We compared migration movements and chronology between Northern Pintails (Anas acuta) marked with dorsally mounted satellite transmitters and pintails marked only with tarsus rings. During weekly intervals of spring and autumn migration between their wintering area in Japan and nesting areas in Russia, the mean distance that ringed pintails had migrated was up to 1000 km farther than the mean distance radiomarked pintails migrated. Radiomarked pintails were detected at spring migration sites on average 9.9 days (90 % CI 8.0, 11.8) later than ringed pintails that were recovered within 50 km. Although ringed and radiomarked pintails departed from Japan on similar dates, the disparity in detection of radiomarked versus ringed pintails at shared sites increased 7.7 days (90 % CI 5.2, 10.2) for each 1000 km increase in distance from Japan. Thus, pintails marked with satellite transmitters arrived at nesting areas that were 2500 km from Japan on average 19 days later than ringed birds. Radiomarked pintails were detected at autumn migration stopovers on average 13.1 days (90 % CI 9.8, 16.4) later than ringed birds that were recovered within 50 km. We hypothesize that dorsal attachment of 12–20 g satellite transmitters to Northern Pintails increased the energetic cost of flight, which resulted in more rapid depletion of energetic reserves and shortened the distance pintails could fly without refueling. Radiomarked pintails may have used more stopovers or spent longer periods at stopovers. causing their migration schedule to diverge from ringed pintails. We urge further evaluation of the effects of dorsally mounted transmitters on migration chronology of waterfowl.
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paramount to devising successful management plans for wildlife species. For example, birds time migration in response, in part, to local and broadscale climate fluctuations to initiate breeding upon arrival to nesting territories, and prolonged inclement weather early in the breeding season can inhibit egg-laying and reduce productivity. Also, density-dependent regulation occurs in raptor populations, as territory size is related to resource availability. Arctic Peregrine Falcons (Falco peregrinus tundrius; hereafter Arctic peregrine) have a limited and northern breeding distribution, including the Colville River Special Area (CRSA) in the National Petroleum Reserve–Alaska, USA. We quantified influences of climate, topography, nest productivity, prey habitat, density dependence, and interspecific competition affecting Arctic peregrines in the CRSA by applying the Dail-Madsen model to estimate abundance and vital rates of adults on nesting cliffs from 1981 through 2002. Arctic peregrine abundance increased throughout the 1980s, which spanned the population's recovery from DDT-induced reproductive failure, until exhibiting a stationary trend in the 1990s. Apparent survival rate (i.e., emigration; death) was negatively correlated with the number of adult Arctic peregrines on the cliff the previous year, suggesting effects of density-dependent population regulation. Apparent survival and arrival rates (i.e., immigration; recruitment) were higher during years with earlier snowmelt and milder winters, and apparent survival was positively correlated with nesting season maximum daily temperature. Arrival rate was positively correlated with average Arctic peregrine productivity along a cliff segment from the previous year and initial abundance was positively correlated with cliff height. Higher cliffs with documented higher productivity (presumably indicative of higher-quality habitat), are a priority for continued protection from potential nearby development and disturbance to minimize population-level impacts. Climate change may affect Arctic peregrines in multiple ways, including through access to more snow-free nest sites and a lengthened breeding season that may increase likelihood of nest success. Our work provides insight into factors affecting a population during and after recovery, and demonstrates how the Dail-Madsen model can be used for any unmarked population with multiple years of abundance data collected through repeated surveys.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/14-1591.1","usgsCitation":"Bruggeman, J.E., Swem, T., Andersen, D., Kennedy, P.L., and Nigro, D.A., 2015, Dynamics of a recovering Arctic bird population: the importance of climate, density dependence, and site quality: Ecological Applications, v. 25, no. 7, p. 1932-1943, https://doi.org/10.1890/14-1591.1.","productDescription":"12 p.","startPage":"1932","endPage":"1943","ipdsId":"IP-055304","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340549,"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 -158.5107421875,\n 68.73638345287264\n ],\n [\n -149.94140625,\n 68.73638345287264\n ],\n [\n -149.94140625,\n 70.56149224990756\n ],\n [\n -158.5107421875,\n 70.56149224990756\n ],\n [\n -158.5107421875,\n 68.73638345287264\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59030327e4b0e862d230f735","contributors":{"authors":[{"text":"Bruggeman, Jason E.","contributorId":18983,"corporation":false,"usgs":false,"family":"Bruggeman","given":"Jason","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":693305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swem, Ted","contributorId":64463,"corporation":false,"usgs":true,"family":"Swem","given":"Ted","affiliations":[],"preferred":false,"id":693306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":2168,"corporation":false,"usgs":true,"family":"Andersen","given":"David E.","email":"dea@usgs.gov","affiliations":[{"id":34539,"text":"Minnesota Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693219,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kennedy, Patricia L.","contributorId":172826,"corporation":false,"usgs":false,"family":"Kennedy","given":"Patricia","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":693307,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nigro, Debora A.","contributorId":10628,"corporation":false,"usgs":false,"family":"Nigro","given":"Debora","email":"","middleInitial":"A.","affiliations":[{"id":12934,"text":"Bureau of Land Management, Arctic Field Office","active":true,"usgs":false}],"preferred":false,"id":693308,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70169289,"text":"70169289 - 2015 - Estimating demographic parameters using a combination of known-fate and open N-mixture models","interactions":[],"lastModifiedDate":"2016-03-24T09:05:51","indexId":"70169289","displayToPublicDate":"2015-10-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating demographic parameters using a combination of known-fate and open N-mixture models","docAbstract":"Accurate estimates of demographic parameters are required to infer appropriate ecological relationships and inform management actions. Known-fate data from marked individuals are commonly used to estimate survival rates, whereas N-mixture models use count data from unmarked individuals to estimate multiple demographic parameters. However, a joint approach combining the strengths of both analytical tools has not been developed. Here we develop an integrated model combining known-fate and open N-mixture models, allowing the estimation of detection probability, recruitment, and the joint estimation of survival. We demonstrate our approach through both simulations and an applied example using four years of known-fate and pack count data for wolves (Canis lupus). Simulation results indicated that the integrated model reliably recovered parameters with no evidence of bias, and survival estimates were more precise under the joint model. Results from the applied example indicated that the marked sample of wolves was biased toward individuals with higher apparent survival rates than the unmarked pack mates, suggesting that joint estimates may be more representative of the overall population. Our integrated model is a practical approach for reducing bias while increasing precision and the amount of information gained from mark–resight data sets. We provide implementations in both the BUGS language and an R package.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/15-0385.1","usgsCitation":"Schmidt, J., Johnson, D.S., Lindberg, M.S., and Adams, L., 2015, Estimating demographic parameters using a combination of known-fate and open N-mixture models: Ecology, v. 96, no. 10, p. 2583-2589, https://doi.org/10.1890/15-0385.1.","productDescription":"7 p.","startPage":"2583","endPage":"2589","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063639","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":471741,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1890/15-0385.1","text":"External Repository"},{"id":319338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gates of the Arctic 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 -154.0283203125,\n 67.23806155909902\n ],\n [\n -154.0283203125,\n 68.2042121888185\n ],\n [\n -152.0068359375,\n 68.2042121888185\n ],\n [\n -152.0068359375,\n 67.23806155909902\n ],\n [\n -154.0283203125,\n 67.23806155909902\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"96","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56f50fc6e4b0f59b85e1eb47","contributors":{"authors":[{"text":"Schmidt, Joshua H.","contributorId":167772,"corporation":false,"usgs":false,"family":"Schmidt","given":"Joshua H.","affiliations":[{"id":24828,"text":"Central Alaska Network, National Park Service, Fairbanks, Alaska","active":true,"usgs":false}],"preferred":false,"id":623458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":167773,"corporation":false,"usgs":false,"family":"Johnson","given":"Devin","email":"","middleInitial":"S.","affiliations":[{"id":24829,"text":"National Marine Mammal Laboratory, Alaska Fisheries Science Center, National Marine Fisheries Service, NOAA, Seattle, Washington","active":true,"usgs":false}],"preferred":false,"id":623459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindberg, Mark S.","contributorId":167774,"corporation":false,"usgs":false,"family":"Lindberg","given":"Mark","email":"","middleInitial":"S.","affiliations":[{"id":24830,"text":"Department of Wildlife and Institute of Arctic Biology, University of Alaska, Fairbanks, Alaska","active":true,"usgs":false}],"preferred":false,"id":623460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":623457,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194287,"text":"70194287 - 2015 - Reconstructing turbidity in a glacially influenced lake using the Landsat TM and ETM+ surface reflectance climate data record archive, Lake Clark, Alaska","interactions":[],"lastModifiedDate":"2017-11-21T16:37:41","indexId":"70194287","displayToPublicDate":"2015-10-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Reconstructing turbidity in a glacially influenced lake using the Landsat TM and ETM+ surface reflectance climate data record archive, Lake Clark, Alaska","docAbstract":"Lake Clark is an important nursery lake for sockeye salmon (Oncorhynchus nerka) in the headwaters of Bristol Bay, Alaska, the most productive wild salmon fishery in the world. Reductions in water clarity within Alaska lake systems as a result of increased glacial runoff have been shown to reduce salmon production via reduced abundance of zooplankton and macroinvertebrates. In this study, we reconstruct long-term, lake-wide water clarity for Lake Clark using the Landsat TM and ETM+ surface reflectance products (1985–2014) and in situwater clarity data collected between 2009 and 2013. Analysis of a Landsat scene acquired in 2009, coincident with in situ measurements in the lake, and uncertainty analysis with four scenes acquired within two weeks of field data collection showed that Band 3 surface reflectance was the best indicator of turbidity (r2 = 0.55,RMSE << 0.01). We then processed 151 (98 partial- and 53 whole-lake) Landsat scenes using this relation and detected no significant long-term trend in mean turbidity for Lake Clark between 1991 and 2014. We did, however, detect interannual variation that exhibited a non-significant (r2 = 0.20) but positive correlation (r = 0.20) with regional mean summer air temperature and found the month of May exhibited a significant positive trend (r2 = 0.68, p = 0.02) in turbidity between 2000 and 2014. This study demonstrates the utility of hindcasting turbidity in a glacially influenced lake using the Landsat surface reflectance products. It may also help land and resource managers reconstruct turbidity records for lakes that lack in situ monitoring, and may be useful in predicting future water clarity conditions based on projected climate scenarios.
","language":"English","publisher":"MDPI","doi":"10.3390/rs71013692","usgsCitation":"Baughman, C., Jones, B.M., Bartz, K.K., Young, D.B., and Zimmerman, C.E., 2015, Reconstructing turbidity in a glacially influenced lake using the Landsat TM and ETM+ surface reflectance climate data record archive, Lake Clark, Alaska: Remote Sensing, v. 7, no. 10, p. 13692-13710, https://doi.org/10.3390/rs71013692.","productDescription":"19 p.","startPage":"13692","endPage":"13710","ipdsId":"IP-066580","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":471755,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs71013692","text":"Publisher Index Page"},{"id":349242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Lake Clark","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.84954833984375,\n 60.0113438097352\n ],\n [\n -153.57513427734375,\n 60.0113438097352\n ],\n [\n -153.57513427734375,\n 60.45992621736877\n ],\n [\n -154.84954833984375,\n 60.45992621736877\n ],\n [\n -154.84954833984375,\n 60.0113438097352\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"10","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-20","publicationStatus":"PW","scienceBaseUri":"5a60fe67e4b06e28e9c252f3","contributors":{"authors":[{"text":"Baughman, Carson 0000-0002-9423-9324 cbaughman@usgs.gov","orcid":"https://orcid.org/0000-0002-9423-9324","contributorId":169657,"corporation":false,"usgs":true,"family":"Baughman","given":"Carson","email":"cbaughman@usgs.gov","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":723094,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":723095,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartz, Krista K.","contributorId":200705,"corporation":false,"usgs":false,"family":"Bartz","given":"Krista","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":723097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, Daniel","contributorId":58468,"corporation":false,"usgs":false,"family":"Young","given":"Daniel","affiliations":[{"id":35763,"text":"National Park Service, Lake Clark National Park and Preserve, Port Alsworth, AK","active":true,"usgs":false}],"preferred":false,"id":723098,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":723096,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189142,"text":"70189142 - 2015 - Field guide to the Mesozoic arc and accretionary complex of South-Central Alaska, Indian to Hatcher Pass","interactions":[],"lastModifiedDate":"2017-07-03T10:06:31","indexId":"70189142","displayToPublicDate":"2015-09-30T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":13,"text":"Handbook"},"title":"Field guide to the Mesozoic arc and accretionary complex of South-Central Alaska, Indian to Hatcher Pass","docAbstract":"This field trip traverses exposures of a multi-generation Mesozoic magmatic arc and subduction-accretion complex that had a complicated history of magmatic activity and experienced variations in composition and deformational style in response to changes in the tectonic environment. This Mesozoic arc formed at an unknown latitude to the south, was accreted to North America, and was subsequently transported along faults to its present location (Plafker and others, 1989; Hillhouse and Coe, 1994). Some of these faults are still active. Similar tectonic, igneous, and sedimentary processes to those that formed the Mesozoic arc complex persist today in southern Alaska, building on, and deforming the Mesozoic arc. The rocks we will see on this field trip provide insights on the three-dimensional composition of the modern arc, and the processes involved in the evolution of an arc and its companion accretionary complex.
","largerWorkTitle":"Fieldtrip Guidebook","language":"English","publisher":"Geological Society of America","usgsCitation":"Karl, S.M., Oswald, P., and Hults, C.P., 2015, Field guide to the Mesozoic arc and accretionary complex of South-Central Alaska, Indian to Hatcher Pass, Report: 66 p.: HTML.","productDescription":"Report: 66 p.: HTML","startPage":"1","endPage":"66","ipdsId":"IP-056862","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":343274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":343273,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://archives.datapages.com/data/alaska/data/039/039001/1_akgs0390001.htm"}],"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 -161.76269531250003,\n 55.30413773740139\n ],\n [\n -133.3740234375,\n 55.30413773740139\n ],\n [\n -133.3740234375,\n 62.57310578449978\n ],\n [\n -161.76269531250003,\n 62.57310578449978\n ],\n [\n -161.76269531250003,\n 55.30413773740139\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595b5799e4b0d1f9f0536dc7","contributors":{"authors":[{"text":"Karl, Susan M. 0000-0003-1559-7826 skarl@usgs.gov","orcid":"https://orcid.org/0000-0003-1559-7826","contributorId":502,"corporation":false,"usgs":true,"family":"Karl","given":"Susan","email":"skarl@usgs.gov","middleInitial":"M.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":703255,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oswald, P.J.","contributorId":72269,"corporation":false,"usgs":true,"family":"Oswald","given":"P.J.","email":"","affiliations":[],"preferred":false,"id":703148,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hults, Chad P. chults@usgs.gov","contributorId":1930,"corporation":false,"usgs":true,"family":"Hults","given":"Chad","email":"chults@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":false,"id":703256,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70155920,"text":"sim3334 - 2015 - Reconnaissance surficial geologic map of the Taylor Mountains quadrangle, southwestern Alaska","interactions":[],"lastModifiedDate":"2017-12-19T15:07:17","indexId":"sim3334","displayToPublicDate":"2015-09-28T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3334","displayTitle":"Reconnaissance surficial geologic map of the Taylor Mountains quadrangle, southwestern Alaska","title":"Reconnaissance surficial geologic map of the Taylor Mountains quadrangle, southwestern Alaska","docAbstract":"This map and accompanying digital files are the result of the interpretation of aerial photographs from the 1950s as well as more modern imagery. The area, long considered a part of Alaska that was largely not glaciated (see Karlstrom, 1964; Coulter and others, 1965; or Péwé, 1975), actually has a long history reflecting local and more distant glaciations. An unpublished photogeologic map of the Taylor Mountains quadrangle from the 1950s by J.N. Platt Jr. was useful in the construction of this map. Limited new field mapping in the area was conducted as part of a mapping project in the Dillingham quadrangle to the south (Wilson and others, 2003); however, extensive aerial photograph interpretation represents the bulk of the mapping effort. The accompanying digital files show the sources for each line and geologic unit shown on the map.
\nI used the Platt and Muller 1950s-era aerial photographic interpretation map as the starting point for the surficial geology; their unpublished data were produced using a reconnaissance quality topographic base map. In addition to transferring their data to a modern base to use as a guide, all of the photographs were re-examined. As result, in a number of areas, the features have been reinterpreted and the linework revised. A major difference between the maps is the recognition of much more extensive glacially dammed lake deposits and reassignment of some glacial deposits to different glacial events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3334","usgsCitation":"Wilson, F.H., 2017, Reconnaissance surficial geologic map of the Taylor Mountains quadrangle, southwestern Alaska (ver. 1.2, December 2017): U.S. Geological Survey Scientific Investigations Map 3334, pamphlet 12 p., scale 1:250,000, https://doi.org/10.3133/sim3334.","productDescription":"Report: iii, 12 p.; 1 Sheet: 41.01 x 31.37 inches; GIS files and related databases; Metadata; Readme","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-061421","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":308630,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3334/sim3334_metadata.xml","text":"XML"},{"id":308631,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3334/sim3334_metadata.txt","text":"TXT"},{"id":347918,"rank":10,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3334/sim3334versionHist_v1.2.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3334 Version Hystory"},{"id":308228,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3334/sim3334_pamphlet_v1.2.pdf","text":"Pamphlet","size":"175 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3334 Pamphlet PDF"},{"id":308229,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3334/sim3334_sheet_v1.2.pdf","text":"Sheet","size":"119 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3334 Sheet"},{"id":308629,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3334/sim3334_metadata.html","text":"HTML"},{"id":308628,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3334/sim3334_database.zip","text":"GIS files and related databases","size":"87.8 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3334 GIS files and databases"},{"id":308632,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3334/sim3334_metadata_faq.html","text":"Metadata FAQ"},{"id":308633,"rank":9,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3334/sim3334_readme.pdf","size":"215 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":308227,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3334/coverthb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Taylor Mountains quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n \n \n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.895263671875,\n 59.94950917225228\n ],\n [\n -158.895263671875,\n 61.03701223240189\n ],\n [\n -155.73120117187497,\n 61.03701223240189\n ],\n [\n -155.73120117187497,\n 59.94950917225228\n ],\n [\n -158.895263671875,\n 59.94950917225228\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted September 28, 2015; Version 1.1: October 31, 2017; Version 1.2: December 19, 2017","contact":"Alaska Science Center staff
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
Alaska Mineral Resources
Alaska Science Center
Arctic land-cover changes induced by recent global climate change (e.g., expansion of woody vegetation into tundra and effects of permafrost degradation) are expected to generate further feedbacks to the climate system. Past changes can be used to assess our understanding of feedback mechanisms through a combination of process modeling and paleo-observations. The subcontinental region of Beringia (northeastern Siberia, Alaska, and northwestern Canada) was largely ice-free at the peak of deglacial warming and experienced both major vegetation change and loss of permafrost when many arctic regions were still ice covered. The evolution of Beringian climate at this time was largely driven by global features, such as the amplified seasonal cycle of Northern Hemisphere insolation and changes in global ice volume and atmospheric composition, but changes in regional land-surface controls, such as the widespread development of thaw lakes, the replacement of tundra by deciduous forest or woodland, and the flooding of the Bering–Chukchi land bridge, were probably also important. We examined the sensitivity of Beringia's early Holocene climate to these regional-scale controls using a regional climate model (RegCM). Lateral and oceanic boundary conditions were provided by global climate simulations conducted using the GENESIS V2.01 atmospheric general circulation model (AGCM) with a mixed-layer ocean. We carried out two present-day simulations of regional climate – one with modern and one with 11 ka geography – plus another simulation for 6 ka. In addition, we performed five ~ 11 ka climate simulations, each driven by the same global AGCM boundary conditions: (i) 11 ka Control, which represents conditions just prior to the major transitions (exposed land bridge, no thaw lakes or wetlands, widespread tundra vegetation), (ii) sea-level rise, which employed present-day continental outlines, (iii) vegetation change, with deciduous needleleaf and deciduous broadleaf boreal vegetation types distributed as suggested by the paleoecological record, (iv) thaw lakes, which used the present-day distribution of lakes and wetlands, and (v) post-11 ka All, incorporating all boundary conditions changed in experiments (ii)–(iv). We find that regional-scale controls strongly mediate the climate responses to changes in the large-scale controls, amplifying them in some cases, damping them in others, and, overall, generating considerable spatial heterogeneity in the simulated climate changes. The change from tundra to deciduous woodland produces additional widespread warming in spring and early summer over that induced by the 11 ka insolation regime alone, and lakes and wetlands produce modest and localized cooling in summer and warming in winter. The greatest effect is the flooding of the land bridge and shelves, which produces generally cooler conditions in summer but warmer conditions in winter and is most clearly manifest on the flooded shelves and in eastern Beringia. By 6 ka continued amplification of the seasonal cycle of insolation and loss of the Laurentide ice sheet produce temperatures similar to or higher than those at 11 ka, plus a longer growing season.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/cp-11-1197-2015","usgsCitation":"Bartlein, P., Edwards, M.E., Hostetler, S.W., Shafer, S., Anderson, P.M., Brubaker, L.B., and Lozhkin, A., 2015, Early-Holocene warming in Beringia and its mediation by sea-level and vegetation changes: Climate of the Past, v. 11, no. 9, p. 1197-1222, https://doi.org/10.5194/cp-11-1197-2015.","productDescription":"26 p.","startPage":"1197","endPage":"1222","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062524","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471775,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-11-1197-2015","text":"Publisher Index Page"},{"id":311350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","state":"Alaska","otherGeospatial":"Beringia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -208.65234374999997,\n 42.032974332441405\n ],\n [\n -208.65234374999997,\n 76.31035754301745\n ],\n [\n -115.31249999999999,\n 76.31035754301745\n ],\n [\n -115.31249999999999,\n 42.032974332441405\n ],\n [\n -208.65234374999997,\n 42.032974332441405\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-24","publicationStatus":"PW","scienceBaseUri":"564b0c45e4b0ebfbef0d3144","contributors":{"authors":[{"text":"Bartlein, P. J.","contributorId":54566,"corporation":false,"usgs":false,"family":"Bartlein","given":"P. J.","affiliations":[],"preferred":false,"id":579849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, M. E.","contributorId":29977,"corporation":false,"usgs":true,"family":"Edwards","given":"M.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":579850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":579848,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shafer, Sarah 0000-0003-3739-2637 sshafer@usgs.gov","orcid":"https://orcid.org/0000-0003-3739-2637","contributorId":149866,"corporation":false,"usgs":true,"family":"Shafer","given":"Sarah","email":"sshafer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":579851,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, P. M.","contributorId":71722,"corporation":false,"usgs":true,"family":"Anderson","given":"P.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":579852,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brubaker, L. B","contributorId":149867,"corporation":false,"usgs":false,"family":"Brubaker","given":"L.","email":"","middleInitial":"B","affiliations":[{"id":17844,"text":"University of Washington, Seattle, Washington, USA","active":true,"usgs":false}],"preferred":false,"id":579853,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lozhkin, A. V","contributorId":149868,"corporation":false,"usgs":false,"family":"Lozhkin","given":"A. V","affiliations":[{"id":17845,"text":"North East Interdisciplinary Research Inst, Far East Branch Russian Academy of Sciences, Magadan, Russia","active":true,"usgs":false}],"preferred":false,"id":579854,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70175782,"text":"70175782 - 2015 - Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution","interactions":[],"lastModifiedDate":"2016-08-19T10:31:38","indexId":"70175782","displayToPublicDate":"2015-09-18T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution","docAbstract":"High-resolution satellite imagery is a promising tool for providing coarse information about polar species abundance and distribution, but current applications are limited. With polar bears (Ursus maritimus), the technique has only proven effective on landscapes with little topographic relief that are devoid of snow and ice, and time-consuming manual review of imagery is required to identify bears. Here, we evaluated mechanisms to further develop methods for satellite imagery by examining data from Rowley Island, Canada. We attempted to automate and expedite detection via a supervised spectral classification and image differencing to expedite image review. We also assessed what proportion of a region should be sampled to obtain reliable estimates of density and abundance. Although the spectral signature of polar bears differed from nontarget objects, these differences were insufficient to yield useful results via a supervised classification process. Conversely, automated image differencing—or subtracting one image from another—correctly identified nearly 90% of polar bear locations. This technique, however, also yielded false positives, suggesting that manual review will still be required to confirm polar bear locations. On Rowley Island, bear distribution approximated a Poisson distribution across a range of plot sizes, and resampling suggests that sampling >50% of the site facilitates reliable estimation of density (CV <15%). Satellite imagery may be an effective monitoring tool in certain areas, but large-scale applications remain limited because of the challenges in automation and the limited environments in which the method can be effectively applied. Improvements in resolution may expand opportunities for its future uses.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.596","usgsCitation":"LaRue, M.A., Stapleton, S.P., Porter, C., Atkinson, S.N., Atwood, T.C., Dyck, M., and Lecomte, N., 2015, Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution: Wildlife Society Bulletin, v. 39, no. 4, p. 772-779, https://doi.org/10.1002/wsb.596.","productDescription":"7 p.","startPage":"772","endPage":"779","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063293","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":500053,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/52601c9e182c489182032129672f748f","text":"External Repository"},{"id":326931,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Rowley Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.44238281249999,\n 69.21525256928653\n ],\n [\n -78.3544921875,\n 69.18404149599671\n ],\n [\n -78.2391357421875,\n 69.2425255645653\n ],\n [\n -78.1842041015625,\n 69.3086176331298\n ],\n [\n -78.1787109375,\n 69.35127582255352\n ],\n [\n -78.2830810546875,\n 69.3899830007604\n ],\n [\n -78.44238281249999,\n 69.39964894620636\n ],\n [\n -78.519287109375,\n 69.40931055535233\n ],\n [\n -78.64562988281249,\n 69.39191653683379\n ],\n [\n -78.7884521484375,\n 69.34740128319982\n ],\n [\n -78.717041015625,\n 69.29114227947211\n ],\n [\n -78.782958984375,\n 69.26976435077849\n ],\n [\n -78.8818359375,\n 69.20940390181205\n ],\n [\n -78.9312744140625,\n 69.15083065920365\n ],\n [\n -78.9422607421875,\n 69.12344255014861\n ],\n [\n -79.0411376953125,\n 69.13518451752405\n ],\n [\n -79.07958984375,\n 69.12148494192485\n ],\n [\n -79.21142578125,\n 69.12148494192485\n ],\n [\n -79.43115234375,\n 68.932736060549\n ],\n [\n -79.4146728515625,\n 68.83180177092166\n ],\n [\n -79.189453125,\n 68.81394200526994\n ],\n [\n -78.9093017578125,\n 68.87341871078524\n ],\n [\n -78.760986328125,\n 68.932736060549\n ],\n [\n -78.6016845703125,\n 69.03321086259241\n ],\n [\n -78.49731445312499,\n 69.08621799303475\n ],\n [\n -78.49731445312499,\n 69.12735724054714\n ],\n [\n -78.4259033203125,\n 69.17037257214531\n ],\n [\n -78.44238281249999,\n 69.21525256928653\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-18","publicationStatus":"PW","scienceBaseUri":"57b82dece4b03fd6b7da3a22","contributors":{"authors":[{"text":"LaRue, Michelle A.","contributorId":20634,"corporation":false,"usgs":true,"family":"LaRue","given":"Michelle","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":646378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stapleton, Seth P. sstapleton@usgs.gov","contributorId":3979,"corporation":false,"usgs":true,"family":"Stapleton","given":"Seth","email":"sstapleton@usgs.gov","middleInitial":"P.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":646379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Porter, Claire","contributorId":131120,"corporation":false,"usgs":false,"family":"Porter","given":"Claire","email":"","affiliations":[],"preferred":false,"id":646380,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atkinson, Stephen N.","contributorId":12365,"corporation":false,"usgs":false,"family":"Atkinson","given":"Stephen","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":646381,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@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}],"preferred":true,"id":646343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dyck, Markus","contributorId":173868,"corporation":false,"usgs":false,"family":"Dyck","given":"Markus","affiliations":[],"preferred":false,"id":646382,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lecomte, Nicolas","contributorId":131119,"corporation":false,"usgs":false,"family":"Lecomte","given":"Nicolas","email":"","affiliations":[],"preferred":false,"id":646383,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70157256,"text":"70157256 - 2015 - Evaluating species richness: biased ecological inference results from spatial heterogeneity in species detection probabilities","interactions":[],"lastModifiedDate":"2015-09-16T08:56:53","indexId":"70157256","displayToPublicDate":"2015-09-16T09:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating species richness: biased ecological inference results from spatial heterogeneity in species detection probabilities","docAbstract":"Accurate estimates of species richness are necessary to test predictions of ecological theory and evaluate biodiversity for conservation purposes. However, species richness is difficult to measure in the field because some species will almost always be overlooked due to their cryptic nature or the observer's failure to perceive their cues. Common measures of species richness that assume consistent observability across species are inviting because they may require only single counts of species at survey sites. Single-visit estimation methods ignore spatial and temporal variation in species detection probabilities related to survey or site conditions that may confound estimates of species richness. We used simulated and empirical data to evaluate the bias and precision of raw species counts, the limiting forms of jackknife and Chao estimators, and multi-species occupancy models when estimating species richness to evaluate whether the choice of estimator can affect inferences about the relationships between environmental conditions and community size under variable detection processes. Four simulated scenarios with realistic and variable detection processes were considered. Results of simulations indicated that (1) raw species counts were always biased low, (2) single-visit jackknife and Chao estimators were significantly biased regardless of detection process, (3) multispecies occupancy models were more precise and generally less biased than the jackknife and Chao estimators, and (4) spatial heterogeneity resulting from the effects of a site covariate on species detection probabilities had significant impacts on the inferred relationships between species richness and a spatially explicit environmental condition. For a real dataset of bird observations in northwestern Alaska, the four estimation methods produced different estimates of local species richness, which severely affected inferences about the effects of shrubs on local avian richness. Overall, our results indicate that neglecting the effects of site covariates on species detection probabilities may lead to significant bias in estimation of species richness, as well as the inferred relationships between community size and environmental covariates.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/14-1248.1","collaboration":"Colleen Handel","usgsCitation":"McNew, L.B., and Handel, C.M., 2015, Evaluating species richness: biased ecological inference results from spatial heterogeneity in species detection probabilities: Ecological Applications, v. 25, no. 6, p. 1669-1680, https://doi.org/10.1890/14-1248.1.","productDescription":"12 p.","startPage":"1669","endPage":"1680","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056170","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":438682,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7F18WS3","text":"USGS data release","linkHelpText":"Avian Habitat Data; Seward Peninsula, Alaska, 2012"},{"id":438681,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JS9NG2","text":"USGS data release","linkHelpText":"Avian Point Transect Survey, Seward Peninsula, Alaska, 2012"},{"id":308145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55fa8499e4b05d6c4e501a21","contributors":{"authors":[{"text":"McNew, Lance B. lmcnew@usgs.gov","contributorId":5086,"corporation":false,"usgs":true,"family":"McNew","given":"Lance","email":"lmcnew@usgs.gov","middleInitial":"B.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":572453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":572454,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155020,"text":"70155020 - 2015 - Landslides and megathrust splay faults captured by the late Holocene sediment record of eastern Prince William Sound, Alaska","interactions":[],"lastModifiedDate":"2015-10-23T15:48:44","indexId":"70155020","displayToPublicDate":"2015-09-15T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Landslides and megathrust splay faults captured by the late Holocene sediment record of eastern Prince William Sound, Alaska","docAbstract":"We present new marine seismic‐reflection profiles and bathymetric maps to characterize Holocene depositional patterns, submarine landslides, and active faults beneath eastern and central Prince William Sound (PWS), Alaska, which is the eastern rupture patch of the 1964 Mw 9.2 earthquake. We show evidence that submarine landslides, many of which are likely earthquake triggered, repeatedly released along the southern margin of Orca Bay in eastern PWS. We document motion on reverse faults during the 1964 Great Alaska earthquake and estimate late Holocene slip rates for these growth faults, which splay from the subduction zone megathrust. Regional bathymetric lineations help define the faults that extend 40–70 km in length, some of which show slip rates as great as 3.75 mm/yr. We infer that faults mapped below eastern PWS connect to faults mapped beneath central PWS and possibly onto the Alaska mainland via an en echelon style of faulting. Moderate (Mw>4) upper‐plate earthquakes since 1964 give rise to the possibility that these faults may rupture independently to potentially generate Mw 7–8 earthquakes, and that these earthquakes could damage local infrastructure from ground shaking. Submarine landslides, regardless of the source of initiation, could generate local tsunamis to produce large run‐ups along nearby shorelines. In a more general sense, the PWS area shows that faults that splay from the underlying plate boundary present proximal, perhaps independent seismic sources within the accretionary prism, creating a broad zone of potential surface rupture that can extend inland 150 km or more from subduction zone trenches.
","language":"English","publisher":"The Seismological Society of America","publisherLocation":"Stanford","doi":"10.1785/0120140273","usgsCitation":"Finn, S., Liberty, L.M., Haeussler, P.J., and Pratt, T.L., 2015, Landslides and megathrust splay faults captured by the late Holocene sediment record of eastern Prince William Sound, Alaska: Bulletin of the Seismological Society of America, v. 105, no. 5, p. 2343-2353, https://doi.org/10.1785/0120140273.","productDescription":"11 p.","startPage":"2343","endPage":"2353","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066872","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":310615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.512939453125,\n 59.147769484619786\n ],\n [\n -149.512939453125,\n 61.454521127671924\n ],\n [\n -144.20654296875,\n 61.454521127671924\n ],\n [\n -144.20654296875,\n 59.147769484619786\n ],\n [\n -149.512939453125,\n 59.147769484619786\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-15","publicationStatus":"PW","scienceBaseUri":"562b5a30e4b00162522207d6","contributors":{"authors":[{"text":"Finn, S.P.","contributorId":65438,"corporation":false,"usgs":true,"family":"Finn","given":"S.P.","email":"","affiliations":[],"preferred":false,"id":564676,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liberty, Lee M.","contributorId":89631,"corporation":false,"usgs":true,"family":"Liberty","given":"Lee","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":564677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","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":564678,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pratt, Thomas L. 0000-0003-3131-3141 tpratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3131-3141","contributorId":3279,"corporation":false,"usgs":true,"family":"Pratt","given":"Thomas","email":"tpratt@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":564679,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156605,"text":"ofr20151164 - 2015 - Field and laboratory guide to freshwater cyanobacteria harmful algal blooms for Native American and Alaska Native communities","interactions":[],"lastModifiedDate":"2015-09-14T10:30:03","indexId":"ofr20151164","displayToPublicDate":"2015-09-14T09:15:00","publicationYear":"2015","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":"2015-1164","title":"Field and laboratory guide to freshwater cyanobacteria harmful algal blooms for Native American and Alaska Native communities","docAbstract":"Cyanobacteria can produce toxins and form harmful algal blooms. The Native American and Alaska Native communities that are dependent on subsistence fishing have an increased risk of exposure to these cyanotoxins. It is important to recognize the presence of an algal bloom in a waterbody and to distinguish a potentially toxic harmful algal bloom from a non-toxic bloom. This guide provides field images that show cyanobacteria blooms, some of which can be toxin producers, as well as other non-toxic algae blooms and floating plants that might be confused with algae. After recognition of a potential toxin-producing cyanobacterial bloom in the field, the type(s) of cyanobacteria present needs to be identified. Species identification, which requires microscopic examination, may help distinguish a toxin-producer from a non-toxin producer. This guide also provides microscopic images of the common cyanobacteria that are known to produce toxins, as well as images of algae that form blooms but do not produce toxins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151164","usgsCitation":"Rosen, B.H., and St. Amand, Ann, Field and laboratory guide to freshwater cyanobacteria harmful algal blooms for Native American and Alaska Native Communities: U.S. Geological Survey Open-File Report 2015–1164, 44 p., https://dx.doi.org/10.3133/ofr20151164.","productDescription":"vi, 44 p.","numberOfPages":"54","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065834","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":308071,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1164/ofr20151164.pdf","text":"Report","size":"7.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1164"},{"id":308070,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1164/coverthb.jpg"}],"contact":"National Tribal Liaison
USGS Office of Tribal Relations
12201 Sunrise Valley Drive, Mail Stop 911
Reston, VA 20192
(703) 648-4437
Through the Changing Arctic Ecosystems (CAE) initiative, the U.S. Geological Survey (USGS) informs key resource management decisions for Arctic Alaska by providing scientific information on current and future ecosystem response to a warming climate. The Arctic Coastal Plain (ACP) of northern Alaska is a key study area within the USGS CAE initiative. This region has experienced a warming trend over the past decades, leading to decreased sea ice, permafrost thaw, and an advancement of spring phenology. The number of birds on the ACP also is changing, marked by increased populations of the four species of geese that nest in the region. The Snow Goose (Chen caerulescens) is the most rapidly increasing of these species. USGS CAE research is quantifying these changes and their implications for management agencies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153062","usgsCitation":"Hupp, J.W., Ward, D.H., Whalen, M.E., and Pearce, J.M., 2015, Changing Arctic ecosystems—What is causing the rapid increase of Snow Geese in northern Alaska?: U.S. Geological Survey Fact Sheet 2015-3062, 2 p., https://dx.doi.org/10.3133/fs20153062.","productDescription":"Report: 2 p.; HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-068563","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":308049,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3062/images/coverthb.jpg"},{"id":308051,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3062/","text":"Fact Sheet HTML","description":"HTML version of FS 2015-3062"},{"id":308050,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3062/pdf/fs20153062.pdf","text":"Fact Sheet","size":"375 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3062"}],"country":"United States","state":"Alaska","otherGeospatial":"Colville River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.8623046875,\n 68.77619083759828\n ],\n [\n -158.8623046875,\n 70.48089578887483\n ],\n [\n -150.22705078124997,\n 70.48089578887483\n ],\n [\n -150.22705078124997,\n 68.77619083759828\n ],\n [\n -158.8623046875,\n 68.77619083759828\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"U.S. Geological Survey
4210 University Drive, Anchorage, AK 99508
http://alaska.usgs.gov
Avian influenza viruses are naturally occurring in wild birds such as ducks, geese, swans, and gulls. These viruses generally do not cause illness in wild birds, however, when spread to poultry they can be highly pathogenic and cause illness and death in backyard and commercial farms. Outbreaks may cause devastating agricultural economic losses and some viral strains have the potential to infect people directly. Furthermore, the combination of avian influenza viruses with mammalian viruses can result in strains with the ability to transmit from person to person, possibly leading to viruses with pandemic potential. All known pandemic influenza viruses have had some genetic material of avian origin. Since 1996, a strain of highly pathogenic avian influenza (HPAI) virus, H5N1, has caused infection in wild birds, losses to poultry farms in Eurasia and North Africa, and led to the deaths of several hundred people. Spread of the H5N1 virus and other influenza strains from China was likely facilitated by migratory birds. In December 2014, HPAI was detected in poultry in Canada and migratory birds in the United States. Since then, HPAI viruses have spread to large parts of the United States and will likely continue to spread through migratory bird flyways and other mechanisms throughout North America. In the United States, HPAI viruses have severely affected the poultry industry with millions of domestic birds dead or culled. These strains of HPAI are not known to cause disease in humans; however, the Centers for Disease Control and Prevention (CDC) advise caution when in close contact with infected birds. Experts agree that HPAI strains currently circulating in wild birds of North America will likely persist for the next few years. This unprecedented situation presents risks to the poultry industry, natural resource management, and potentially human health. Scientific knowledge and decision support tools are urgently needed to understand factors affecting the persistence of HPAI in wild birds, to forecast future spread of HPAI by wild birds, and to detect novel strains of HPAI that may emerge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153060","usgsCitation":"Harris, M.C., Miles, A.K., Pearce, J.M., Prosser, D.J., Sleeman, J.M., and Whalen, M.E., 2015, USGS highly pathogenic avian influenza research strategy: U.S. Geological Survey Fact Sheet 2015-3060, 4 p., https://dx.doi.org/10.3133/fs20153060.","productDescription":"Report: 4 p.; HTML Document","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-067931","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":308013,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3060/pdf/fs20153060.pdf","text":"Fact Sheet","size":"975 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3060"},{"id":308014,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3060/","text":"Fact Sheet HTML","description":"HTML version of FS 2015-3060"},{"id":308012,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3060/images/coverthb.jpg"}],"contact":"Anne Kinsinger
USGS Associate Director for Ecosystems
703-648-4050
akinsinger@usgs.gov
M. Camille Harris
USGS Wildlife Disease Coordinator
703-648-4019
mcharris@usgs.gov
Avian influenza viruses are naturally occurring in wild birds such as ducks, geese, swans, and gulls. These viruses generally do not cause illness in wild birds, however, when spread to poultry they can be highly pathogenic and cause illness and death in backyard and commercial farms. Outbreaks may cause devastating agricultural economic losses and some viral strains have the potential to infect people directly. Furthermore, the combination of avian influenza viruses with mammalian viruses can result in strains with the ability to transmit from person to person, possibly leading to viruses with pandemic potential. All known pandemic influenza viruses have had some genetic material of avian origin. Since 1996, a strain of highly pathogenic avian influenza (HPAI) virus, H5N1, has caused infection in wild birds, losses to poultry farms in Eurasia and North Africa, and led to the deaths of several hundred people. Spread of the H5N1 virus and other influenza strains from China was likely facilitated by migratory birds. In December 2014, HPAI was detected in poultry in Canada and migratory birds in the United States. Since then, HPAI viruses have spread to large parts of the United States and will likely continue to spread through migratory bird flyways and other mechanisms throughout North America. In the United States, HPAI viruses have severely affected the poultry industry with millions of domestic birds dead or culled. These strains of HPAI are not known to cause disease in humans; however, the Centers for Disease Control and Prevention (CDC) advise caution when in close contact with infected birds. Experts agree that HPAI strains currently circulating in wild birds of North America will likely persist for the next few years. This unprecedented situation presents risks to the poultry industry, natural resource management, and potentially human health. Scientific knowledge and decision support tools are urgently needed to understand factors affecting the persistence of HPAI in wild birds, to forecast future spread of HPAI by wild birds, and to detect novel strains of HPAI that may emerge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153059","usgsCitation":"Harris, M.C., Miles, A.K., Pearce, J.M., Prosser, D.J., Sleeman, J.M., and Whalen, M.E., 2015, USGS role and response to highly pathogenic avian influenza: U.S. Geological Survey Fact Sheet 2015-3059, 2 p., https://dx.doi.org/10.3133/fs20153059.","productDescription":"Report: 2 p.; HTML Document","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066180","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":308009,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3059/","text":"Fact Sheet HTML","description":"HTML version of FS 2015-3059"},{"id":308008,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3059/pdf/fs20153059.pdf","text":"Fact Sheet","size":"745 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3059"},{"id":308007,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3059/images/coverthb.jpg"}],"contact":"Anne Kinsinger
USGS Associate Director for Ecosystems
703-648-4050
akinsinger@usgs.gov
M. Camille Harris
USGS Wildlife Disease Coordinator
703-648-4019
mcharris@usgs.gov
Subglacial discharge influences glacier basal motion and erodes and redeposits sediment. At tidewater glacier termini, discharge drives submarine terminus melting, affects fjord circulation, and is a central component of proglacial marine ecosystems. However, our present inability to track subglacial discharge and its variability significantly hinders our understanding of these processes. Here we report observations of hourly to seasonal variations in 1.5–10 Hz seismic tremor that strongly correlate with subglacial discharge but not with basal motion, weather, or discrete icequakes. Our data demonstrate that vigorous discharge occurs from tidewater glaciers during summer, in spite of fast basal motion that could limit the formation of subglacial conduits, and then abates during winter. Furthermore, tremor observations and a melt model demonstrate that drainage efficiency of tidewater glaciers evolves seasonally. Glaciohydraulic tremor provides a means by which to quantify subglacial discharge variations and offers a promising window into otherwise obscured glacierized environments.
","language":"English","publisher":"Wiley","doi":"10.1002/2015GL064590","usgsCitation":"Bartholomaus, T.C., Amundson, J.M., Walter, J., O’Neel, S., West, M.E., and Larsen, C.F., 2015, Subglacial discharge at tidewater glaciers revealed by seismic tremor: Geophysical Research Letters, v. 42, no. 15, p. 6391-6398, https://doi.org/10.1002/2015GL064590.","productDescription":"8 p.","startPage":"6391","endPage":"6398","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060356","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":471808,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl064590","text":"Publisher Index Page"},{"id":307956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greenland, United States","state":"Alaska","otherGeospatial":"Columbia Glacier, Hubbard Glacier, Jakobshavn Isbræ, Mendenhall Glacier, 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The long-tailed duck adenovirus genome was approximately 27 kb. A 907 bp hexon gene segment was used to design primers specific for the long-tailed duck adenovirus. Nineteen isolates were phylogenetically characterized based on portions of their hexon gene and 12 were most closely related to Goose adenovirus A. The remaining 7 shared no hexon sequences with any known adenoviruses. Experimental infections of mallards with a long-tailed duck reference adenovirus caused mild lymphoid infiltration of the intestine and paint brush hemorrhages of the mucosa and dilation of the intestine. This study shows novel adenoviruses from long-tailed ducks are diverse and provides further evidence that they should be considered in cases of morbidity and mortality in sea ducks. Conserved and specific primers have been developed that will help screen sea ducks for adenoviral infections.
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Christian 0000-0002-0251-4238 jfranson@usgs.gov","orcid":"https://orcid.org/0000-0002-0251-4238","contributorId":140358,"corporation":false,"usgs":true,"family":"Franson","given":"J.","email":"jfranson@usgs.gov","middleInitial":"Christian","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":546932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hollmen, Tuula E.","contributorId":106077,"corporation":false,"usgs":true,"family":"Hollmen","given":"Tuula","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":546935,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159739,"text":"70159739 - 2015 - Re-colonization by common eiders Somateria mollissima in the Aleutian Archipelago following removal of introduced arctic foxes Vulpes lagopus","interactions":[],"lastModifiedDate":"2021-09-01T16:05:43.950398","indexId":"70159739","displayToPublicDate":"2015-09-01T00:00:00","publicationYear":"2015","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}},"displayTitle":"Re-colonization by common eiders Somateria mollissima in the Aleutian Archipelago following removal of introduced arctic foxes Vulpes lagopus","title":"Re-colonization by common eiders Somateria mollissima in the Aleutian Archipelago following removal of introduced arctic foxes Vulpes lagopus","docAbstract":"Islands provide refuges for populations of many species where they find safety from predators, but the introduction of predators frequently results in elimination or dramatic reductions in island-dwelling organisms. When predators are removed, re-colonization for some species occurs naturally, and inter-island phylogeographic relationships and current movement patterns can illuminate processes of colonization. We studied a case of re-colonization of common eiders Somateria mollissima following removal of introduced arctic foxes Vulpes lagopus in the Aleutian Archipelago, Alaska. We expected common eiders to resume nesting on islands cleared of foxes and to re-colonize from nearby islets, islands, and island groups. We thus expected common eiders to show limited genetic structure indicative of extensive mixing among island populations. Satellite telemetry was used to record current movement patterns of female common eiders from six islands across three island groups. We collected genetic data from these and other nesting common eiders at 14 microsatellite loci and the mitochondrial DNA control region to examine population genetic structure, historical fluctuations in population demography, and gene flow. Our results suggest recent interchange among islands. Analysis of microsatellite data supports satellite telemetry data of increased dispersal of common eiders to nearby areas and little between island groups. Although evidence from mtDNA is suggestive of female dispersal among island groups, gene flow is insufficient to account for recolonization and rapid population growth. Instead, near-by remnant populations of common eiders contributed substantially to population expansion, without which re-colonization would have likely occurred at a much lower rate. Genetic and morphometric data of common eiders within one island group two and three decades after re-colonization suggests reduced movement of eiders among islands and little movement between island groups after populations were re-established. We predict that re-colonization of an island group where all common eiders are extirpated could take decades.
","language":"English","publisher":"Wiley","doi":"10.1111/jav.00626","usgsCitation":"Petersen, M.R., Sonsthagen, S.A., and Sexson, M.G., 2015, Re-colonization by common eiders Somateria mollissima in the Aleutian Archipelago following removal of introduced arctic foxes Vulpes lagopus: Journal of Avian Biology, v. 46, no. 5, p. 538-549, https://doi.org/10.1111/jav.00626.","productDescription":"12 p.","startPage":"538","endPage":"549","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054807","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":311558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Andreanof Islands, Near Islands, Rat Islands,","volume":"46","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-12","publicationStatus":"PW","scienceBaseUri":"564f00c9e4b064dd1d09558c","contributors":{"authors":[{"text":"Petersen, Margaret R. 0000-0001-6082-3189 mrpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-6082-3189","contributorId":167729,"corporation":false,"usgs":true,"family":"Petersen","given":"Margaret","email":"mrpetersen@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":580290,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":580291,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sexson, Matthew G. 0000-0002-1078-0835 msexson@usgs.gov","orcid":"https://orcid.org/0000-0002-1078-0835","contributorId":5544,"corporation":false,"usgs":true,"family":"Sexson","given":"Matthew","email":"msexson@usgs.gov","middleInitial":"G.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":580292,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186566,"text":"70186566 - 2015 - Development of twelve microsatellite loci in the red tree corals Primnoa resedaeformis and Primnoa pacifica","interactions":[],"lastModifiedDate":"2017-04-05T15:57:17","indexId":"70186566","displayToPublicDate":"2015-09-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1325,"text":"Conservation Genetics Resources","active":true,"publicationSubtype":{"id":10}},"title":"Development of twelve microsatellite loci in the red tree corals Primnoa resedaeformis and Primnoa pacifica","docAbstract":"A suite of tetra-, penta-, and hexa-nucleotide microsatellite loci were developed from Roche 454 pyrosequencing data for the cold-water octocorals Primnoa resedaeformis and P. pacifica. Twelve of 98 primer sets tested consistently amplified in 30 P. resedaeformis samples from Baltimore Canyon (western North Atlantic Ocean) and in 24 P. pacifica samples (Shutter Ridge, eastern Gulf of Alaska). The loci displayed moderate levels of allelic diversity (average 7.5 alleles/locus) and heterozygosity (average 47 %). Levels of genetic diversity were sufficient to produce unique multi-locus genotypes and to distinguish species. These common species are long-lived (hundreds of years) and provide essential fish habitat (P. pacifica), yet populations are provided little protection from human activities. These loci will be used to determine regional patterns of population connectivity to inform effective marine spatial planning and ecosystem-based fisheries management.
","language":"English","publisher":"Springer","doi":"10.1007/s12686-015-0455-1","usgsCitation":"Morrison, C.L., Springmann, M.J., Shroades, K., and Stone, R.P., 2015, Development of twelve microsatellite loci in the red tree corals Primnoa resedaeformis and Primnoa pacifica: Conservation Genetics Resources, v. 7, no. 3, p. 763-765, https://doi.org/10.1007/s12686-015-0455-1.","productDescription":"3 p.","startPage":"763","endPage":"765","ipdsId":"IP-061828","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":339267,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-21","publicationStatus":"PW","scienceBaseUri":"58e60273e4b09da6799ac685","contributors":{"authors":[{"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":689603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Springmann, Marcus J. mspringmann@usgs.gov","contributorId":4372,"corporation":false,"usgs":true,"family":"Springmann","given":"Marcus","email":"mspringmann@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":689604,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shroades, Kelsey kshroades@usgs.gov","contributorId":190568,"corporation":false,"usgs":true,"family":"Shroades","given":"Kelsey","email":"kshroades@usgs.gov","affiliations":[],"preferred":true,"id":689605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stone, Robert P.","contributorId":190569,"corporation":false,"usgs":false,"family":"Stone","given":"Robert","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":689606,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157158,"text":"70157158 - 2015 - A rapid estimation of near field tsunami run-up","interactions":[],"lastModifiedDate":"2015-10-26T14:13:08","indexId":"70157158","displayToPublicDate":"2015-08-19T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"A rapid estimation of near field tsunami run-up","docAbstract":"Many efforts have been made to quickly estimate the maximum run-up height of tsunamis associated with large earthquakes. This is a difficult task, because of the time it takes to construct a tsunami model using real time data from the source. It is possible to construct a database of potential seismic sources and their corresponding tsunami a priori.However, such models are generally based on uniform slip distributions and thus oversimplify the knowledge of the earthquake source. Here, we show how to predict tsunami run-up from any seismic source model using an analytic solution, that was specifically designed for subduction zones with a well defined geometry, i.e., Chile, Japan, Nicaragua, Alaska. The main idea of this work is to provide a tool for emergency response, trading off accuracy for speed. The solutions we present for large earthquakes appear promising. Here, run-up models are computed for: The 1992 Mw 7.7 Nicaragua Earthquake, the 2001 Mw 8.4 Perú Earthquake, the 2003Mw 8.3 Hokkaido Earthquake, the 2007 Mw 8.1 Perú Earthquake, the 2010 Mw 8.8 Maule Earthquake, the 2011 Mw 9.0 Tohoku Earthquake and the recent 2014 Mw 8.2 Iquique Earthquake. The maximum run-up estimations are consistent with measurements made inland after each event, with a peak of 9 m for Nicaragua, 8 m for Perú (2001), 32 m for Maule, 41 m for Tohoku, and 4.1 m for Iquique. Considering recent advances made in the analysis of real time GPS data and the ability to rapidly resolve the finiteness of a large earthquake close to existing GPS networks, it will be possible in the near future to perform these calculations within the first minutes after the occurrence of similar events. Thus, such calculations will provide faster run-up information than is available from existing uniform-slip seismic source databases or past events of pre-modeled seismic sources.
","language":"English","publisher":"Wiley","doi":"10.1002/2015JB012218","usgsCitation":"Riqueime, S., Fuentes, M., Hayes, G.P., and Campos, J., 2015, A rapid estimation of near field tsunami run-up: Journal of Geophysical Research, v. 120, no. 9, p. 6487-6500, https://doi.org/10.1002/2015JB012218.","productDescription":"14 p.","startPage":"6487","endPage":"6500","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068627","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471867,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012218","text":"Publisher Index Page"},{"id":308323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-26","publicationStatus":"PW","scienceBaseUri":"56012a39e4b03bc34f5443ee","contributors":{"authors":[{"text":"Riqueime, Sebastian","contributorId":147554,"corporation":false,"usgs":false,"family":"Riqueime","given":"Sebastian","email":"","affiliations":[{"id":16869,"text":"National Seismological Center (CSN), University of Chile, Santiago, Chile","active":true,"usgs":false}],"preferred":false,"id":571999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuentes, Mauricio","contributorId":147555,"corporation":false,"usgs":false,"family":"Fuentes","given":"Mauricio","email":"","affiliations":[{"id":16870,"text":"Department of Geophysics, University of Chile, Santiago, Chile","active":true,"usgs":false}],"preferred":false,"id":572000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Gavin P. 0000-0003-3323-0112 ghayes@usgs.gov","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":147556,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin","email":"ghayes@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":572001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campos, Jamie","contributorId":147557,"corporation":false,"usgs":false,"family":"Campos","given":"Jamie","email":"","affiliations":[{"id":16870,"text":"Department of Geophysics, University of Chile, Santiago, Chile","active":true,"usgs":false}],"preferred":false,"id":572002,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70155402,"text":"sir20155110 - 2015 - 2013 volcanic activity in Alaska: summary of events and response of the Alaska Volcano Observatory","interactions":[],"lastModifiedDate":"2015-08-17T09:31:36","indexId":"sir20155110","displayToPublicDate":"2015-08-14T17:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5110","title":"2013 volcanic activity in Alaska: summary of events and response of the Alaska Volcano Observatory","docAbstract":"The Alaska Volcano Observatory (AVO) responded to eruptions, volcanic unrest or suspected unrest, and seismic events at 18 volcanic centers in Alaska during 2013. Beginning with the 2013 AVO Summary of Events, the annual description of the AVO seismograph network and activity, once a stand-alone publication, is now part of this report. Because of this change, the annual summary now contains an expanded description of seismic activity at Alaskan volcanoes. Eruptions occurred at three volcanic centers in 2013: Pavlof Volcano in May and June, Mount Veniaminof Volcano in June through December, and Cleveland Volcano throughout the year. None of these three eruptive events resulted in 24-hour staffing at AVO facilities in Anchorage or Fairbanks.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155110","collaboration":"The Alaska Volcano Observatory is a cooperative program of the U.S. Geological Survey, University of Alaska Fairbanks Geophysical Institute, and the Alaska Division of Geological & Geophysical Surveys. The Alaska Volcano Observatory is funded by the U.S. Geological Survey Volcano Hazards Program and the State of Alaska.","usgsCitation":"Dixon, J.P., Cameron, Cheryl, McGimsey, R.G., Neal, C.A., and Waythomas, Chris, 2015, 2013 Volcanic activity in Alaska—Summary of events and response of the Alaska Volcano Observatory: U.S. Geological Survey Scientific Investigations Report 2015–5110, 92 p., https://dx.doi.org/10.3133/sir20155110.","productDescription":"vii, 92 p.","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060824","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":306769,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5110/sir20155110.pdf","text":"Report","size":"35.5","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5110 report"},{"id":306768,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5110/coverthb.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 -183.2958984375,\n 51.01375465718821\n ],\n [\n -183.2958984375,\n 61.75233128411639\n ],\n [\n -149.1064453125,\n 61.75233128411639\n ],\n [\n -149.1064453125,\n 51.01375465718821\n ],\n [\n -183.2958984375,\n 51.01375465718821\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Volcano Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, Alaska 99508
http://volcanoes.usgs.gov/
Mountain glaciers and ice caps cover an area of over 400 000 km2 in the Arctic, and are a major influence on global sea level (Gardner et al. 2011, 2013; Jacob et al. 2012). They gain mass by snow accumulation and lose mass by meltwater runoff. Where they terminate in water (ocean or lake), they also lose mass by iceberg calving. The climatic mass balance (Bclim, the difference between annual snow accumulation and annual meltwater runoff) is a widely used index of how glaciers respond to climate variability and change. The total mass balance (ΔM) is defined as the difference between annual snow accumulation and annual mass losses (by iceberg calving plus runoff).
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\":{\"name\":\"Alaska\",\"nation\":\"USA \"}}]}","contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401-2602
http://ngtoc.usgs.gov/
Large research studies are often challenged to effectively expose and document the types of information being collected and the reasons for data collection across what are often a diverse cadre of investigators of differing disciplines. We applied concepts from the field of information or data modeling to the U.S. Geological Survey (USGS) Changing Arctic Ecosystems (CAE) initiative to prototype an application of information modeling. The USGS CAE initiative is collecting information from marine and terrestrial environments in Alaska to identify and understand the links between rapid physical changes in the Arctic and response of wildlife populations to these ecosystem changes. An associated need is to understand how data collection strategies are informing the overall science initiative and facilitating communication of those strategies to a wide audience. We explored the use of conceptual data modeling to provide a method by which to document, describe, and visually communicate both enterprise and study level data; provide a simple means to analyze commonalities and differences in data acquisition strategies between studies; and provide a tool for discussing those strategies among researchers and managers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151148","collaboration":"Science to Support the USGS Changing Arctic Ecosystems Initiative","usgsCitation":"Walworth, Dennis, and Pearce, J.M., 2015, Conceptual data modeling of wildlife response indicators to\necosystem change in the Arctic: U.S. Geological Survey Open-File Report 2015-1148, 28 p.,\nhttps://dx.doi.org/10.3133/ofr20151148.","productDescription":"iv, 28 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-053898","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":306449,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1148/coverthb.jpg"},{"id":306450,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1148/ofr20151148.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1148 Report"}],"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 -168.48632812499997,\n 62.3903694381427\n ],\n [\n -168.48632812499997,\n 71.46912418989677\n ],\n [\n -144.84375,\n 71.46912418989677\n ],\n [\n -144.84375,\n 62.3903694381427\n ],\n [\n -168.48632812499997,\n 62.3903694381427\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Dr
Anchorage, Alaska 99508-4560
http://alaska.usgs.gov
High-latitude regions are experiencing rapid and extensive changes in ecosystem composition and function as the result of increases in average air temperature. Increasing air temperatures have led to widespread thawing and degradation of permafrost, which in turn has affected ecosystems, socioeconomics, and the carbon cycle of high latitudes. Here we overcome complex interactions among surface and subsurface conditions to map nearsurface permafrost through decision and regression tree approaches that statistically and spatially extend field observations using remotely sensed imagery, climatic data, and thematic maps of a wide range of surface and subsurface biophysical characteristics. The data fusion approach generated medium-resolution (30-m pixels) maps of near-surface (within 1 m) permafrost, active-layer thickness, and associated uncertainty estimates throughout mainland Alaska. Our calibrated models (overall test accuracy of ~85%) were used to quantify changes in permafrost distribution under varying future climate scenarios assuming no other changes in biophysical factors. Models indicate that near-surface permafrost underlies 38% of mainland Alaska and that near-surface permafrost will disappear on 16 to 24% of the landscape by the end of the 21st Century. Simulations suggest that near-surface permafrost degradation is more probable in central regions of Alaska than more northerly regions. Taken together, these results have obvious implications for potential remobilization of frozen soil carbon pools under warmer temperatures. Additionally, warmer and drier conditions may increase fire activity and severity, which may exacerbate rates of permafrost thaw and carbon remobilization relative to climate alone. The mapping of permafrost distribution across Alaska is important for land-use planning, environmental assessments, and a wide-array of geophysical studies.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.rse.2015.07.019","usgsCitation":"Pastick, N.J., Jorgenson, M., Wylie, B.K., Nield, S.J., Johnson, K.D., and Finley, A., 2015, Distribution of near-surface permafrost in Alaska: estimates of present and future conditions: Remote Sensing of Environment, v. 168, p. 301-315, https://doi.org/10.1016/j.rse.2015.07.019.","productDescription":"15 p.","startPage":"301","endPage":"315","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066157","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":471892,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2015.07.019","text":"Publisher Index Page"},{"id":306428,"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 -140.9326171875,\n 69.7485511291223\n ],\n [\n -142.9541015625,\n 70.1403642720717\n ],\n [\n -156.6650390625,\n 71.46912418989677\n ],\n [\n -162.2900390625,\n 70.42207856801004\n ],\n [\n -166.81640625,\n 69.06856318696033\n ],\n [\n -167.5634765625,\n 68.25311055665718\n ],\n [\n -168.662109375,\n 65.58572002329473\n ],\n [\n -166.3330078125,\n 60.65164736580915\n ],\n [\n -162.24609375,\n 58.309488840677645\n ],\n [\n -158.642578125,\n 57.89149735271031\n ],\n [\n -166.025390625,\n 54.80068486732233\n ],\n [\n -164.70703125,\n 53.80065082633023\n ],\n [\n -155.7421875,\n 57.040729838360875\n ],\n [\n -154.0283203125,\n 56.145549500679074\n ],\n [\n -151.1279296875,\n 57.7041472343419\n ],\n [\n -150.46875,\n 59.28833169203345\n ],\n [\n -145.5908203125,\n 60.08676274626006\n ],\n [\n -141.7236328125,\n 59.55659188568175\n ],\n [\n -137.5927734375,\n 58.0546319113729\n ],\n [\n -132.2314453125,\n 53.72271667491848\n ],\n [\n -129.0234375,\n 55.60317816902704\n ],\n [\n -135,\n 59.977005492196\n ],\n [\n -137.3291015625,\n 59.24341475839977\n ],\n [\n -138.8671875,\n 60.392147922518845\n ],\n [\n -140.888671875,\n 60.43554230669233\n ],\n [\n -140.9326171875,\n 69.7485511291223\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"168","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55c325a5e4b033ef52106a63","chorus":{"doi":"10.1016/j.rse.2015.07.019","url":"http://dx.doi.org/10.1016/j.rse.2015.07.019","publisher":"Elsevier BV","authors":"Pastick Neal J., Jorgenson M. Torre, Wylie Bruce K., Nield Shawn J., Johnson Kristofer D., Finley Andrew O.","journalName":"Remote Sensing of Environment","publicationDate":"10/2015"},"contributors":{"authors":[{"text":"Pastick, Neal J. 0000-0002-8169-3018 njpastick@usgs.gov","orcid":"https://orcid.org/0000-0002-8169-3018","contributorId":4785,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"njpastick@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":564959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jorgenson, M. Torre","contributorId":34848,"corporation":false,"usgs":true,"family":"Jorgenson","given":"M. Torre","affiliations":[],"preferred":false,"id":564960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":564961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nield, Shawn J.","contributorId":145680,"corporation":false,"usgs":false,"family":"Nield","given":"Shawn","email":"","middleInitial":"J.","affiliations":[{"id":16195,"text":"Natural Resource Conservation Service, U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":564962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Kristofer D.","contributorId":81027,"corporation":false,"usgs":true,"family":"Johnson","given":"Kristofer","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":564963,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Finley, Andrew O.","contributorId":70666,"corporation":false,"usgs":true,"family":"Finley","given":"Andrew O.","affiliations":[],"preferred":false,"id":564964,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}