., Belant, J.L., Mangipane, B., Gustine, D., and Hilderbrand, G., 2018, Sex-specific variation in denning by brown bears: Mammalian Biology, v. 93, p. 38-44, https://doi.org/10.1016/j.mambio.2018.08.001.","productDescription":"7 p.","startPage":"38","endPage":"44","ipdsId":"IP-088749","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":369571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Lake Clark National Park and Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.14892578125,\n 59.65664225341022\n ],\n [\n -153.2867431640625,\n 59.65664225341022\n ],\n [\n -153.2867431640625,\n 60.76184270045503\n ],\n [\n -155.14892578125,\n 60.76184270045503\n ],\n [\n -155.14892578125,\n 59.65664225341022\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"93","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mangipane, Lindsey","contributorId":201731,"corporation":false,"usgs":false,"family":"Mangipane","given":"Lindsey","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":760762,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belant, Jerrold L.","contributorId":108394,"corporation":false,"usgs":false,"family":"Belant","given":"Jerrold","email":"","middleInitial":"L.","affiliations":[{"id":35599,"text":"Carnivore Ecology Laboratory, Mississippi State University, Mississippi State, MS","active":true,"usgs":false}],"preferred":false,"id":760763,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mangipane, Buck","contributorId":211731,"corporation":false,"usgs":false,"family":"Mangipane","given":"Buck","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":760764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gustine, David","contributorId":200449,"corporation":false,"usgs":false,"family":"Gustine","given":"David","affiliations":[],"preferred":false,"id":760765,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hilderbrand, Grant V. 0000-0002-0051-8315 ghilderbrand@usgs.gov","orcid":"https://orcid.org/0000-0002-0051-8315","contributorId":199764,"corporation":false,"usgs":true,"family":"Hilderbrand","given":"Grant V.","email":"ghilderbrand@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":760761,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198472,"text":"70198472 - 2018 - Pliocene erosional pulse and glacier-landscape feedbacks in the western Alaska Range","interactions":[],"lastModifiedDate":"2018-09-25T14:35:27","indexId":"70198472","displayToPublicDate":"2018-08-06T12:04:39","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Pliocene erosional pulse and glacier-landscape feedbacks in the western Alaska Range","docAbstract":"Pliocene–Pleistocene glaciation modified the topography and erosion of most middle- and high-latitude mountain belts, because the evolution of catchment topography controls long-term glacier mass balance and erosion. Hence, characterizing how erosion rates change during repeated glaciations can help test hypothesized glacier erosion-landscape feedbacks across a range of settings. To better understand how glaciations and landscapes coevolve on geologic timescales, I quantify erosion rates in the glaciated western Alaska Range with low-temperature thermochronometric data and modeling. Zircon (U–Th)/He and apatite fission track data suggest mountain-building was underway by the early Miocene. In contrast, lower-temperature apatite (U–Th)/He age-elevation and grain age-kinetic data indicate that erosion accelerated coincident with regional Pliocene glaciation ca. 4 Ma. Furthermore, erosion rates calculated within an eroding half-space indicate slow erosion at a rate ≤0.3 km/m.y. before 4.2 Ma, an initial pulse of rapid erosion at a rate of 1.0–1.6 km/m.y. during 4.2–2.9 Ma, and more moderate erosion at a rate of 0.4–0.7 km/m.y. since 2.9 Ma. The initial erosion pulse suggests a significant transient landscape adjustment to the introduction of efficient glacial erosion. The subsequent decrease in Pleistocene erosion rates is consistent with a negative feedback between continuing glaciation and glacier size/erosivity: If glacial erosion outpaces rock uplift, glacier erosion decreases over time as topography, mass balance, valley gradients, and ice flux are reduced. These findings imply that in areas of moderate rock uplift rates, the onset of local Plio–Pleistocene glaciation may have been punctuated by an initial pulse of rapid landscape change, after which change became more gradual.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2018.06.009","usgsCitation":"Lease, R.O., 2018, Pliocene erosional pulse and glacier-landscape feedbacks in the western Alaska Range: Earth and Planetary Science Letters, v. 497, p. 62-68, https://doi.org/10.1016/j.epsl.2018.06.009.","productDescription":"7 p.","startPage":"62","endPage":"68","ipdsId":"IP-080067","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":468520,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2018.06.009","text":"Publisher Index Page"},{"id":437800,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZNIHT7","text":"USGS data release","linkHelpText":"Low-Temperature Thermochronometric Data from the Revelation Mountains, Western Alaska Range, 2013-2018"},{"id":356187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.33,\n 61.33\n ],\n [\n -153.67,\n 61.33\n ],\n [\n -153.67,\n 61.83\n ],\n [\n -154.33,\n 61.83\n ],\n [\n -154.33,\n 61.33\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"497","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc3dfe4b0f5d57878e911","contributors":{"authors":[{"text":"Lease, Richard O. 0000-0003-2582-8966 rlease@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-8966","contributorId":5098,"corporation":false,"usgs":true,"family":"Lease","given":"Richard","email":"rlease@usgs.gov","middleInitial":"O.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":741561,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70198785,"text":"70198785 - 2018 - Lake levels in a discontinuous permafrost landscape: Late Holocene variations inferred from sediment oxygen isotopes, Yukon Flats, Alaska","interactions":[],"lastModifiedDate":"2018-08-24T11:44:58","indexId":"70198785","displayToPublicDate":"2018-08-03T16:34:14","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":899,"text":"Arctic, Antarctic, and Alpine Research","active":true,"publicationSubtype":{"id":10}},"title":"Lake levels in a discontinuous permafrost landscape: Late Holocene variations inferred from sediment oxygen isotopes, Yukon Flats, Alaska","docAbstract":"During recent decades, lake levels in the Yukon Flats region of interior Alaska have fluctuated dramatically. However, prior to recorded observations, no data are available to indicate if similar or more extreme variations occurred during past centuries and millennia. This study explores the history of Yukon Flats lake origins and lake levels for the past approximately 5,500 years from sediment analyses guided by previous work on permafrost extent, thermokarst, and modern isotope hydrology. Sediments dated by 210Pb and AMS radiocarbon indicate stable chronologies following initial lake initiation. Subsequent lithology is autochthonous, and oxygen isotope ratios of endogenic carbonate reflect lake level change at multiple time scales. Sediment results indicate high lake levels between approximately 4000 and 1850 cal yr BP, which is interpreted to reflect wetter-than-modern conditions. Lower lake levels with short-lived high stands during the past approximately 800 years reflect generally arid conditions with brief wet intervals similar to the region’s moisture regime today. The millennial trend is one of increasing aridity and corresponds closely with fire reconstructions and regional paleoclimatic trends. We conclude that high-magnitude lake-level fluctuations and decadal scale trends occurred before the observational period and are persistent hydroclimatic features of the Yukon Flats region.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15230430.2018.1496565","usgsCitation":"Anderson, L., Finney, B.P., and Shapley, M.D., 2018, Lake levels in a discontinuous permafrost landscape: Late Holocene variations inferred from sediment oxygen isotopes, Yukon Flats, Alaska: Arctic, Antarctic, and Alpine Research, v. 50, no. 1, e1496565; 27 p., https://doi.org/10.1080/15230430.2018.1496565.","productDescription":"e1496565; 27 p.","ipdsId":"IP-082065","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468522,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/15230430.2018.1496565","text":"Publisher Index Page"},{"id":356634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon Flats","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150,\n 64.87825917194242\n ],\n [\n -142,\n 64.87825917194242\n ],\n [\n -142,\n 67.50523546529972\n ],\n [\n -150,\n 67.50523546529972\n ],\n [\n -150,\n 64.87825917194242\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-03","publicationStatus":"PW","scienceBaseUri":"5b98a28ae4b0702d0e842f53","contributors":{"authors":[{"text":"Anderson, Lesleigh 0000-0002-5264-089X land@usgs.gov","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":436,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","email":"land@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":742947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finney, Bruce P.","contributorId":199566,"corporation":false,"usgs":false,"family":"Finney","given":"Bruce","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":742948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shapley, Mark D.","contributorId":199569,"corporation":false,"usgs":false,"family":"Shapley","given":"Mark","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":742949,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198369,"text":"70198369 - 2018 - Riparian defoliation by the invasive green alder sawfly influences terrestrial prey subsidies to salmon streams","interactions":[],"lastModifiedDate":"2018-09-28T09:11:06","indexId":"70198369","displayToPublicDate":"2018-08-02T11:41:54","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Riparian defoliation by the invasive green alder sawfly influences terrestrial prey subsidies to salmon streams","docAbstract":"Invasive species in riparian forests are unique as their effects can transcend ecosystem boundaries via stream‐riparian linkages. The green alder sawfly (Monsoma pulveratum) is an invasive wasp whose larvae are defoliating riparian thin‐leaf alder (Alnus tenuifolia) stands across southcentral Alaska. To test the hypothesis that riparian defoliation by this invasive sawfly negatively affects the flow of terrestrial prey resources to stream fishes, we sampled terrestrial invertebrates on riparian alder foliage, their subsidies to streams and their consumption by juvenile coho salmon (Oncorhynchus kisutch). Invasive sawflies altered the composition of terrestrial invertebrates on riparian alder foliage and as terrestrial prey subsidies to streams. Community analyses supported these findings revealing that invasive sawflies shifted the community structure of terrestrial invertebrates between seasons and levels of energy flow (riparian foliage, streams and fish). Invasive sawfly biomass peaked mid‐summer, altering the timing and magnitude of terrestrial prey subsidies to streams. Contrary to our hypothesis, invasive sawflies had no effect on the biomass of native taxa on riparian alder foliage, as terrestrial prey subsidies, or in juvenile coho salmon diets. Juvenile coho salmon consumed invasive sawflies when most abundant, but relied more on other prey types selecting against sawflies relative to their availability. Although we did not find effects of invasive sawflies extending to juvenile coho salmon in this study, these results could change as the distribution of invasive sawflies expands or as defoliation intensifies. Nevertheless, riparian defoliation by these invasive sawflies is likely having other ecological effects that merits further investigation.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12407","usgsCitation":"Roon, D.A., Wipfli, M.S., and Kruse, J.J., 2018, Riparian defoliation by the invasive green alder sawfly influences terrestrial prey subsidies to salmon streams: Ecology of Freshwater Fish, v. 27, no. 4, p. 963-975, https://doi.org/10.1111/eff.12407.","productDescription":"13 p.","startPage":"963","endPage":"975","ipdsId":"IP-075675","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":356109,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.5621337890625,\n 60.35141309155354\n ],\n [\n -148.941650390625,\n 60.35141309155354\n ],\n [\n -148.941650390625,\n 61.380936033590665\n ],\n [\n -150.5621337890625,\n 61.380936033590665\n ],\n [\n -150.5621337890625,\n 60.35141309155354\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-11","publicationStatus":"PW","scienceBaseUri":"5b6fc3e9e4b0f5d57878e92b","contributors":{"authors":[{"text":"Roon, David A.","contributorId":42922,"corporation":false,"usgs":true,"family":"Roon","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":741399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":741274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kruse, James J.","contributorId":72245,"corporation":false,"usgs":true,"family":"Kruse","given":"James","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":741400,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201749,"text":"70201749 - 2018 - Landscape genetics identifies streams and drainage infrastructure as dispersal corridors for an endangered wetland bird","interactions":[],"lastModifiedDate":"2019-01-28T15:46:28","indexId":"70201749","displayToPublicDate":"2018-08-01T15:46:22","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Landscape genetics identifies streams and drainage infrastructure as dispersal corridors for an endangered wetland bird","docAbstract":"Anthropogenic alterations to landscape structure and composition can have significant impacts on biodiversity, potentially leading to species extinctions. Population‐level impacts of landscape change are mediated by animal behaviors, in particular dispersal behavior. Little is known about the dispersal habits of rails (Rallidae) due to their cryptic behavior and tendency to occupy densely vegetated habitats. The effects of landscape structure on the movement behavior of waterbirds in general are poorly studied due to their reputation for having high dispersal abilities. We used a landscape genetic approach to test hypotheses of landscape effects on dispersal behavior of the Hawaiian gallinule (Gallinula galeata sandvicensis), an endangered subspecies endemic to the Hawaiian Islands. We created a suite of alternative resistance surfaces representing biologically plausible a priori hypotheses of how gallinules might navigate the landscape matrix and ranked these surfaces by their ability to explain observed patterns in genetic distance among 12 populations on the island of O`ahu. We modeled effective distance among wetland locations on all surfaces using both cumulative least‐cost‐path and resistance‐distance approaches and evaluated relative model performance using Mantel tests, a causal modeling approach, and the mixed‐model maximum‐likelihood population‐effects framework. Across all genetic markers, simulation methods, and model comparison metrics, surfaces that treated linear water features like streams, ditches, and canals as corridors for gallinule movement outperformed all other models. This is the first landscape genetic study on the movement behavior of any waterbird species to our knowledge. Our results indicate that lotic water features, including drainage infrastructure previously thought to be of minimal habitat value, contribute to habitat connectivity in this listed subspecies.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4296","usgsCitation":"van Rees, C.B., Reed, J.M., Wilson, R.E., Underwood, J.G., and Sonsthagen, S.A., 2018, Landscape genetics identifies streams and drainage infrastructure as dispersal corridors for an endangered wetland bird: Ecology and Evolution, v. 8, no. 16, p. 8328-8343, https://doi.org/10.1002/ece3.4296.","productDescription":"16 p.","startPage":"8328","endPage":"8343","ipdsId":"IP-093331","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468532,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4296","text":"Publisher Index Page"},{"id":360770,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai`i","otherGeospatial":"O`ahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.31024169921875,\n 21.215140254089395\n ],\n [\n -157.6263427734375,\n 21.215140254089395\n ],\n [\n -157.6263427734375,\n 21.746744749939243\n ],\n [\n -158.31024169921875,\n 21.746744749939243\n ],\n [\n -158.31024169921875,\n 21.215140254089395\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"16","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-24","publicationStatus":"PW","scienceBaseUri":"5c5022c5e4b0708288f7e823","contributors":{"authors":[{"text":"van Rees, Charles B.","contributorId":198604,"corporation":false,"usgs":false,"family":"van Rees","given":"Charles","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":755178,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, J. Michael","contributorId":198605,"corporation":false,"usgs":false,"family":"Reed","given":"J.","email":"","middleInitial":"Michael","affiliations":[],"preferred":false,"id":755179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","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":755180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Underwood, Jared G.","contributorId":198606,"corporation":false,"usgs":false,"family":"Underwood","given":"Jared","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":755181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","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":755177,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200453,"text":"70200453 - 2018 - Climate change and future wildfire in the western USA: An ecological approach to nonstationarity","interactions":[],"lastModifiedDate":"2018-10-18T13:51:09","indexId":"70200453","displayToPublicDate":"2018-08-01T13:50:42","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Climate change and future wildfire in the western USA: An ecological approach to nonstationarity","docAbstract":"We developed ecologically based climate‐fire projections for the western United States. Using a finer ecological classification and fire‐relevant climate predictors, we created statistical models linking climate and wildfire area burned for ecosections, which are geographic delineations based on biophysical variables. The results indicate a gradient from purely fuel‐limited (antecedent positive water balance anomalies or negative energy balance anomalies) to purely flammability‐limited (negative water balance anomalies or positive energy balance anomalies) fire regimes across ecosections. Although there are other influences (such as human ignitions and management) on fire occurrence and area burned, seasonal climate significantly explains interannual fire area burned. Differences in the role of climate across ecosections are not random, and the relative dominance of climate predictors allows objective classification of ecosection climate‐fire relationships. Expected future trends in area burned range from massive increases, primarily in flammability limited systems near the middle of the water balance deficit distribution, to substantial decreases, in fuel‐limited nonforested systems. We predict increasing area burned in most flammability‐limited systems but predict decreasing area burned in primarily fuel‐limited systems with a flammability‐limited (“hybrid”) component. Compared to 2030–2059 (2040s), projected area burned for 2070–2099 (2080s) increases much more in the flammability and flammability‐dominated hybrid systems than those with equal control and continues to decrease in fuel‐limited hybrid systems. Exceedance probabilities for historical 95th percentile fire years are larger in exclusively flammability‐limited ecosections than in those with fuel controls. Filtering the projected results using a fire‐rotation constraint minimizes overprojection due to static vegetation assumptions, making projections more conservative.
","language":"English","publisher":"AGU","doi":"10.1029/2018EF000878","usgsCitation":"Littell, J.S., McKenzie, D., Wan, H.Y., and Cushman, S.A., 2018, Climate change and future wildfire in the western USA: An ecological approach to nonstationarity: Earth's Future, v. 6, no. 8, p. 1097-1111, https://doi.org/10.1029/2018EF000878.","productDescription":"15 p.","startPage":"1097","endPage":"1111","ipdsId":"IP-097140","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"links":[{"id":468537,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018ef000878","text":"Publisher Index Page"},{"id":358539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"6","issue":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-18","publicationStatus":"PW","scienceBaseUri":"5c10a970e4b034bf6a7e51ca","contributors":{"authors":[{"text":"Littell, Jeremy S. 0000-0002-5302-8280 jlittell@usgs.gov","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":4428,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","email":"jlittell@usgs.gov","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":748942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKenzie, Donald","contributorId":181509,"corporation":false,"usgs":false,"family":"McKenzie","given":"Donald","affiliations":[],"preferred":false,"id":748943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wan, Ho Yi","contributorId":209843,"corporation":false,"usgs":false,"family":"Wan","given":"Ho","email":"","middleInitial":"Yi","affiliations":[{"id":38007,"text":"3Northern Arizona University, School of Earth Sciences and Environmental Sustainability","active":true,"usgs":false}],"preferred":false,"id":748944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cushman, Samuel A.","contributorId":209844,"corporation":false,"usgs":false,"family":"Cushman","given":"Samuel","email":"","middleInitial":"A.","affiliations":[{"id":38008,"text":"US Department of Agriculture Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":748945,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201112,"text":"70201112 - 2018 - Assessment of Alaska rain-on-snow events using dynamical downscaling","interactions":[],"lastModifiedDate":"2018-11-29T12:01:05","indexId":"70201112","displayToPublicDate":"2018-08-01T12:00:58","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5202,"text":"Journal of Applied Meteorology and Climatology","onlineIssn":"1558-8432","printIssn":"1558-8424","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of Alaska rain-on-snow events using dynamical downscaling","docAbstract":"The ice formed by cold-season rainfall or rain on snow (ROS) has striking impacts on the economy and ecology of Alaska. An understanding of the atmospheric drivers of ROS events is required to better predict them and plan for environmental change. The spatially/temporally sparse network of stations in Alaska makes studying such events challenging, and gridded reanalysis or remote sensing products are necessary to fill the gaps. Recently developed dynamically downscaled climate data provide a new suite of high-resolution variables for investigating historical and projected ROS events across all of Alaska from 1979 to 2100. The dynamically downscaled reanalysis data of ERA-Interim replicated the seasonal patterns of ROS events but tended to produce more rain events than in station observations. However, dynamical downscaling reduced the bias toward more rain events in the coarse reanalysis. ROS occurred most frequently over southwestern and southern coastal regions. Extreme events with the heaviest rainfall generally coincided with anomalous high pressure centered to the south/southeast of the locations receiving the event and warm-air advection from the resulting southwesterly wind flow. ROS events were projected to increase in frequency overall and for extremes across most of the region but were expected to decline over southwestern/southern Alaska. Increases in frequency were projected as a result of more frequent winter rainfall, but the number of ROS events may ultimately decline in some areas as a result of temperatures rising above the freezing threshold. These projected changes in ROS can significantly affect wildlife, vegetation, and human activities across the Alaska landscape.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JAMC-D-17-0276.1","usgsCitation":"Bieniek, P.A., Bhatt, U.S., Walsh, J.E., Lader, R., Griffith, B., Roach, J.K., and Thoman, R.L., 2018, Assessment of Alaska rain-on-snow events using dynamical downscaling: Journal of Applied Meteorology and Climatology, v. 57, p. 1847-1863, https://doi.org/10.1175/JAMC-D-17-0276.1.","productDescription":"17 p.","startPage":"1847","endPage":"1863","ipdsId":"IP-091265","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468541,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1175/jamc-d-17-0276.1","text":"External Repository"},{"id":359794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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K.","contributorId":210911,"corporation":false,"usgs":false,"family":"Roach","given":"Jennifer","email":"","middleInitial":"K.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":752723,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thoman, Richard L.","contributorId":210912,"corporation":false,"usgs":false,"family":"Thoman","given":"Richard","email":"","middleInitial":"L.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":752724,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208432,"text":"70208432 - 2018 - Lactation and resource limitation affect stress responses, thyroid hormones, immune function, and antioxidant capacity of sea otters (Enhydra lutris)","interactions":[],"lastModifiedDate":"2020-02-10T06:21:01","indexId":"70208432","displayToPublicDate":"2018-07-25T12:28:54","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Lactation and resource limitation affect stress responses, thyroid hormones, immune function, and antioxidant capacity of sea otters (Enhydra lutris)","docAbstract":"Lactation is the most energetically demanding stage of reproduction in female mammals. Increased energetic allocation toward current reproduction may result in fitness costs, although the mechanisms underlying these trade‐offs are not well understood. Trade‐offs during lactation may include reduced energetic allocation to cellular maintenance, immune response, and survival and may be influenced by resource limitation. As the smallest marine mammal, sea otters (Enhydra lutris) have the highest mass‐specific metabolic rate necessitating substantial energetic requirements for survival. To provide the increased energy needed for lactation, female sea otters significantly increase foraging effort, especially during late‐lactation. Caloric insufficiency during lactation is reflected in the high numbers of maternal deaths due to End‐Lactation Syndrome in the California subpopulation. We investigated the effects of lactation and resource limitation on maternal stress responses, metabolic regulation, immune function, and antioxidant capacity in two subspecies of wild sea otters (northern: E. l. nereis and southern: E. l. kenyoni) within the California, Washington, and Alaska subpopulations. Lactation and resource limitation were associated with reduced glucocorticoid responses to acute capture stress. Corticosterone release was lower in lactating otters. Cortisol release was lower under resource limitation and suppression during lactation was only evident under resource limitation. Lactation and resource limitation were associated with alterations in thyroid hormones. Immune responses and total antioxidant capacity were not reduced by lactation or resource limitation. Southern sea otters exhibited higher concentrations of antioxidants, immunoglobulins, and thyroid hormones than northern sea otters. These data provide evidence for allocation trade‐offs during reproduction and in response to nutrient limitation but suggest self‐maintenance of immune function and antioxidant defenses despite energetic constraints. Income‐breeding strategists may be especially vulnerable to the consequences of stress and modulation of thyroid function when food resources are insufficient to support successful reproduction and may come at a cost to survival, and thereby influence population trends.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4280","usgsCitation":"Chinn, S., Monson, D., Tinker, M., Staedler, M.M., and Crocker, D.E., 2018, Lactation and resource limitation affect stress responses, thyroid hormones, immune function, and antioxidant capacity of sea otters (Enhydra lutris): Ecology and Evolution, v. 8, no. 16, p. 8433-8447, https://doi.org/10.1002/ece3.4280.","productDescription":"15 p.","startPage":"8433","endPage":"8447","ipdsId":"IP-091093","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468567,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4280","text":"Publisher Index Page"},{"id":372171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California 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\"}}]}","volume":"8","issue":"16","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Chinn, Sarah M.","contributorId":222316,"corporation":false,"usgs":false,"family":"Chinn","given":"Sarah M.","affiliations":[{"id":40519,"text":"Department of Biology, Sonoma State University","active":true,"usgs":false}],"preferred":false,"id":781859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monson, Daniel 0000-0002-4593-5673 dmonson@usgs.gov","orcid":"https://orcid.org/0000-0002-4593-5673","contributorId":196670,"corporation":false,"usgs":true,"family":"Monson","given":"Daniel","email":"dmonson@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":781858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tinker, M. Tim 0000-0002-3314-839X","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":214291,"corporation":false,"usgs":true,"family":"Tinker","given":"M. Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":781862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Staedler, Michelle M. 0000-0002-1101-6580","orcid":"https://orcid.org/0000-0002-1101-6580","contributorId":222317,"corporation":false,"usgs":true,"family":"Staedler","given":"Michelle","email":"","middleInitial":"M.","affiliations":[{"id":6953,"text":"Monterey Bay Aquarium","active":true,"usgs":false}],"preferred":true,"id":781860,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crocker, Daniel E.","contributorId":222318,"corporation":false,"usgs":false,"family":"Crocker","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":40519,"text":"Department of Biology, Sonoma State University","active":true,"usgs":false}],"preferred":false,"id":781861,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217854,"text":"70217854 - 2018 - Prevalence of seismic rate anomalies preceding volcanic eruptions in Alaska","interactions":[],"lastModifiedDate":"2021-02-05T20:45:27.73204","indexId":"70217854","displayToPublicDate":"2018-07-20T14:40:16","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Prevalence of seismic rate anomalies preceding volcanic eruptions in Alaska","docAbstract":"Seismic rate increases often precede eruptions at volcanoes worldwide. However, many eruptions occur without such precursors. Additionally, identifying seismic rate increases near volcanoes with high levels of background seismicity is non-trivial and many periods of elevated seismicity occur without ensuing eruptions, limiting their usefulness for forecasting in some cases. Although these issues are commonly known, efforts to quantify them are limited. In this study, we consistently apply a common statistical tool, the β-statistic, to seismically monitored eruptions in Alaska of various styles to determine the overall prevalence of seismic rate anomalies immediately preceding eruptions. We find that 6 out of 20 (30%) eruptions have statistically significant precursory seismic rate increases. Of these 6 eruptions, 3 of them occur at volcanoes with relatively felsic compositions, repose periods >15 years, and VEI ≥ 3. Overall, our results confirm that seismic rate increases are common prior to larger eruptions at long dormant, “closed-system” volcanoes, but uncommon preceding smaller eruptions at more frequently active, “open-system” volcanoes with more mafic magmas. We also explore the rate of other anomalies not precursory to eruptions and investigate their origins. Some of these non-eruptive anomalies can be explained by aftershocks of regional seismic events, magmatic activity that did not lead to eruption, or unrest at other nearby volcanoes. Some open-system volcanoes have high non-eruptive anomaly rates and low pre-eruptive anomaly rates and are thus not amenable to forecasting based on earthquake catalogs. In this study, we find that 31% of anomalies lead to eruption. With continued calibration at more volcanoes, the β-statistic that we apply may be used more broadly to analyze future periods of seismic unrest at other volcanoes, properly placing such episodes into the context of the long-term background rate. These results may be useful for informing future eruption forecasts around the world, and the statistical tool may aid volcano observatories in identifying future seismic rate anomalies under changing network conditions.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2018.00100","usgsCitation":"Pesicek, J.D., Wellik, J., Prejean, S., and Ogburn, S.E., 2018, Prevalence of seismic rate anomalies preceding volcanic eruptions in Alaska: Frontiers in Earth Science, v. 6, 100, 15 p., https://doi.org/10.3389/feart.2018.00100.","productDescription":"100, 15 p.","ipdsId":"IP-096007","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":460875,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2018.00100","text":"Publisher Index Page"},{"id":383077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -152.2265625,\n 60.261617082844616\n ],\n [\n -150.29296875,\n 61.52269494598361\n ],\n [\n -148.5791015625,\n 65.164578884019\n ],\n [\n -166.1572265625,\n 66.10716955858042\n ],\n [\n -172.3095703125,\n 63.68524808030715\n ],\n [\n -173.759765625,\n 60.326947742998414\n ],\n [\n -175.166015625,\n 51.699799849741936\n ],\n [\n -165.8056640625,\n 52.9883372533954\n ],\n [\n -153.4130859375,\n 58.37867853932655\n ],\n [\n -152.138671875,\n 60.174306261926034\n ],\n [\n -152.2265625,\n 60.261617082844616\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2018-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Pesicek, Jeremy D. 0000-0001-7964-5845","orcid":"https://orcid.org/0000-0001-7964-5845","contributorId":202042,"corporation":false,"usgs":true,"family":"Pesicek","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":809909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wellik, John 0000-0002-8099-5794","orcid":"https://orcid.org/0000-0002-8099-5794","contributorId":204753,"corporation":false,"usgs":true,"family":"Wellik","given":"John","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":809910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prejean, Stephanie G. 0000-0003-0510-1989 sprejean@usgs.gov","orcid":"https://orcid.org/0000-0003-0510-1989","contributorId":172404,"corporation":false,"usgs":true,"family":"Prejean","given":"Stephanie","email":"sprejean@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":809911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogburn, Sarah E. 0000-0002-4734-2118","orcid":"https://orcid.org/0000-0002-4734-2118","contributorId":204751,"corporation":false,"usgs":true,"family":"Ogburn","given":"Sarah","email":"","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":809912,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70226824,"text":"70226824 - 2018 - Linking the Ukinrek 1977 maar-eruption observations to the tephra deposits: New insights into maar depositional processes","interactions":[],"lastModifiedDate":"2021-12-14T12:44:30.908574","indexId":"70226824","displayToPublicDate":"2018-07-19T06:39:09","publicationYear":"2018","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":"Linking the Ukinrek 1977 maar-eruption observations to the tephra deposits: New insights into maar depositional processes","docAbstract":"The Ukinrek Maars erupted 30 March to 9 April 1977, forming two maars, a line of small pit craters and a tephra blanket extending to ~2 km from the vents. We combine photographic and written observations with stratigraphic analysis to reconstruct the eruption. The eruption began with very low (a few meters high) fountaining from small craters above an inferred east-west-trending dike, creating local scoria/spatter agglomerate ramparts with a sandy matrix. The eruption very quickly (in minutes to hours) centered on the West Maar. The West Maar eruption lasted 1–2 days, starting and ending with phreatomagmatic explosions with weak phreato-Strombolian activity in between. Initial explosions formed a 30-m-wide crater, enlarged by crater-wall collapse, and columns as high as 6500 m. Phreato-Strombolian activity produced ~72% of the erupted volume, including a small spatter cone and a scoria blanket around the vent. A final explosion series emplaced a lithic-rich breccia as ballistic blocks, possibly as the northern half of the final crater collapsed into the southern vent area. The East Maar formed over the last nine days of the eruption and represents ~93% of the total volume (4.6 × 106 m3) of the Ukinrek eruption. Initial explosions were probably shallower than 10–20 m but most of the eruption occurred from explosions at 50–60 m below the pre-eruptive surface, with evidence of explosions to 90 m depth only at the very end of the eruption. The East Maar eruption mostly produced columns of lapilli, ash, and steam and the deposits are mostly fallout. Winds blew fallout mostly to the north for the first 5–6 days and to the south for the last three days of the eruption. Wind-directed pyroclastic density currents collapsed from the column, producing fines-rich layers within the coarser fallout. Sporadic explosions produced weak density currents in the first few days and lithic-and juvenile-block-rich breccias in the last few days of the eruption. We interpret that collapse of the crater walls made a slurry that in part provided the water for phreatomagmatic interaction. Explosions came from depths <90 m below the pre-eruptive surface except for a few explosions at the end of the eruption, with most occurring at <70 m depth. The East Maar crater was open to 40–60 m depth throughout most of the eruption, so the explosions were rarely, if ever, deeper than 30 m below the crater floor. Thus, we infer there is no classic, well-formed diatreme structure below the maar. Collapse of the East Maar crater walls provided a supply of water-saturated sediment for much of the phreatomagmatic activity, which came from two vents that did not migrate much, if at all, during the eruption. The Ukinrek Maars deposits were nearly entirely emplaced by fallout, rather than density currents, from explosions and low columns.
The 2016‐2017 eruption of Bogoslof volcano, a submarine stratovolcano in the Bering Sea, produced 70 discrete explosive eruptions over 8 months. With no local monitoring data, activity was seismically recorded on nearby islands 50‐100 km away, limiting the detection and resolution of seismic observations. We construct a matched filter catalog of 3199 events from 49 earthquake families, many of which occurred with hydroacousticT waves of varying strength. We then use a 2D finite difference model to show that hydroacoustic amplitudes should decrease with increased source depth beneath the edifice and leverage each family's seismically recorded T wave amplitude as a proxy for source depth, which we compare to regional infrasound data. This unique combination of using P and S waves to detect events, T waves as a proxy for depth, and infrasound for precise timing of emissions allows us to interpret the dynamics and evolution of the Bogoslof eruption.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018GL078457","usgsCitation":"Wech, A., Tepp, G., Lyons, J.J., and Haney, M.M., 2018, Using earthquakes, T waves, and infrasound to investigate the eruption of Bogoslof Volcano, Alaska: Geophysical Research Letters, v. 45, no. 14, p. 6918-6925, https://doi.org/10.1029/2018GL078457.","productDescription":"8 p.","startPage":"6918","endPage":"6925","ipdsId":"IP-097523","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":355679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.06129455566406,\n 53.92021282471509\n ],\n [\n -168.01769256591797,\n 53.92021282471509\n ],\n [\n -168.01769256591797,\n 53.95335826795407\n ],\n [\n -168.06129455566406,\n 53.95335826795407\n ],\n [\n -168.06129455566406,\n 53.92021282471509\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"14","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-25","publicationStatus":"PW","scienceBaseUri":"5b6fc415e4b0f5d57878e9d1","contributors":{"authors":[{"text":"Wech, Aaron 0000-0003-4983-1991","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":202561,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":740022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tepp, Gabrielle 0000-0001-5388-5138","orcid":"https://orcid.org/0000-0001-5388-5138","contributorId":206305,"corporation":false,"usgs":true,"family":"Tepp","given":"Gabrielle","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":740023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":740024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":740025,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199208,"text":"70199208 - 2018 - Defining the risk landscape in the context of pathogen pollution: Toxoplasma gondii in sea otters along the Pacific Rim","interactions":[],"lastModifiedDate":"2018-09-10T13:50:22","indexId":"70199208","displayToPublicDate":"2018-07-04T13:50:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3908,"text":"Royal Society Open Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Defining the risk landscape in the context of pathogen pollution: Toxoplasma gondii in sea otters along the Pacific Rim","title":"Defining the risk landscape in the context of pathogen pollution: Toxoplasma gondii in sea otters along the Pacific Rim","docAbstract":"Pathogens entering the marine environment as pollutants exhibit a spatial signature driven by their transport mechanisms. The sea otter (Enhydra lutris), a marine animal which lives much of its life within sight of land, presents a unique opportunity to understand land–sea pathogen transmission. Using a dataset on Toxoplasma gondii prevalence across sea otter range from Alaska to California, we found that the dominant drivers of infection risk vary depending upon the spatial scale of analysis. At the population level, regions with high T. gondii prevalence had higher human population density and a greater proportion of human-dominated land uses, suggesting a strong role for population density of the felid definitive host of this parasite. This relationship persisted when a subset of data were analysed at the individual level: large-scale patterns in sea otter T. gondii infection prevalence were largely explained by individual exposure to areas of high human housing unit density, and other landscape features associated with anthropogenic land use, such as impervious surfaces and cropping land. These results contrast with the small-scale, within-region analysis, in which age, sex and prey choice accounted for most of the variation in infection risk, and terrestrial environmental features provided little variation to help in explaining observed patterns. These results underscore the importance of spatial scale in study design when quantifying both individual-level risk factors and landscape-scale variation in infection risk.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rsos.171178","usgsCitation":"Burgess, T.L., Tinker, M.T., Miller, M.A., Bodkin, J.L., Murray, M.J., Saarinen, J.A., Nichol, L.M., Larson, S.E., Conrad, P.A., and Johnson, C., 2018, Defining the risk landscape in the context of pathogen pollution: Toxoplasma gondii in sea otters along the Pacific Rim: Royal Society Open Science, v. 5, Article 171178; 11 p., https://doi.org/10.1098/rsos.171178.","productDescription":"Article 171178; 11 p.","ipdsId":"IP-091756","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468604,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsos.171178","text":"Publisher Index Page"},{"id":357204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.618408203125,\n 34.15272698011818\n ],\n [\n -119.24560546875001,\n 34.15272698011818\n ],\n [\n -119.24560546875001,\n 37.69251435532741\n ],\n [\n -122.618408203125,\n 37.69251435532741\n ],\n [\n -122.618408203125,\n 34.15272698011818\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-04","publicationStatus":"PW","scienceBaseUri":"5b98a2a2e4b0702d0e842f94","contributors":{"authors":[{"text":"Burgess, Tristan L.","contributorId":207772,"corporation":false,"usgs":false,"family":"Burgess","given":"Tristan","email":"","middleInitial":"L.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":744678,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":744677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Melissa A.","contributorId":57701,"corporation":false,"usgs":false,"family":"Miller","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":39007,"text":"CA Dept of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":744679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bodkin, James L. 0000-0003-1641-4438 jbodkin@usgs.gov","orcid":"https://orcid.org/0000-0003-1641-4438","contributorId":748,"corporation":false,"usgs":true,"family":"Bodkin","given":"James","email":"jbodkin@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":744680,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murray, Michael J.","contributorId":206852,"corporation":false,"usgs":false,"family":"Murray","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":37418,"text":"Monterey Bay Aquarium, Monterey, CA","active":true,"usgs":false}],"preferred":false,"id":744681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Saarinen, Justin A.","contributorId":207774,"corporation":false,"usgs":false,"family":"Saarinen","given":"Justin","email":"","middleInitial":"A.","affiliations":[{"id":35150,"text":"New College of Florida","active":true,"usgs":false}],"preferred":false,"id":744682,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nichol, Linda M.","contributorId":207775,"corporation":false,"usgs":false,"family":"Nichol","given":"Linda","email":"","middleInitial":"M.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":744683,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Larson, Shawn E.","contributorId":149287,"corporation":false,"usgs":false,"family":"Larson","given":"Shawn","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":744684,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Conrad, Patricia A.","contributorId":181937,"corporation":false,"usgs":false,"family":"Conrad","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":744685,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Johnson, Christine K.","contributorId":23771,"corporation":false,"usgs":false,"family":"Johnson","given":"Christine K.","affiliations":[],"preferred":false,"id":744686,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70259745,"text":"70259745 - 2018 - Alaska Volcano Observatory alert and forecasting timeliness: 1989–2017","interactions":[],"lastModifiedDate":"2024-10-23T11:37:30.603843","indexId":"70259745","displayToPublicDate":"2018-07-02T06:34:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17169,"text":"Frontiers in Earth Science - Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Alaska Volcano Observatory alert and forecasting timeliness: 1989–2017","docAbstract":"The Alaska Volcano Observatory (AVO) monitors volcanoes in Alaska and issues notifications and warnings of volcanic unrest and eruption. We evaluate the timeliness and accuracy of eruption forecasts for 53 eruptions at 20 volcanoes, beginning with Mount Redoubt's 1989–1990 eruption. Successful forecasts are defined as those where AVO issued a formal warning before eruption onset. These warning notifications are now part of AVO's Aviation Color Code and Volcanic Alert Level. This analysis considers only the start of an eruption, although many eruptions have multiple phases of activity. For the 21 eruptions at volcanoes with functioning local seismic networks, AVO has high forecasting success at volcanoes with: >15 years repose intervals and magmatic eruptions (4 out of 4, 100%); or larger eruptions (Volcanic Explosivity Index (VEI) 3 or greater; 6 out of 10, 60%). Therefore, AVO successfully forecast all four monitored, longer-repose period, VEI 3+ eruptions: Redoubt 1989–1990 and 2009, Spurr 1992, and Augustine 2005–2006. For volcanoes with functioning seismic monitoring networks, success rates are lower for: volcanoes with shorter repose periods (3 out of 16, 19%); more mafic compositions (3 out of 18, 17%); or smaller eruption size (VEI 2 or less, 1 out of 11, 9%). These eruptions (Okmok, Pavlof, Veniaminof, and Shishaldin) often lack detectable precursory signals. For 32 eruptions at volcanoes without functioning local seismic networks, the forecasting success rate is much lower (2, 6%; Kasatochi 2008 and Shishaldin 2014). For remote volcanoes where the main hazard is to aviation, rapid detection is a goal in the absence of in situ monitoring. Eruption detection has improved in recent years, shown by a decrease in the time between eruption onset and notification. Even limited seismic monitoring can detect precursory activity at volcanoes with certain characteristics (intermediate composition, longer repose times, larger eruptions), but difficulty persists in detecting subtle precursory activity at frequently active volcanoes with more mafic compositions. This suggests that volcano-specific characteristics should be considered when designing monitoring programs and evaluating forecasting success. More proximally-located sensors and data types are likely needed to forecast eruptive activity at frequently-active, more mafic volcanoes that generally produce smaller eruptions.
The tufted puffin (Fratercula cirrhata) is a generalist seabird that breeds throughout the North Pacific and eats more than 75 different prey species. Using puffins as samplers, we characterized the geographic variability in pelagic food webs across the subarctic North Pacific from the composition of ~10,000 tufted puffin meals (~56,000 prey items) collected at 35 colonies in the Gulf of Alaska (GoA) and Aleutian Archipelago. Cluster analysis of diet species composition suggested three distinct forage fish communities: (i) in the northern GoA, multiple age‐classes of coastal and shelf residents such as capelin, sand lance and herring dominated the food web, (ii) in the western GoA to eastern Aleutians, the shelf community was dominated by transient age‐0 walleye pollock, and (iii) in the western Aleutians, shelf‐edge and mesopelagic forage species such as squid, lanternfish, and Atka mackerel were prevalent. Geographic patterns of abundance of capelin and sand lance in tufted puffin diets were corroborated by independent research fisheries and diets of piscivorous fish, indicating that puffin diets reflect the local abundance of forage species, not just selection of favored species. Generalized additive models showed that habitat characteristics predict, in a non‐linear fashion, forage species distribution and abundance across two large marine ecosystems. We conclude that major biogeographic patterns in forage fish distribution follow gradients in key habitat features, and puffin diets reflect those patterns.
","language":"English","publisher":"Wiley","doi":"10.1111/fog.12258","usgsCitation":"Piatt, J.F., Arimitsu, M.L., Sydeman, W.J., Thompson, S.A., Renner, H., Zador, S., Douglas, D., Hatch, S., Kettle, A.B., and Williams, J.C., 2018, Biogeography of pelagic food webs in the North Pacific: Fisheries Oceanography, v. 27, no. 4, p. 366-380, https://doi.org/10.1111/fog.12258.","productDescription":"15 p.","startPage":"366","endPage":"380","ipdsId":"IP-067595","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":468614,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/fog.12258","text":"External Repository"},{"id":358187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-12","publicationStatus":"PW","scienceBaseUri":"5bc02fd7e4b0fc368eb5398f","contributors":{"authors":[{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"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":747424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":747425,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sydeman, William J.","contributorId":208489,"corporation":false,"usgs":false,"family":"Sydeman","given":"William","email":"","middleInitial":"J.","affiliations":[{"id":35859,"text":"Farallon Institute","active":true,"usgs":false}],"preferred":false,"id":747426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Sarah Ann","contributorId":198394,"corporation":false,"usgs":false,"family":"Thompson","given":"Sarah","email":"","middleInitial":"Ann","affiliations":[],"preferred":false,"id":747427,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Renner, Heather","contributorId":200807,"corporation":false,"usgs":false,"family":"Renner","given":"Heather","affiliations":[],"preferred":false,"id":747428,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zador, Stephani","contributorId":60992,"corporation":false,"usgs":false,"family":"Zador","given":"Stephani","affiliations":[],"preferred":false,"id":747429,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"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":747430,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hatch, Scott A.","contributorId":201044,"corporation":false,"usgs":false,"family":"Hatch","given":"Scott A.","affiliations":[],"preferred":false,"id":747431,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kettle, Arthur B.","contributorId":98064,"corporation":false,"usgs":false,"family":"Kettle","given":"Arthur","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":747432,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Williams, Jeffrey C.","contributorId":126882,"corporation":false,"usgs":false,"family":"Williams","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":747433,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70198676,"text":"70198676 - 2018 - Comparative nest survival of three sympatric loon species breeding in the Arctic","interactions":[],"lastModifiedDate":"2018-08-15T13:53:17","indexId":"70198676","displayToPublicDate":"2018-07-01T13:53:12","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Comparative nest survival of three sympatric loon species breeding in the Arctic","docAbstract":"Identifying factors influencing nest survival among sympatric species is important for understanding and managing sources of variation in population dynamics of individual species. Three species of loons nest sympatrically in northern Alaska and differ in body size, life history characteristics, and population trends. We tested the effects of competition, nest site selection, and water level variations on nest survival of Pacific Gavia pacifica, yellow‐billed G. adamsii, and red‐throated loons G. stellata on the Arctic Coastal Plain in Alaska. Although overall nest survival rates did not differ between species, the factors influencing nest survival varied. Nest site selection influenced nest survival for Pacific and yellow‐billed loons, with both species having high nest survival when nesting on islands and peninsulas, likely due to a reduction in access by terrestrial predators. However, on mainland shorelines, Pacific loons had lower nest survival than yellow‐billed loons, and used a higher proportion of vegetation mats for nest sites suggesting that their smaller body size makes them less adept at nest defense. Nest site selection did not influence nest survival of red‐throated loons corresponding to our result of no nest site preferences by this species. Initiation date had a strong influence on nest survival for Pacific and yellow‐billed loons with nests laid earlier having higher survival. Pacific and yellow‐billed loon nests were susceptible to flooding due to precipitation, which contrasted with red‐throated loons that nest on smaller lakes with lower water level variations. Competition did not affect nest survival for any of the species likely due to most territorial encounters occurring prior to incubation. The only influence we found on red‐throated loon nest survival was differences among years. Our results indicate that loons chose nest sites based on predation risk and that factors influencing breeding success of closely related species may differ under similar breeding conditions.
","language":"English","publisher":"Wiley","doi":"10.1111/jav.01671","usgsCitation":"Uher-Koch, B.D., Koch, J.C., Wright, K.G., and Schmutz, J.A., 2018, Comparative nest survival of three sympatric loon species breeding in the Arctic: Journal of Avian Biology, v. 49, no. 7, p. 1-15, https://doi.org/10.1111/jav.01671.","productDescription":"e01671; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-090934","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":499979,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/5ae4f5eb63564114b5a16aec9f3f4b8a","text":"External Repository"},{"id":437834,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74F1Q0D","text":"USGS data release","linkHelpText":"Pacific (Gavia pacifica), Yellow-billed (G. adamsii), and Red-throated Loon (G. stellata) Nest Monitoring Data; National Petroleum Reserve-Alaska, 2011-2014"},{"id":356517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157,\n 70.33\n ],\n [\n -153,\n 70.33\n ],\n [\n -153,\n 71.33\n ],\n [\n -157,\n 71.33\n ],\n [\n -157,\n 70.33\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-18","publicationStatus":"PW","scienceBaseUri":"5b98a2a2e4b0702d0e842f9c","contributors":{"authors":[{"text":"Uher-Koch, Brian D. 0000-0002-1885-0260 buher-koch@usgs.gov","orcid":"https://orcid.org/0000-0002-1885-0260","contributorId":5117,"corporation":false,"usgs":true,"family":"Uher-Koch","given":"Brian","email":"buher-koch@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":742522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":742523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wright, Kenneth G.","contributorId":207044,"corporation":false,"usgs":false,"family":"Wright","given":"Kenneth","email":"","middleInitial":"G.","affiliations":[{"id":37436,"text":"Biodiversity Research Institute","active":true,"usgs":false}],"preferred":false,"id":742524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","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":742525,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200841,"text":"70200841 - 2018 - A revised Triassic stratigraphic framework for the Arctic Alaska Basin","interactions":[],"lastModifiedDate":"2018-11-07T09:39:08","indexId":"70200841","displayToPublicDate":"2018-07-01T09:04:26","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"A revised Triassic stratigraphic framework for the Arctic Alaska Basin","docAbstract":"The Triassic Shublik Formation and the Triassic–Jurassic Otuk Formation are partially age-equivalent lithostratigraphic units that were deposited in the Arctic Alaska Basin (AAB). The Shublik Formation represents proximal deposition within the basin, with episodic siliciclastic input, whereas the Otuk Formation was deposited in the distal part of the basin, with significant intervals of mudstone and chert. Both the Shublik and Otuk Formations have significant intervals of organic-rich mudstone, and the Shublik is a major source rock for northern Alaska hydrocarbon accumulations such as Prudhoe Bay. The revised stratigraphic framework presented herein, based on the integration of lithostratigraphy and biostratigraphy, correlates intervals within these two formations, as well as the Ivishak Formation and the Karen Creek and Sag River Sandstones (which underlie and overlie the Shublik). This stratigraphic framework provides a basis for comparison of proximal and distal parts of the AAB through the Triassic, thus allowing for a more robust understanding of the spatial and temporal variability of lithology and organic richness within this basin. Five transgressive–regressive sequences are defined in the Shublik, based on lithostratigraphy and better age constraints provided by the revised stratigraphic framework. These sequences are age-correlative and recognized in other Arctic basins, implying that they have regional, and perhaps global, significance.","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/0726171616517250","usgsCitation":"Whidden, K.J., Dumoulin, J.A., and Rouse, W.A., 2018, A revised Triassic stratigraphic framework for the Arctic Alaska Basin: AAPG Bulletin, v. 102, no. 7, p. 1171-1212, https://doi.org/10.1306/0726171616517250.","productDescription":"42 p.","startPage":"1171","endPage":"1212","ipdsId":"IP-079096","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":359268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":" Arctic Alaska Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.48632812499997,\n 65.58572002329473\n ],\n [\n -135.615234375,\n 65.58572002329473\n ],\n [\n -135.615234375,\n 71.49703690095419\n ],\n [\n -168.48632812499997,\n 71.49703690095419\n ],\n [\n -168.48632812499997,\n 65.58572002329473\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5be40823e4b0b3fc5cf7cc0a","contributors":{"authors":[{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":750884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":750885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rouse, William A. 0000-0002-0790-370X wrouse@usgs.gov","orcid":"https://orcid.org/0000-0002-0790-370X","contributorId":4172,"corporation":false,"usgs":true,"family":"Rouse","given":"William","email":"wrouse@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":750886,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197961,"text":"70197961 - 2018 - Influence of landscape structure, topography, and forest type on spatial variation in historical fire regimes, central Oregon, USA","interactions":[],"lastModifiedDate":"2018-07-13T14:22:04","indexId":"70197961","displayToPublicDate":"2018-06-29T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Influence of landscape structure, topography, and forest type on spatial variation in historical fire regimes, central Oregon, USA","docAbstract":"Context In the interior Northwest, debate over restoring mixed-conifer forests after a century of fire exclusion is hampered by poor understanding of the pattern and causes of spatial variation in historical fire regimes. \n\nObjectives To identify the roles of topography, landscape structure, and forest type in driving spatial variation in historical fire regimes in mixed-conifer forests of central Oregon.\n\nMethods We used tree rings to reconstruct multicentury fire and forest histories at 105 plots over 10,393 ha. We classified fire regimes into four types and assessed whether they varied with topography, the location of fuel-limited pumice basins that inhibit fire spread, and an updated classification of forest type. \n\nResults We identified four fire-regime types and six forest types. Although surface fires were frequent and often extensive, severe fires were rare in all four types. Fire regimes varied with some aspects of topography (elevation), but not others (slope or aspect) and with the distribution of pumice basins. Fire regimes did not strictly co-vary with mixed-conifer forest types. \n\nConclusions Our work reveals the persistent influence of landscape structure on spatial variation in historical fire regimes and can help inform discussions about appropriate restoration of fire-excluded forests in the interior Northwest. Where the goal is to restore historical fire regimes at landscape scales, managers may want to consider the influence of topoedaphic and vegetation patch types that could affect fire spread and ignition frequency.","language":"English","publisher":"Springer","doi":"10.1007/s10980-018-0656-6","usgsCitation":"Merschel, A., Heyerdahl, E.K., Spies, T.A., and Loehman, R.A., 2018, Influence of landscape structure, topography, and forest type on spatial variation in historical fire regimes, central Oregon, USA: Landscape Ecology, v. 33, no. 7, p. 1195-1209, https://doi.org/10.1007/s10980-018-0656-6.","productDescription":"15 p.","startPage":"1195","endPage":"1209","ipdsId":"IP-096960","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":355435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-07","publicationStatus":"PW","scienceBaseUri":"5b46e549e4b060350a15d0a3","contributors":{"authors":[{"text":"Merschel, Andrew","contributorId":206075,"corporation":false,"usgs":false,"family":"Merschel","given":"Andrew","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":739338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heyerdahl, Emily K.","contributorId":204192,"corporation":false,"usgs":false,"family":"Heyerdahl","given":"Emily","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":739339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spies, Thomas A.","contributorId":169892,"corporation":false,"usgs":false,"family":"Spies","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":18944,"text":"Pacific Northwest Research Station, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":739340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":739337,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197953,"text":"70197953 - 2018 - Sulfur isotopes of host strata for Howards Pass (Yukon–Northwest Territories) Zn-Pb deposits implicate anaerobic oxidation of methane, not basin stagnation","interactions":[],"lastModifiedDate":"2018-06-28T12:00:17","indexId":"70197953","displayToPublicDate":"2018-06-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Sulfur isotopes of host strata for Howards Pass (Yukon–Northwest Territories) Zn-Pb deposits implicate anaerobic oxidation of methane, not basin stagnation","docAbstract":"A new sulfur isotope stratigraphic profile has been developed for Ordovician-Silurian mudstones that host the Howards Pass Zn-Pb deposits (Canada) in an attempt to reconcile the traditional model of a stagnant euxinic basin setting with new contradictory findings. Our analyses of pyrite confirm the up-section 34S enrichment reported previously, but additional observations show parallel depletion of carbonate 13C, an increase in organic carbon weight percent, and a change in pyrite morphology. Taken together, the data suggest that the 34S enrichment reflects a transition in the mechanism of pyrite formation during diagenesis, not isotopic evolution of a stagnant water mass. Low in the stratigraphic section, pyrite formed mainly in the sulfate reduction zone in association with organic matter–driven bacterial sulfate reduction. In contrast, starting just below the Zn-Pb mineralized horizon, pyrite formed increasingly within the sulfate-methane transition zone in association with anaerobic oxidation of methane. Our new insights on diagenesis have implications for (1) the setting of Zn-Pb ore formation, (2) the reliability of redox proxies involving metals, and (3) the source of ore sulfur for Howards Pass, and potentially for other stratiform Zn-Pb deposits contained in carbonaceous strata.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G40274.1","usgsCitation":"Johnson, C.A., Slack, J.F., Dumoulin, J.A., Kelley, K.D., and Falck, H., 2018, Sulfur isotopes of host strata for Howards Pass (Yukon–Northwest Territories) Zn-Pb deposits implicate anaerobic oxidation of methane, not basin stagnation: Geology, v. 46, no. 7, p. 619-622, https://doi.org/10.1130/G40274.1.","productDescription":"4 p.","startPage":"619","endPage":"622","ipdsId":"IP-092844","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":437841,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WS3IS0","text":"USGS data release","linkHelpText":"Isotope and chemical data for: Sulfur isotopes of host strata for Howards Pass (Yukon-Northwest Territories) Zn-Pb deposits implicate anaerobic oxidation of methane not basin stagnation"},{"id":437840,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WS3IS0","text":"USGS data release","linkHelpText":"Isotope and chemical data for: Sulfur isotopes of host strata for Howards Pass (Yukon-Northwest Territories) Zn-Pb deposits implicate anaerobic oxidation of methane not basin stagnation"},{"id":355408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Northwest Territories, Yukon","otherGeospatial":" Howards Pass","volume":"46","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-07","publicationStatus":"PW","scienceBaseUri":"5b46e54be4b060350a15d0ab","contributors":{"authors":[{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":739307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":739308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":739309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelley, Karen Duttweiler 0000-0002-3232-5809 kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":192758,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"Duttweiler","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":739310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Falck, Hendrik","contributorId":167705,"corporation":false,"usgs":false,"family":"Falck","given":"Hendrik","email":"","affiliations":[{"id":24811,"text":"NWT Geoscience Office, Yellowknife, Canada","active":true,"usgs":false}],"preferred":false,"id":739311,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}