Phytoplankton growth in the Gulf of Alaska (GoA) is limited by iron (Fe), yet Fe sources are poorly constrained. We examine the temporal and spatial distributions of Fe, and its sources in the GoA, based on data from three cruises carried out in 2010 from the Copper River (AK) mouth to beyond the shelf break. April data are the first to describe late winter Fe behavior before surface water nitrate depletion began. Sediment resuspension during winter and spring storms generated high “total dissolvable Fe” (TDFe) concentrations of ~1000 nmol kg−1 along the entire continental shelf, which decreased beyond the shelf break. In July, high TDFe concentrations were similar on the shelf, but more spatially variable, and driven by low‐salinity glacial meltwater. Conversely, dissolved Fe (DFe) concentrations in surface waters were far lower and more seasonally consistent, ranging from ~4 nmol kg−1 in nearshore waters to ~0.6–1.5 nmol kg−1seaward of the shelf break during April and July, despite dramatic depletion of nitrate over that period. The reasonably constant DFe concentrations are likely maintained during the year across the shelf by complexation by strong organic ligands, coupled with ample supply of labile particulate Fe. The April DFe data can be simulated using a simple numerical model that assumes a DFe flux from shelf sediments, horizontal transport by eddy diffusion, and removal by scavenging. Given how global change is altering many processes impacting the Fe cycle, additional studies are needed to examine controls on DFe in the Gulf of Alaska.
","language":"English","publisher":"Ameican Geophysical Union","doi":"10.1002/2016GB005493","usgsCitation":"Crusius, J., Schroth, A.W., Resing, J.A., Cullen, J., and Campbell, R.W., 2017, Seasonal and spatial variabilities in northern Gulf of Alaska surface water iron concentrations driven by shelf sediment resuspension, glacial meltwater, a Yakutat eddy, and dust: Global Biogeochemical Cycles, v. 31, no. 6, p. 942-960, https://doi.org/10.1002/2016GB005493.","productDescription":"19 p.","startPage":"942","endPage":"960","ipdsId":"IP-078971","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":469779,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gb005493","text":"Publisher Index Page"},{"id":438308,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7222S06","text":"USGS data release","linkHelpText":"Gulf of Alaska Shelf and Slope Iron and Nitrate data, Copper River Region, 2010"},{"id":356112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -147.5,\n 58\n ],\n [\n -143,\n 58\n ],\n [\n -143,\n 60.359564131824236\n ],\n [\n -147.5,\n 60.359564131824236\n ],\n [\n -147.5,\n 58\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-03","publicationStatus":"PW","scienceBaseUri":"5b6fc67ce4b0f5d57878eb84","contributors":{"authors":[{"text":"Crusius, John 0000-0003-2554-0831 jcrusius@usgs.gov","orcid":"https://orcid.org/0000-0003-2554-0831","contributorId":2155,"corporation":false,"usgs":true,"family":"Crusius","given":"John","email":"jcrusius@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":741299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schroth, Andrew W.","contributorId":192042,"corporation":false,"usgs":false,"family":"Schroth","given":"Andrew","email":"","middleInitial":"W.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":741300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Resing, Joseph A.","contributorId":206619,"corporation":false,"usgs":false,"family":"Resing","given":"Joseph","email":"","middleInitial":"A.","affiliations":[{"id":37351,"text":"University of Washington; Joint Institute for the Study of the Atmosphere and the Ocean","active":true,"usgs":false}],"preferred":false,"id":741301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cullen, Jay","contributorId":206620,"corporation":false,"usgs":false,"family":"Cullen","given":"Jay","email":"","affiliations":[{"id":37352,"text":"University of Victoria; School of Earth and Ocean Sciences Victoria, B.C.","active":true,"usgs":false}],"preferred":false,"id":741302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell, Robert W.","contributorId":206621,"corporation":false,"usgs":false,"family":"Campbell","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":37353,"text":"Prince William Sound Science Center, Cordova, AK","active":true,"usgs":false}],"preferred":false,"id":741303,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193291,"text":"70193291 - 2017 - Uncertainties in forecasting the response of polar bears to global climate change","interactions":[],"lastModifiedDate":"2021-04-26T15:04:42.409319","indexId":"70193291","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Uncertainties in forecasting the response of polar bears to global climate change","docAbstract":"Several sources of uncertainty affect how precisely the future status of polar bears (Ursus maritimus) can be forecasted. Foremost are unknowns about the future levels of global greenhouse gas emissions, which could range from an unabated increase to an aggressively mitigated reduction. Uncertainties also arise because different climate models project different amounts and rates of future warming (and sea ice loss)—even for the same emission scenario. There are also uncertainties about how global warming could affect the Arctic Ocean’s food web, so even if climate models project the presence of sea ice in the future, the availability of polar bear prey is not guaranteed. Under a worst-case emission scenario in which rates of greenhouse gas emissions continue to rise unabated to century’s end, the uncertainties about polar bear status center on a potential for extinction. If the species were to persist, it would likely be restricted to a high-latitude refugium in northern Canada and Greenland—assuming a food web also existed with enough accessible prey to fuel weight gains for surviving onshore during the most extreme years of summer ice melt. On the other hand, if emissions were to be aggressively mitigated at the levels proposed in the Paris Climate Agreement, healthy polar bear populations would probably continue to occupy all but the most southern areas of their contemporary summer range. While polar bears have survived previous warming phases—which indicate some resiliency to the loss of sea ice habitat—what is certain is that the present pace of warming is unprecedented and will increasingly expose polar bears to historically novel stressors.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Marine animal welfare","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-319-46994-2_25","usgsCitation":"Douglas, D.C., and Atwood, T.C., 2017, Uncertainties in forecasting the response of polar bears to global climate change, chap. of Marine animal welfare, p. 463-473, https://doi.org/10.1007/978-3-319-46994-2_25.","productDescription":"11 p.","startPage":"463","endPage":"473","ipdsId":"IP-076001","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":349594,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-20","publicationStatus":"PW","scienceBaseUri":"5a60fbbde4b06e28e9c23530","contributors":{"editors":[{"text":"Butterworth, Andy","contributorId":45100,"corporation":false,"usgs":false,"family":"Butterworth","given":"Andy","email":"","affiliations":[],"preferred":false,"id":724155,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":718566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":718567,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193122,"text":"70193122 - 2017 - Ecological change drives a decline in mercury concentrations in southern Beaufort Sea polar bears","interactions":[],"lastModifiedDate":"2017-11-01T16:48:55","indexId":"70193122","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Ecological change drives a decline in mercury concentrations in southern Beaufort Sea polar bears","docAbstract":"We evaluated total mercury (THg) concentrations and trends in polar bears from the southern Beaufort Sea subpopulation from 2004 to 2011. Hair THg concentrations ranged widely among individuals from 0.6 to 13.3 μg g–1 dry weight (mean: 3.5 ± 0.2 μg g–1). Concentrations differed among sex and age classes: solitary adult females ≈ adult females with cubs ≈ subadults > adult males ≈ yearlings > cubs-of-the-year ≈ 2 year old dependent cubs. No variation was observed between spring and fall samples. For spring-sampled adults, THg concentrations declined by 13% per year, contrasting recent trends observed for other Western Hemispheric Arctic biota. Concentrations also declined by 15% per year considering adult males only, while a slower, nonsignificant decrease of 4.4% per year was found for adult females. Lower THg concentrations were associated with higher body mass index (BMI) and higher proportions of lower trophic position food resources consumed. Because BMI and diet were related, and the relationship to THg was strongest for BMI, trends were re-evaluated adjusting for BMI as the covariate. The adjusted annual decline was not significant. These findings indicate that changes in foraging ecology, not declining environmental concentrations of mercury, are driving short-term declines in THg concentrations in southern Beaufort Sea polar bears.
","language":"English","publisher":"ACS Publishing","doi":"10.1021/acs.est.7b00812","usgsCitation":"McKinney, M.A., Atwood, T.C., Pedro, S., and Peacock, E.L., 2017, Ecological change drives a decline in mercury concentrations in southern Beaufort Sea polar bears: Environmental Science & Technology, v. 51, no. 14, p. 7814-7822, https://doi.org/10.1021/acs.est.7b00812.","productDescription":"9 p.","startPage":"7814","endPage":"7822","ipdsId":"IP-084265","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":469786,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.7b00812","text":"Publisher Index Page"},{"id":438309,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70Z71H2","text":"USGS data release","linkHelpText":"Polar Bear Hair Mercury Concentrations Southern Beaufort Sea 2004-2011"},{"id":348057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea","volume":"51","issue":"14","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-14","publicationStatus":"PW","scienceBaseUri":"59fadd22e4b0531197b13c97","contributors":{"authors":[{"text":"McKinney, Melissa A.","contributorId":11496,"corporation":false,"usgs":false,"family":"McKinney","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":6619,"text":"University of Connecticutt","active":true,"usgs":false}],"preferred":false,"id":718056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":718055,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pedro, Sara","contributorId":199068,"corporation":false,"usgs":false,"family":"Pedro","given":"Sara","email":"","affiliations":[],"preferred":false,"id":718057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peacock, Elizabeth L. 0000-0001-7279-0329 lpeacock@usgs.gov","orcid":"https://orcid.org/0000-0001-7279-0329","contributorId":3361,"corporation":false,"usgs":true,"family":"Peacock","given":"Elizabeth","email":"lpeacock@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":false,"id":718058,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192634,"text":"70192634 - 2017 - Reflected stochastic differential equation models for constrained animal movement","interactions":[],"lastModifiedDate":"2018-02-14T14:17:57","indexId":"70192634","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2151,"text":"Journal of Agricultural, Biological, and Environmental Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Reflected stochastic differential equation models for constrained animal movement","docAbstract":"Movement for many animal species is constrained in space by barriers such as rivers, shorelines, or impassable cliffs. We develop an approach for modeling animal movement constrained in space by considering a class of constrained stochastic processes, reflected stochastic differential equations. Our approach generalizes existing methods for modeling unconstrained animal movement. We present methods for simulation and inference based on augmenting the constrained movement path with a latent unconstrained path and illustrate this augmentation with a simulation example and an analysis of telemetry data from a Steller sea lion (Eumatopias jubatus) in southeast Alaska.
","language":"English","publisher":"Springer","doi":"10.1101/152017","usgsCitation":"Hanks, E.M., Johnson, D., and Hooten, M., 2017, Reflected stochastic differential equation models for constrained animal movement: Journal of Agricultural, Biological, and Environmental Statistics, v. 22, no. 3, p. 353-372, https://doi.org/10.1101/152017.","productDescription":"20 p.","startPage":"353","endPage":"372","ipdsId":"IP-083237","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469797,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/152017","text":"External Repository"},{"id":348557,"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 -136.6259765625,\n 55.75803176823725\n ],\n [\n -132.82470703125,\n 55.75803176823725\n ],\n [\n -132.82470703125,\n 58.228596132481435\n ],\n [\n -136.6259765625,\n 58.228596132481435\n ],\n [\n -136.6259765625,\n 55.75803176823725\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a06c8cce4b09af898c8611d","contributors":{"authors":[{"text":"Hanks, Ephraim M.","contributorId":178093,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":47524,"corporation":false,"usgs":true,"family":"Johnson","given":"Devin S.","affiliations":[],"preferred":false,"id":721544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":716606,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192735,"text":"70192735 - 2017 - A decade of boreal rich fen greenhouse gas fluxes in response to natural and experimental water table variability","interactions":[],"lastModifiedDate":"2017-11-08T13:06:03","indexId":"70192735","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"A decade of boreal rich fen greenhouse gas fluxes in response to natural and experimental water table variability","docAbstract":"Rich fens are common boreal ecosystems with distinct hydrology, biogeochemistry and ecology that influence their carbon (C) balance. We present growing season soil chamber methane emission (FCH4), ecosystem respiration (ER), net ecosystem exchange (NEE) and gross primary production (GPP) fluxes from a 9-years water table manipulation experiment in an Alaskan rich fen. The study included major flood and drought years, where wetting and drying treatments further modified the severity of droughts. Results support previous findings from peatlands that drought causes reduced magnitude of growing season FCH4, GPP and NEE, thus reducing or reversing their C sink function. Experimentally exacerbated droughts further reduced the capacity for the fen to act as a C sink by causing shifts in vegetation and thus reducing magnitude of maximum growing season GPP in subsequent flood years by ~15% compared to control plots. Conversely, water table position had only a weak influence on ER, but dominant contribution to ER switched from autotrophic respiration in wet years to heterotrophic in dry years. Droughts did not cause inter-annual lag effects on ER in this rich fen, as has been observed in several nutrient-poor peatlands. While ER was dependent on soil temperatures at 2 cm depth, FCH4 was linked to soil temperatures at 25 cm. Inter-annual variability of deep soil temperatures was in turn dependent on wetness rather than air temperature, and higher FCH4 in flooded years was thus equally due to increased methane production at depth and decreased methane oxidation near the surface. Short-term fluctuations in wetness caused significant lag effects on FCH4, but droughts caused no inter-annual lag effects on FCH4. Our results show that frequency and severity of droughts and floods can have characteristic effects on the exchange of greenhouse gases, and emphasize the need to project future hydrological regimes in rich fens.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13612","usgsCitation":"Olefeldt, D., Euskirchen, E., Harden, J.W., Kane, E.S., McGuire, A.D., Waldrop, M.P., and Turetsky, M.R., 2017, A decade of boreal rich fen greenhouse gas fluxes in response to natural and experimental water table variability: Global Change Biology, v. 23, no. 6, p. 2428-2440, https://doi.org/10.1111/gcb.13612.","productDescription":"13 p.","startPage":"2428","endPage":"2440","ipdsId":"IP-075210","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-31","publicationStatus":"PW","scienceBaseUri":"5a0425b8e4b0dc0b45b45367","contributors":{"authors":[{"text":"Olefeldt, David","contributorId":169408,"corporation":false,"usgs":false,"family":"Olefeldt","given":"David","affiliations":[{"id":32365,"text":"Department of Renewable Resources, University of Alberta","active":true,"usgs":false}],"preferred":false,"id":721161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Euskirchen, Eugénie S.","contributorId":83378,"corporation":false,"usgs":false,"family":"Euskirchen","given":"Eugénie S.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":721162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":721163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kane, Evan S.","contributorId":11903,"corporation":false,"usgs":true,"family":"Kane","given":"Evan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":721164,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waldrop, Mark P. 0000-0003-1829-7140 mwaldrop@usgs.gov","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":1599,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","email":"mwaldrop@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":721165,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Turetsky, Merritt R.","contributorId":169398,"corporation":false,"usgs":false,"family":"Turetsky","given":"Merritt","email":"","middleInitial":"R.","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":721166,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192992,"text":"70192992 - 2017 - A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011","interactions":[],"lastModifiedDate":"2018-03-08T13:03:59","indexId":"70192992","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011","docAbstract":"Monitoring and mapping land cover changes are important ways to support evaluation of the status and transition of ecosystems. The Alaska National Land Cover Database (NLCD) 2001 was the first 30-m resolution baseline land cover product of the entire state derived from circa 2001 Landsat imagery and geospatial ancillary data. We developed a comprehensive approach named AKUP11 to update Alaska NLCD from 2001 to 2011 and provide a 10-year cyclical update of the state's land cover and land cover changes. Our method is designed to characterize the main land cover changes associated with different drivers, including the conversion of forests to shrub and grassland primarily as a result of wildland fire and forest harvest, the vegetation successional processes after disturbance, and changes of surface water extent and glacier ice/snow associated with weather and climate changes. For natural vegetated areas, a component named AKUP11-VEG was developed for updating the land cover that involves four major steps: 1) identify the disturbed and successional areas using Landsat images and ancillary datasets; 2) update the land cover status for these areas using a SKILL model (System of Knowledge-based Integrated-trajectory Land cover Labeling); 3) perform decision tree classification; and 4) develop a final land cover and land cover change product through the postprocessing modeling. For water and ice/snow areas, another component named AKUP11-WIS was developed for initial land cover change detection, removal of the terrain shadow effects, and exclusion of ephemeral snow changes using a 3-year MODIS snow extent dataset from 2010 to 2012. The overall approach was tested in three pilot study areas in Alaska, with each area consisting of four Landsat image footprints. The results from the pilot study show that the overall accuracy in detecting change and no-change is 90% and the overall accuracy of the updated land cover label for 2011 is 86%. The method provided a robust, consistent, and efficient means for capturing major disturbance events and updating land cover for Alaska. The method has subsequently been applied to generate the land cover and land cover change products for the entire state of Alaska.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2017.04.021","usgsCitation":"Jin, S., Yang, L., Zhu, Z., and Homer, C.G., 2017, A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011: Remote Sensing of Environment, v. 195, p. 44-55, https://doi.org/10.1016/j.rse.2017.04.021.","productDescription":"12 p.","startPage":"44","endPage":"55","ipdsId":"IP-082390","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":347728,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"195","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f83a36e4b063d5d30980dc","contributors":{"authors":[{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","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}],"preferred":true,"id":717548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Limin 0000-0002-2843-6944 lyang@usgs.gov","orcid":"https://orcid.org/0000-0002-2843-6944","contributorId":4305,"corporation":false,"usgs":true,"family":"Yang","given":"Limin","email":"lyang@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhu, Zhe 0000-0001-8283-6407 zhezhu@usgs.gov","orcid":"https://orcid.org/0000-0001-8283-6407","contributorId":168792,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhe","email":"zhezhu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","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":717549,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193287,"text":"70193287 - 2017 - Seasonal movements of the Short-eared Owl (Asio flammeus) in western North America as revealed by satellite telemetry","interactions":[],"lastModifiedDate":"2017-11-01T16:38:03","indexId":"70193287","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Seasonal movements of the Short-eared Owl (Asio flammeus) in western North America as revealed by satellite telemetry","title":"Seasonal movements of the Short-eared Owl (Asio flammeus) in western North America as revealed by satellite telemetry","docAbstract":"The Short-eared Owl (Asio flammeus) is a widespread raptor whose abundance and distribution fluctuates in response to the varying amplitudes of its prey, which are predominately microtines. Previous efforts to describe the seasonal movements of Short-eared Owls have been hindered by few band recoveries and the species' cryptic and irruptive behavior. We attached satellite transmitters to adult Short-eared Owls at breeding areas in western and interior Alaska in June 2009 and July 2010, and tracked their movements for up to 19 mo. Owls initiated long-distance southward movements from Alaska and most followed a corridor east of the Rocky Mountains into the Prairie provinces and Great Plains states. Four owls followed a coastal route west of the Rocky Mountains, including one owl that crossed the Gulf of Alaska. Completed autumn migration distances ranged from 3205–6886 km (mean = 4722 ± 1156 km [SD]). Wintering areas spanned 21° of latitude from central Montana to southern Texas, and 24° of longitude from central California to western Kansas. Subsequent seasonal migrations were generally northward in spring and southward in autumn; these movements were comparatively short-distance (mean = 767.5 ± 517.4 km [SD]) and the owls exhibited low site fidelity. The Short-eared Owls we tracked from two relatively local breeding areas in Alaska used a patchwork of diverse open habitats across a large area of North America, which highlights that effective conservation of this species requires a collaborative, continental-scale focus.
","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-15-81.1","usgsCitation":"Johnson, J.A., Booms, T.L., DeCicco, L.H., and Douglas, D.C., 2017, Seasonal movements of the Short-eared Owl (Asio flammeus) in western North America as revealed by satellite telemetry: Journal of Raptor Research, v. 51, no. 2, p. 115-128, https://doi.org/10.3356/JRR-15-81.1.","productDescription":"14 p.","startPage":"115","endPage":"128","ipdsId":"IP-064603","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":461523,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr-15-81.1","text":"Publisher Index Page"},{"id":348053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fadd22e4b0531197b13c93","contributors":{"authors":[{"text":"Johnson, James A.","contributorId":199284,"corporation":false,"usgs":false,"family":"Johnson","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":718552,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Booms, Travis L.","contributorId":199285,"corporation":false,"usgs":false,"family":"Booms","given":"Travis","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":718553,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeCicco, Lucas H.","contributorId":199286,"corporation":false,"usgs":false,"family":"DeCicco","given":"Lucas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":718554,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":718551,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187849,"text":"gip177 - 2017 - Sculpted by water, elevated by earthquakes—The coastal landscape of Glacier Bay National Park, Alaska","interactions":[],"lastModifiedDate":"2017-05-22T16:54:29","indexId":"gip177","displayToPublicDate":"2017-05-22T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"177","title":"Sculpted by water, elevated by earthquakes—The coastal landscape of Glacier Bay National Park, Alaska","docAbstract":"Within Glacier Bay National Park in southeastern Alaska, the Fairweather Fault represents the onshore boundary between two of Earth’s constantly moving tectonic plates: the North American Plate and the Yakutat microplate. Satellite measurements indicate that during the past few decades the Yakutat microplate has moved northwest at a rate of nearly 5 centimeters per year relative to the North American Plate. Motion between the tectonic plates results in earthquakes on the Fairweather Fault during time intervals spanning one or more centuries. For example, in 1958, a 260-kilometer section of the Fairweather Fault ruptured during a magnitude 7.8 earthquake, causing permanent horizontal (as much as 6.5 meters) and vertical (as much as 1 meter) displacement of the ground surface across the fault. Thousands to millions of years of tectonic plate motion, including earthquakes like the one in 1958, raised and shifted the ground surface across the Fairweather Fault, while rivers, glaciers, and ocean waves eroded and sculpted the surrounding landscape along the Gulf of Alaska coast in Glacier Bay National Park.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip177","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory and the National Center for Airborne Laser Mapping","usgsCitation":"Witter, R.C., LeWinter, A., Bender, A., Glennie, C., and Finnegan, D., 2017, Sculpted by water, elevated by earthquakes—The coastal landscape of Glacier Bay National Park, Alaska: U.S. Geological Survey General Information Product 177, https://doi.org/10.3133/gip177.","productDescription":"Poster: 50.04 x 40.68 inches","onlineOnly":"Y","ipdsId":"IP-082030","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":438337,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7W094D4","text":"USGS data release","linkHelpText":"Digital Elevation Models of Glacier Bay National Park, Between Lituya Bay and Icy Point, Alaska, Derived from Airborne Lidar Data Acquired in September 2015"},{"id":341543,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/177/coverthb.jpg"},{"id":341544,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/177/gip177.pdf","text":"Report","size":"16.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 177"}],"country":"United States","state":"Alaska","otherGeospatial":"Glacial Bay National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -137.97454833984375,\n 58.21413156442685\n ],\n [\n -135.966796875,\n 58.21413156442685\n ],\n [\n -135.966796875,\n 58.9202457956557\n ],\n [\n -137.97454833984375,\n 58.9202457956557\n ],\n [\n -137.97454833984375,\n 58.21413156442685\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Science Center
Alaska Mineral Resources
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
Density-dependent (DD) and density-independent (DI) habitat selection is strongly linked to a species’ evolutionary history. Determining the relative importance of each is necessary because declining populations are not always the result of altered DI mechanisms but can often be the result of DD via a reduced carrying capacity. We developed spatially and temporally explicit models throughout the Chena River, Alaska to predict important DI mechanisms that influence Chinook salmon spawning success. We used resource-selection functions to predict suitable spawning habitat based on geomorphic characteristics, a semi-distributed water-and-energy balance hydrologic model to generate stream flow metrics, and modeled stream temperature as a function of climatic variables. Spawner counts were predicted throughout the core and periphery spawning sections of the Chena River from escapement estimates (DD) and DI variables. Additionally, we used isodar analysis to identify whether spawners actively defend spawning habitat or follow an ideal free distribution along the riverscape. Aerial counts were best explained by escapement and reference to the core or periphery, while no models with DI variables were supported in the candidate set. Furthermore, isodar plots indicated habitat selection was best explained by ideal free distributions, although there was strong evidence for active defense of core spawning habitat. Our results are surprising, given salmon commonly defend spawning resources, and are likely due to competition occurring at finer spatial scales than addressed in this study.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0177467","usgsCitation":"Huntsman, B.M., Falke, J.A., Savereide, J.W., and Bennett, K.E., 2017, The role of density-dependent and –independent processes in spawning habitat selection by salmon in an Arctic riverscape: PLoS ONE, v. 12, no. 5, p. 1-21, https://doi.org/10.1371/journal.pone.0177467.","productDescription":"e0177467; 21 p.","startPage":"1","endPage":"21","ipdsId":"IP-077611","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":461565,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0177467","text":"Publisher Index Page"},{"id":353885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chena River Basin","volume":"12","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-22","publicationStatus":"PW","scienceBaseUri":"5afee879e4b0da30c1bfc457","contributors":{"authors":[{"text":"Huntsman, Brock M. 0000-0003-4090-1949","orcid":"https://orcid.org/0000-0003-4090-1949","contributorId":166748,"corporation":false,"usgs":false,"family":"Huntsman","given":"Brock","email":"","middleInitial":"M.","affiliations":[{"id":24497,"text":"West Virginia University, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":734441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":734396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Savereide, James W.","contributorId":204591,"corporation":false,"usgs":false,"family":"Savereide","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":734442,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bennett, Katrina E.","contributorId":204592,"corporation":false,"usgs":false,"family":"Bennett","given":"Katrina","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":734443,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187710,"text":"70187710 - 2017 - Habitat degradation affects the summer activity of polar bears","interactions":[],"lastModifiedDate":"2018-04-21T13:18:43","indexId":"70187710","displayToPublicDate":"2017-05-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Habitat degradation affects the summer activity of polar bears","docAbstract":"Understanding behavioral responses of species to environmental change is critical to forecasting population-level effects. Although climate change is significantly impacting species’ distributions, few studies have examined associated changes in behavior. Polar bear (Ursus maritimus) subpopulations have varied in their near-term responses to sea ice decline. We examined behavioral responses of two adjacent subpopulations to changes in habitat availability during the annual sea ice minimum using activity data. Location and activity sensor data collected from 1989 to 2014 for 202 adult female polar bears in the Southern Beaufort Sea (SB) and Chukchi Sea (CS) subpopulations were used to compare activity in three habitat types varying in prey availability: (1) land; (2) ice over shallow, biologically productive waters; and (3) ice over deeper, less productive waters. Bears varied activity across and within habitats with the highest activity at 50–75% sea ice concentration over shallow waters. On land, SB bears exhibited variable but relatively high activity associated with the use of subsistence-harvested bowhead whale carcasses, whereas CS bears exhibited low activity consistent with minimal feeding. Both subpopulations had fewer observations in their preferred shallow-water sea ice habitats in recent years, corresponding with declines in availability of this substrate. The substantially higher use of marginal habitats by SB bears is an additional mechanism potentially explaining why this subpopulation has experienced negative effects of sea ice loss compared to the still-productive CS subpopulation. Variability in activity among, and within, habitats suggests that bears alter their behavior in response to habitat conditions, presumably in an attempt to balance prey availability with energy costs.
","language":"English","publisher":"Springer","doi":"10.1007/s00442-017-3839-y","usgsCitation":"Ware, J.V., Rode, K.D., Bromaghin, J.F., Douglas, D.C., Wilson, R.H., Regehr, E.V., Amstrup, S.C., Durner, G.M., Pagano, A.M., Olson, J., Robbins, C.T., and Jansen, H.T., 2017, Habitat degradation affects the summer activity of polar bears: Oecologia, v. 184, no. 1, p. 87-99, https://doi.org/10.1007/s00442-017-3839-y.","productDescription":"13 p.","startPage":"87","endPage":"99","ipdsId":"IP-073535","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":438339,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7B27SCH","text":"USGS data release","linkHelpText":"Summer Activity Sensor Data from Collars Deployed on Female Polar Bears in the Chukchi Sea 1989 to 1995 and Southern Beaufort Sea 1989 to 2014"},{"id":341342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Chukchi Sea, Southern Beaufort Sea","volume":"184","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-28","publicationStatus":"PW","scienceBaseUri":"591c0fc8e4b0a7fdb43ddeea","contributors":{"authors":[{"text":"Ware, Jasmine V.","contributorId":192039,"corporation":false,"usgs":false,"family":"Ware","given":"Jasmine","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":695205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","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":695204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","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":695206,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":695207,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":695208,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Regehr, Eric V. 0000-0003-4487-3105","orcid":"https://orcid.org/0000-0003-4487-3105","contributorId":66364,"corporation":false,"usgs":false,"family":"Regehr","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":695209,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Amstrup, Steven C.","contributorId":67034,"corporation":false,"usgs":false,"family":"Amstrup","given":"Steven","email":"","middleInitial":"C.","affiliations":[{"id":13182,"text":"Polar Bears International","active":true,"usgs":false}],"preferred":false,"id":695210,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","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":695211,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":695212,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Olson, Jay","contributorId":150116,"corporation":false,"usgs":false,"family":"Olson","given":"Jay","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":695213,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Robbins, Charles T.","contributorId":124585,"corporation":false,"usgs":false,"family":"Robbins","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5127,"text":"Washington State University, P.O. Box 644236, Pullman, WA 99164","active":true,"usgs":false}],"preferred":false,"id":695214,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jansen, Heiko T","contributorId":192040,"corporation":false,"usgs":false,"family":"Jansen","given":"Heiko","email":"","middleInitial":"T","affiliations":[],"preferred":false,"id":695215,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70187713,"text":"70187713 - 2017 - Performance and retention of lightweight satellite radio tags applied to the ears of polar bears (Ursus maritimus)","interactions":[],"lastModifiedDate":"2017-05-16T11:02:37","indexId":"70187713","displayToPublicDate":"2017-05-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Performance and retention of lightweight satellite radio tags applied to the ears of polar bears (Ursus maritimus)","docAbstract":"Background
Satellite telemetry studies provide information that is critical to the conservation and management of species affected by ecological change. Here we report on the performance and retention of two types (SPOT-227 and SPOT-305A) of ear-mounted Argos-linked satellite transmitters (i.e., platform transmitter terminal, or PTT) deployed on free-ranging polar bears in Eastern Greenland, Baffin Bay, Kane Basin, the southern Beaufort Sea, and the Chukchi Sea during 2007–2013.
Results
Transmissions from 142 out of 145 PTTs deployed on polar bears were received for an average of 69.3 days. The average functional longevity, defined as the number of days they transmitted while still attached to polar bears, for SPOT-227 was 56.8 days and for SPOT-305A was 48.6 days. Thirty-four of the 142 (24%) PTTs showed signs of being detached before they stopped transmitting, indicating that tag loss was an important aspect of tag failure. Furthermore, 10 of 26 (38%) bears that were re-observed following application of a PTT had a split ear pinna, suggesting that some transmitters were detached by force. All six PTTs that were still on bears upon recapture had lost the antenna, which indicates that antenna breakage was a significant contributor to PTT failure. Finally, only nine of the 142 (6%) PTTs—three of which were still attached to bears—had a final voltage reading close to the value indicating battery exhaustion. This suggests that battery exhaustion was not a major factor in tag performance.
Conclusions
The average functional longevity of approximately 2 months for ear-mounted PTTs (this study) is poor compared to PTT collars fitted to adult female polar bears, which can last for several years. Early failure of the ear-mounted PTTs appeared to be caused primarily by detachment from the ear or antenna breakage. We suggest that much smaller and lighter ear-mounted transmitters are necessary to reduce the risk of tissue irritation, tissue damage, and tag detachment, and with a more robust antenna design. Our results are applicable to other tag types (e.g., iridium and VHF systems) and to research on other large mammals that cannot wear radio collars.
Rationale
The use of stable isotopes for dietary estimates of wildlife assumes that there are consistent differences in isotopic ratios among diet items, and that the differences in these ratios between the diet item and the animal tissues (i.e., fractionation) are predictable. However, variation in isotopic ratios and fractionation of δ13C and δ15N values among locations, seasons, and forages are poorly described for arctic herbivores especially migratory species such as caribou (Rangifer tarandus).
Methods
We measured the δ13C and δ15N values of seven species of forage growing along a 200-km transect through the range of the Central Arctic caribou herd on the North Slope of Alaska over 2 years. We compared forages available at the beginning (May; n = 175) and the end (n = 157) of the growing season (September). Purified enzymes were used to measure N digestibility and to assess isotopic fractionation in response to nutrient digestibility during simulated digestion.
Results
Values for δ13C declined by 1.38 ‰ with increasing latitude across the transect, and increased by 0.44 ‰ from the beginning to the end of the season. The range of values for δ15N was greater than that for δ13C (13.29 vs 5.60 ‰). Differences in values for δ13C between graminoids (Eriophorum and Carex spp.) and shrubs (Betula and Salix spp.) were small but δ15N values distinguished graminoids (1.87 ± 1.02 ‰) from shrubs (−2.87 ± 2.93 ‰) consistently across season and latitude. However, undigested residues of forages were enriched in 15N when the digestibility of N was less than 0.67.
Conclusions
Although δ15N values can distinguish plant groups in the diet of arctic herbivores, variation in the digestibility of dietary items may need to be considered in applying fractionation values for 15N to caribou and other herbivores that select highly digestible items (e.g. forbs) as well as heavily defended plants (e.g. woody browse).
","language":"English","publisher":"Wiley","doi":"10.1002/rcm.7849","usgsCitation":"Vansomeren, L.L., Barboza, P.S., Gustine, D.D., and Bret-Harte, M., 2017, Variation in δ15N and δ13C values of forages for Arctic caribou: Effects of location, phenology and simulated digestion: Rapid Communications in Mass Spectrometry, v. 31, no. 9, p. 813-820, https://doi.org/10.1002/rcm.7849.","productDescription":"8 p.","startPage":"813","endPage":"820","ipdsId":"IP-065040","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":349861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"North Slope","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.0205078125,\n 69.61120561869633\n ],\n [\n -143.701171875,\n 70.31873847853124\n ],\n [\n -148.6669921875,\n 70.55417853776078\n ],\n [\n -151.5234375,\n 70.94535555009823\n ],\n [\n -156.796875,\n 71.48308562053703\n ],\n [\n -159.7412109375,\n 70.94535555009823\n ],\n [\n -162.421875,\n 70.34831755984779\n ],\n [\n -164.53125,\n 69.25614923150721\n ],\n [\n -166.376953125,\n 69.08425705053145\n ],\n [\n -166.728515625,\n 68.38299634059615\n ],\n [\n -166.1572265625,\n 68.2042121888185\n ],\n [\n -162.68554687499997,\n 68.35059429645612\n ],\n [\n -153.369140625,\n 68.39918004344189\n ],\n [\n -146.9970703125,\n 69.30279408245205\n ],\n [\n -141.0205078125,\n 69.61120561869633\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-04","publicationStatus":"PW","scienceBaseUri":"5a60fbc9e4b06e28e9c23672","contributors":{"authors":[{"text":"Vansomeren, Lindsey L.","contributorId":167723,"corporation":false,"usgs":false,"family":"Vansomeren","given":"Lindsey","email":"","middleInitial":"L.","affiliations":[{"id":24816,"text":"Department of Biology and Wildlife, University of Alaska Fairbanks, Fairbanks, AK","active":true,"usgs":false}],"preferred":false,"id":724650,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barboza, Perry S.","contributorId":36454,"corporation":false,"usgs":false,"family":"Barboza","given":"Perry","email":"","middleInitial":"S.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":724651,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gustine, David D. dgustine@usgs.gov","contributorId":3776,"corporation":false,"usgs":true,"family":"Gustine","given":"David","email":"dgustine@usgs.gov","middleInitial":"D.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":724649,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bret-Harte, M. 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Assigning behaviors to accelerometer data often involves the use of captive animals or surrogate species, as their accelerometer signatures are generally assumed to be similar to those of their wild counterparts. However, this has rarely been tested. Validated accelerometer data are needed for polar bears Ursus maritimus to understand how habitat conditions may influence behavior and energy demands. We used accelerometer and water conductivity data to remotely distinguish 10 polar bear behaviors. We calibrated accelerometer and conductivity data collected from collars with behaviors observed from video-recorded captive polar bears and brown bears U. arctos, and with video from camera collars deployed on free-ranging polar bears on sea ice and on land. We used random forest models to predict behaviors and found strong ability to discriminate the most common wild polar bear behaviors using a combination of accelerometer and conductivity sensor data from captive or wild polar bears. In contrast, models using data from captive brown bears failed to reliably distinguish most active behaviors in wild polar bears. Our ability to discriminate behavior was greatest when species- and habitat-specific data from wild individuals were used to train models. Data from captive individuals may be suitable for calibrating accelerometers, but may provide reduced ability to discriminate some behaviors. The accelerometer calibrations developed here provide a method to quantify polar bear behaviors to evaluate the impacts of declines in Arctic sea ice.
","language":"English","publisher":"Inter Research","doi":"10.3354/esr00779","usgsCitation":"Pagano, A.M., Rode, K.D., Cutting, A., Owen, M., Jensen, S., Ware, J., Robbins, C., Durner, G.M., Atwood, T.C., Obbard, M., Middel, K., Thiemann, G., and Williams, T., 2017, Using tri-axial accelerometers to identify wild polar bear behaviors: Endangered Species Research, v. 32, p. 19-33, https://doi.org/10.3354/esr00779.","productDescription":"15 p.","startPage":"19","endPage":"33","ipdsId":"IP-075328","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":469849,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00779","text":"Publisher Index 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Pullman","active":true,"usgs":false}],"preferred":false,"id":695226,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","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":695227,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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 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G.W.","contributorId":192051,"corporation":false,"usgs":false,"family":"Thiemann","given":"G.W.","affiliations":[{"id":27291,"text":"York University, Toronto, ON","active":true,"usgs":false}],"preferred":false,"id":695231,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Williams, T.M.","contributorId":192052,"corporation":false,"usgs":false,"family":"Williams","given":"T.M.","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":695232,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70187523,"text":"70187523 - 2017 - The relationship between female brooding and male nestling provisioning: does climate underlie geographic variation in sex roles?","interactions":[],"lastModifiedDate":"2017-05-08T11:30:44","indexId":"70187523","displayToPublicDate":"2017-05-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"The relationship between female brooding and male nestling provisioning: does climate underlie geographic variation in sex roles?","docAbstract":"Comparative studies of populations occupying different environments can provide insights into the ecological conditions affecting differences in parental strategies, including the relative contributions of males and females. Male and female parental strategies reflect the interplay between ecological conditions, the contributions of the social mate, and the needs of offspring. Climate is expected to underlie geographic variation in incubation and brooding behavior, and can thereby affect both the absolute and relative contributions of each sex to other aspects of parental care such as offspring provisioning. However, geographic variation in brooding behavior has received much less attention than variation in incubation attentiveness or provisioning rates. We compared parental behavior during the nestling period in populations of orange-crowned warblers Oreothlypis celata near the northern (64°N) and southern (33°N) boundaries of the breeding range. In Alaska, we found that males were responsible for the majority of food delivery whereas the sexes contributed equally to provisioning in California. Higher male provisioning in Alaska appeared to facilitate a higher proportion of time females spent brooding the nestlings. Surprisingly, differences in brooding between populations could not be explained by variation in ambient temperature, which was similar between populations during the nestling period. While these results represent a single population contrast, they suggest additional hypotheses for the ecological correlates and evolutionary drivers of geographic variation in brooding behavior, and the factors that shape the contributions of each sex.
","language":"English","publisher":"Wiley","doi":"10.1111/jav.00890","usgsCitation":"Yoon, J., Sofaer, H., Sillett, T., Morrison, S.A., and Ghalambor, C.K., 2017, The relationship between female brooding and male nestling provisioning: does climate underlie geographic variation in sex roles?: Journal of Avian Biology, v. 48, no. 2, p. 220-228, https://doi.org/10.1111/jav.00890.","productDescription":"9 p. ","startPage":"220","endPage":"228","ipdsId":"IP-070914","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":340920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"591183b3e4b0e541a03c1a58","contributors":{"authors":[{"text":"Yoon, Jongmin","contributorId":191808,"corporation":false,"usgs":false,"family":"Yoon","given":"Jongmin","email":"","affiliations":[],"preferred":false,"id":694316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sofaer, Helen 0000-0002-9450-5223 hsofaer@usgs.gov","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":169118,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"hsofaer@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":694315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sillett, T. Scott","contributorId":80788,"corporation":false,"usgs":false,"family":"Sillett","given":"T. Scott","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":694317,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morrison, Scott A.","contributorId":83780,"corporation":false,"usgs":false,"family":"Morrison","given":"Scott","email":"","middleInitial":"A.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":694318,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ghalambor, Cameron K.","contributorId":93722,"corporation":false,"usgs":false,"family":"Ghalambor","given":"Cameron","email":"","middleInitial":"K.","affiliations":[{"id":6998,"text":"Department of Biology, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":694319,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187355,"text":"ofr20171049 - 2017 - Eastern Denali Fault surface trace map, eastern Alaska and Yukon, Canada","interactions":[],"lastModifiedDate":"2023-11-03T16:52:08.991249","indexId":"ofr20171049","displayToPublicDate":"2017-05-04T00:00:00","publicationYear":"2017","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":"2017-1049","title":"Eastern Denali Fault surface trace map, eastern Alaska and Yukon, Canada","docAbstract":"We map the 385-kilometer (km) long surface trace of the right-lateral, strike-slip Denali Fault between the Totschunda-Denali Fault intersection in Alaska, United States and the village of Haines Junction, Yukon, Canada. In Alaska, digital elevation models based on light detection and ranging and interferometric synthetic aperture radar data enabled our fault mapping at scales of 1:2,000 and 1:10,000, respectively. Lacking such resources in Yukon, we developed new structure-from-motion digital photogrammetry products from legacy aerial photos to map the fault surface trace at a scale of 1:10,000 east of the international border. The section of the fault that we map, referred to as the Eastern Denali Fault, did not rupture during the 2002 Denali Fault earthquake (moment magnitude 7.9). Seismologic, geodetic, and geomorphic evidence, along with a paleoseismic record of past ground-rupturing earthquakes, demonstrate Holocene and contemporary activity on the fault, however. This map of the Eastern Denali Fault surface trace complements other data sets by providing an openly accessible digital interpretation of the location, length, and continuity of the fault’s surface trace based on the accompanying digital topography dataset. Additionally, the digitized fault trace may provide geometric constraints useful for modeling earthquake scenarios and related seismic hazard.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171049","usgsCitation":"Bender, A.M., and Haeussler, P.J., 2017, Eastern Denali Fault surface trace map, eastern Alaska and Yukon, Canada: U.S. Geological Survey Open-File Report 2017–1049, 10 p., https://doi.org/10.3133/ofr20171049.","productDescription":"iii, 10 p.","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-084514","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":438353,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7T151WC","text":"USGS data release","linkHelpText":"Eastern Denali Fault Surface Trace Map, Eastern Alaska and Adjacent Canada, 1978-2008"},{"id":422373,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_105646.htm","linkFileType":{"id":5,"text":"html"}},{"id":340824,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1049/coverthb.jpg"},{"id":340825,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1049/ofr20171049.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1049"}],"country":"Canada, United States","state":"Alaska, Yukon","otherGeospatial":"Denali Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -147,\n 60\n ],\n [\n -135,\n 60\n ],\n [\n -135,\n 64\n ],\n [\n -147,\n 64\n ],\n [\n -147,\n 60\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Science Center
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
This assessment was conducted to fulfill the requirements of section 712 of the Energy Independence and Security Act of 2007 and to improve understanding of factors influencing carbon balance in ecosystems of Hawai‘i. Ecosystem carbon storage, carbon fluxes, and carbon balance were examined for major terrestrial ecosystems on the seven main Hawaiian islands in two time periods: baseline (from 2007 through 2012) and future (projections from 2012 through 2061). The assessment incorporated observed data, remote sensing, statistical methods, and simulation models. The national assessment has been completed for the conterminous United States, using methodology described in SIR 2010-5233, with results provided in three regional reports (PP 1804, PP 1797, and PP 1897), and for Alaska, with results provided in PP 1826.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1834","usgsCitation":"Selmants, P.C., Giardina, C.P., Jacobi, J.D., and Zhu, Zhiliang, eds., 2017, Baseline and projected future carbon storage and carbon fluxes in ecosystems of Hawai‘i: U.S. Geological Survey Professional Paper 1834, 134 p., https://doi.org/10.3133/pp1834.","productDescription":"vii, 134 p.","numberOfPages":"146","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-077242","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":340802,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/pp1787","text":"Professional Paper 1787","linkHelpText":"- Baseline and projected future carbon storage and greenhouse-gas fluxes in the Great Plains Region of the United States"},{"id":340799,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/pp1826","text":"Professional Paper 1826","linkHelpText":"- Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of Alaska"},{"id":340797,"rank":13,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter8.pdf","text":"Chapter 8. Projected Future Carbon Storage and Carbon Fluxes in Terrestrial Ecosystems of Hawai‘i From Changes in Climate, Land Use, and Disturbance","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Benjamin M. Sleeter, Jinxun Liu, Colin J. Daniel, Todd J. Hawbaker, Tamara S. Wilson, Lucas B. Fortini, James D. Jacobi, Paul C. Selmants, Christian P. Giardina, Creighton M. Litton, and R. Flint Hughes"},{"id":340796,"rank":12,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter7.pdf","text":"Chapter 7. Baseline and Projected Future Aquatic Carbon Fluxes to Nearshore Waters in Hawai‘i","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Richard A. MacKenzie, Ayron M. Strauch, Tracy N. Wiegner, Steven L. Colbert, Edward G. Stets, and Robert G. Streigl"},{"id":340794,"rank":10,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter5.pdf","text":"Chapter 5. Wildland Fires and Greenhouse Gas Emissions in Hawai‘i","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Todd J. Hawbaker, Clay Trauernicht, Stephen M. Howard, Creighton M. Litton, Christian P. Giardina, James D. Jacobi, Lucas B. Fortini, R. Flint Hughes, Paul C. Selmants, and Zhiliang Zhu"},{"id":340791,"rank":7,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter2.pdf","text":"Chapter 2. Baseline Land Cover","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By James D. Jacobi, Jonathan P. Price, Lucas B. Fortini, Samuel M. Gon III, and Paul Berkowitz"},{"id":340821,"rank":5,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_executive_summary.pdf","text":"Executive Summary","size":"250 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Paul C. Selmants, Christian P. Giardina, James D. Jacobi, Lucas B. Fortini, R. Flint Hughes, Todd J. Hawbaker, Richard A. MacKenzie, Benjamin M. Sleeter, and Zhiliang Zhu"},{"id":340803,"rank":19,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20105233","text":"Scientific Investigations Report 2010-5233","linkHelpText":"- A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios"},{"id":340798,"rank":14,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter9.pdf","text":"Chapter 9. Hawai‘i Carbon Balance","size":"600 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Paul C. Selmants, Christian P. 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Selmants, Todd J. Hawbaker, James D. Jacobi, Christian P. Giardina, and Benjamin M. Sleeter"},{"id":340795,"rank":11,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter6.pdf","text":"Chapter 6. Baseline Carbon Storage and Carbon Fluxes in Terrestrial Ecosystems of Hawai‘i","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Paul C. Selmants, Christian P. Giardina, Sinan Sousan, David E. Knapp, Heather L. Kimball, Todd J. Hawbaker, Alvaro Moreno, Jami Seirer, Steve W. Running, Tomoaki Miura, Rafael Bergstrom, R. Flint Hughes, Creighton M. Litton, and Gregory P. Asner"},{"id":342057,"rank":20,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DB80B9","text":"Hawaii Land Cover and Habitat Status","linkHelpText":"(Chapter 2)"},{"id":340800,"rank":16,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/pp1804","text":"Professional Paper 1804","linkHelpText":"- Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of the Eastern United States"},{"id":340801,"rank":17,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/pp1797","text":"Professional Paper 1797","linkHelpText":"- Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of the Western United States"}],"country":"United 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\"}}]}","contact":"Land Change Science Program
U.S. Geological Survey
12201 Sunrise Valley Drive
MS 519A National Center
Reston, VA 20192
Burn area and the frequency of extreme fire events have been increasing during recent decades in North America, and this trend is expected to continue over the 21st century. While many aspects of the North American carbon budget have been intensively studied, the net contribution of fire disturbance to the overall net carbon flux at the continental scale remains uncertain. Based on national scale, spatially explicit and long-term fire data, along with the improved model parameterization in a process-based ecosystem model, we simulated the impact of fire disturbance on both direct carbon emissions and net terrestrial ecosystem carbon balance in North America. Fire-caused direct carbon emissions were 106.55 ± 15.98 Tg C/yr during 1990–2012; however, the net ecosystem carbon balance associated with fire was −26.09 ± 5.22 Tg C/yr, indicating that most of the emitted carbon was resequestered by the terrestrial ecosystem. Direct carbon emissions showed an increase in Alaska and Canada during 1990–2012 as compared to prior periods due to more extreme fire events, resulting in a large carbon source from these two regions. Among biomes, the largest carbon source was found to be from the boreal forest, primarily due to large reductions in soil organic matter during, and with slower recovery after, fire events. The interactions between fire and environmental factors reduced the fire-caused ecosystem carbon source. Fire disturbance only caused a weak carbon source as compared to the best estimate terrestrial carbon sink in North America owing to the long-term legacy effects of historical burn area coupled with fast ecosystem recovery during 1990–2012.
","language":"English","publisher":"AGU","doi":"10.1002/2016GB005548","usgsCitation":"Chen, G., Hayes, D.J., and McGuire, A.D., 2017, Contributions of wildland fire to terrestrial ecosystem carbon dynamics in North America from 1990 to 2012: Global Biogeochemical Cycles, v. 31, no. 5, p. 878-900, https://doi.org/10.1002/2016GB005548.","productDescription":"23 p.","startPage":"878","endPage":"900","ipdsId":"IP-084072","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469883,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gb005548","text":"Publisher Index Page"},{"id":348451,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","volume":"31","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-27","publicationStatus":"PW","scienceBaseUri":"5a0425b9e4b0dc0b45b45388","contributors":{"authors":[{"text":"Chen, Guangsheng","contributorId":200153,"corporation":false,"usgs":false,"family":"Chen","given":"Guangsheng","email":"","affiliations":[],"preferred":false,"id":721156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Daniel J.","contributorId":100237,"corporation":false,"usgs":true,"family":"Hayes","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721157,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716799,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192603,"text":"70192603 - 2017 - Magmatic degassing, lava dome extrusion, and explosions from Mount Cleveland volcano, Alaska, 2011–2015: Insight into the continuous nature of volcanic activity over multi-year timescales","interactions":[],"lastModifiedDate":"2017-10-31T16:46:52","indexId":"70192603","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Magmatic degassing, lava dome extrusion, and explosions from Mount Cleveland volcano, Alaska, 2011–2015: Insight into the continuous nature of volcanic activity over multi-year timescales","docAbstract":"Mount Cleveland volcano (1730 m) is one of the most active volcanoes in the Aleutian arc, Alaska, but heightened activity is rarely accompanied by geophysical signals, which makes interpretation of the activity difficult. In this study, we combine volcanic gas emissions measured for the first time in August 2015 with longer-term measurements of thermal output and lava extrusion rates between 2011 and 2015 calculated from MODIS satellite data with the aim to develop a better understanding of the nature of volcanic activity at Mount Cleveland. Degassing measurements were made in the month following two explosive events (21 July and 7 August 2015) and during a period of new dome growth in the summit crater. SO2 emission rates ranged from 400 to 860 t d− 1 and CO2/SO2 ratios were < 3, consistent with the presence of shallow magma in the conduit and the observed growth of a new lava dome. Thermal anomalies derived from MODIS data from 2011 to 2015 had an average repose time of only 4 days, pointing to the continuous nature of volcanic activity at this volcano. Rapid increases in the cumulative thermal output were often coincident with visual confirmation of dome growth or accumulations of tephra in the crater. The average rate of lava extrusion calculated for 9 periods of rapid increase in thermal output was 0.28 m3 s− 1, and the total volume extruded from 2011 to 2015 was 1.9–5.8 Mm3. The thermal output from the lava extrusion events only accounts for roughly half of the thermal budget, suggesting a continued presence of shallow magma in the upper conduit, likely driven by convection. Axisymmetric dome morphology and occasional drain back of lava into the conduit suggests low-viscosity magmas drive volcanism at Mount Cleveland. It follows also that only small overpressures can be maintained given the small domes and fluid magmas, which is consistent with the low explosivity of most of Mount Cleveland's eruptions. Changes between phases of dome growth and explosive activity are somewhat unpredictable and likely result from plugs that are related to the dome obtaining a critical dimension, or from small variations in the magma ascent rate that lead to crystallization-induced blockages in the upper conduit, thereby reducing the ability of magma to degas. We suggest the small magma volumes, slow ascent rates, and low magma viscosity lead to the overall lack of anomalous geophysical signals prior to eruptions, and that more continuous volcanic degassing measurements might lead to more successful eruption forecasting at this continuously-active open-vent volcano.
","language":"English","publisher":"Elsever","doi":"10.1016/j.jvolgeores.2017.03.001","usgsCitation":"Werner, C., Kern, C., Coppola, D., Lyons, J.J., Kelly, P.J., Wallace, K.L., Schneider, D.J., and Wessels, R., 2017, Magmatic degassing, lava dome extrusion, and explosions from Mount Cleveland volcano, Alaska, 2011–2015: Insight into the continuous nature of volcanic activity over multi-year timescales: Journal of Volcanology and Geothermal Research, v. 337, p. 98-110, https://doi.org/10.1016/j.jvolgeores.2017.03.001.","productDescription":"13 p.","startPage":"98","endPage":"110","ipdsId":"IP-081346","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469894,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://hdl.handle.net/2318/1652262","text":"Publisher Index Page"},{"id":347945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Mount Cleveland Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -171.650390625,\n 52.22443459871999\n ],\n [\n -166.57470703125,\n 52.22443459871999\n ],\n [\n -166.57470703125,\n 54.04971418210692\n ],\n [\n -171.650390625,\n 54.04971418210692\n ],\n [\n -171.650390625,\n 52.22443459871999\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"337","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f98bb7e4b0531197af9ff0","contributors":{"authors":[{"text":"Werner, Cynthia","contributorId":198599,"corporation":false,"usgs":false,"family":"Werner","given":"Cynthia","affiliations":[],"preferred":false,"id":716519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":716518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coppola, Diego","contributorId":190919,"corporation":false,"usgs":false,"family":"Coppola","given":"Diego","email":"","affiliations":[],"preferred":false,"id":716520,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":716521,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":716522,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wallace, Kristi L. 0000-0002-0962-048X kwallace@usgs.gov","orcid":"https://orcid.org/0000-0002-0962-048X","contributorId":3454,"corporation":false,"usgs":true,"family":"Wallace","given":"Kristi","email":"kwallace@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":716523,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schneider, David J. 0000-0001-9092-1054 djschneider@usgs.gov","orcid":"https://orcid.org/0000-0001-9092-1054","contributorId":198601,"corporation":false,"usgs":true,"family":"Schneider","given":"David","email":"djschneider@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":716524,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wessels, Rick 0000-0001-9711-6402 rwessels@usgs.gov","orcid":"https://orcid.org/0000-0001-9711-6402","contributorId":198602,"corporation":false,"usgs":true,"family":"Wessels","given":"Rick","email":"rwessels@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":716525,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70192920,"text":"70192920 - 2017 - Disturbance of a rare seabird by ship-based tourism in a marine protected area","interactions":[],"lastModifiedDate":"2017-11-07T13:32:06","indexId":"70192920","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Disturbance of a rare seabird by ship-based tourism in a marine protected area","docAbstract":"Managers of marine protected areas (MPAs) must often seek ways to allow for visitation while minimizing impacts to the resources they are intended to protect. Using shipboard observers, we quantified the “zone of disturbance” for Kittlitz’s and marbled murrelets (Brachyramphus brevirostris and B. marmoratus) exposed to large cruise ships traveling through Glacier Bay National Park, one of the largest MPAs in North America. In the upper reaches of Glacier Bay, where Kittlitz’s murrelets predominated, binary logistic regression models predicted that 61% of all murrelets within 850 m perpendicular distance of a cruise ship were disturbed (defined as flushing or diving), whereas in the lower reaches, where marbled murrelets predominated, this percentage increased to 72%. Using survival analysis, murrelets in both reaches were found to react at greater distances when ships approached indirectly, presumably because of the ship’s larger profile, suggesting murrelets responded to visual rather than audio cues. No management-relevant covariates (e.g., ship velocity, route distance from shore) were found to be important predictors of disturbance, as distance from ship to murrelet accounted for > 90% of the explained variation in murrelet response. Utilizing previously published murrelet density estimates from Glacier Bay, and applying an average empirical disturbance probability (68%) out to 850 m from a cruise ship’s typical route, we estimated that a minimum of 9.8–19.6% of all murrelets in Glacier Bay are disturbed per ship entry. Whether these disturbance levels are inconsistent with Park management objectives, which include conserving wildlife as well as providing opportunities for visitation, depends in large part on whether disturbance events caused by cruise ships have impacts on murrelet fitness, which remains uncertain.
Barrow's goldeneyes are sea ducks that winter throughout coastal British Columbia (BC). Their diet consists primarily of intertidal blue mussels, which can accumulate PAHs; accordingly, goldeneyes may be susceptible to exposure through contaminated prey. In 2014/15, we examined total PAH concentrations in mussels from undeveloped and developed coastal areas of BC. At those same sites, we used EROD to measure hepatic CYP1A induction in goldeneyes. We found higher mussel PAH concentrations at developed coastal sites. Regionally, goldeneyes from southern BC, which has relatively higher coastal development, had higher EROD activity compared to birds from northern BC. Our results suggest goldeneyes wintering in coastal BC were exposed to PAHs through diet, with higher exposure among birds wintering in coastal areas with greater anthropogenic influence. These results suggest the mussel-goldeneye system is suitable as a natural, multi-trophic-level indicator of contemporary hydrocarbon contamination occurrence and exposure useful for establishing oil spill recovery endpoints.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2017.02.010","usgsCitation":"Willie, M., Esler, D., Boyd, W.S., Molloy, P., and Ydenberg, R.C., 2017, Spatial variation in polycyclic aromatic hydrocarbon exposure in Barrow's goldeneye (Bucephala islandica) in coastal British Columbia: Marine Pollution Bulletin, v. 118, no. 1-2, p. 167-179, https://doi.org/10.1016/j.marpolbul.2017.02.010.","productDescription":"14 p.","startPage":"167","endPage":"179","ipdsId":"IP-078959","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":348014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"British Columbia","volume":"118","issue":"1-2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fadd23e4b0531197b13c9a","contributors":{"authors":[{"text":"Willie, Megan","contributorId":199404,"corporation":false,"usgs":false,"family":"Willie","given":"Megan","email":"","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":false,"id":719002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esler, Daniel 0000-0001-5501-4555 desler@usgs.gov","orcid":"https://orcid.org/0000-0001-5501-4555","contributorId":5465,"corporation":false,"usgs":true,"family":"Esler","given":"Daniel","email":"desler@usgs.gov","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":719001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyd, W. Sean","contributorId":199405,"corporation":false,"usgs":false,"family":"Boyd","given":"W.","email":"","middleInitial":"Sean","affiliations":[{"id":35539,"text":"Science and Technology Branch, Environment and Climate Change Canada, Delta, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":719003,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Molloy, Philip","contributorId":199406,"corporation":false,"usgs":false,"family":"Molloy","given":"Philip","email":"","affiliations":[{"id":35540,"text":"Stantec Consulting, Ltd., Sidney, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":719004,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ydenberg, Ronald C.","contributorId":199407,"corporation":false,"usgs":false,"family":"Ydenberg","given":"Ronald","email":"","middleInitial":"C.","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":false,"id":719005,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193423,"text":"70193423 - 2017 - Cessation of oil exposure in harlequin ducks after the Exxon Valdez oil spill: Cytochrome P4501A biomarker evidence","interactions":[],"lastModifiedDate":"2017-11-01T12:57:16","indexId":"70193423","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Cessation of oil exposure in harlequin ducks after the Exxon Valdez oil spill: Cytochrome P4501A biomarker evidence","title":"Cessation of oil exposure in harlequin ducks after the Exxon Valdez oil spill: Cytochrome P4501A biomarker evidence","docAbstract":"The authors quantified hepatic hydrocarbon-inducible cytochrome P4501A (CYP1A) expression, as ethoxyresorufin-O-deethylase (EROD) activity, in wintering harlequin ducks (Histrionicus histrionicus) captured in Prince William Sound, Alaska (USA), during 2011, 2013, and 2014 (22–25 yr following the 1989 Exxon Valdez oil spill). Average EROD activity was compared between birds from areas oiled by the spill and those from nearby unoiled areas. The present study replicated studies conducted from 1998 to 2009 demonstrating that harlequin ducks using areas oiled in 1989 had elevated EROD activity, indicative of oil exposure, up to 2 decades post spill. In the present study, it was found that average EROD activity during March 2011 was significantly higher in wintering harlequin ducks captured in oiled areas relative to unoiled areas, which the authors interpret to indicate that harlequin ducks continued to be exposed to residual Exxon Valdez oil up to 22 yr after the original spill. However, the 2011 results also indicated reductions in exposure relative to previous years. Average EROD activity in birds from oiled areas was approximately 2 times that in birds from unoiled areas in 2011, compared with observations from 2005 to 2009, in which EROD activity was 3 to 5 times higher in oiled areas. It was also found that average EROD activity during March 2013 and March 2014 was not elevated in wintering harlequin ducks from oiled areas. The authors interpret these findings to indicate that exposure of harlequin ducks to residual Exxon Valdez oil abated within 24 yr after the original spill. The present study finalizes a timeline of exposure, extending over 2 decades, for a bird species thought to be particularly vulnerable to oil contamination in marine environments
","language":"English","publisher":"Wiley","doi":"10.1002/etc.3659","usgsCitation":"Esler, D., Ballachey, B.E., Bowen, L., Miles, A.K., Dickson, R.D., and Henderson, J.D., 2017, Cessation of oil exposure in harlequin ducks after the Exxon Valdez oil spill: Cytochrome P4501A biomarker evidence: Environmental Toxicology and Chemistry, v. 36, no. 5, p. 1294-1300, https://doi.org/10.1002/etc.3659.","productDescription":"7 p.","startPage":"1294","endPage":"1300","ipdsId":"IP-076871","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":438357,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KD1W1M","text":"USGS data release","linkHelpText":"Harlequin duck capture and EROD activity data from Prince William Sound, Alaska, 2011, 2013, 2014"},{"id":348006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","volume":"36","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-20","publicationStatus":"PW","scienceBaseUri":"59fadd23e4b0531197b13c9f","contributors":{"authors":[{"text":"Esler, Daniel 0000-0001-5501-4555 desler@usgs.gov","orcid":"https://orcid.org/0000-0001-5501-4555","contributorId":5465,"corporation":false,"usgs":true,"family":"Esler","given":"Daniel","email":"desler@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":718988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ballachey, Brenda E. 0000-0003-1855-9171 bballachey@usgs.gov","orcid":"https://orcid.org/0000-0003-1855-9171","contributorId":2966,"corporation":false,"usgs":true,"family":"Ballachey","given":"Brenda","email":"bballachey@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}],"preferred":true,"id":718989,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":718990,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miles, A. Keith 0000-0002-3108-808X keith_miles@usgs.gov","orcid":"https://orcid.org/0000-0002-3108-808X","contributorId":196,"corporation":false,"usgs":true,"family":"Miles","given":"A.","email":"keith_miles@usgs.gov","middleInitial":"Keith","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":718991,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dickson, Rian D.","contributorId":138554,"corporation":false,"usgs":false,"family":"Dickson","given":"Rian","email":"","middleInitial":"D.","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":false,"id":718992,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Henderson, John D.","contributorId":94632,"corporation":false,"usgs":false,"family":"Henderson","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":718993,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196238,"text":"70196238 - 2017 - Historical biogeography sets the foundation for contemporary conservation of martens (genus Martes) in northwestern North America","interactions":[],"lastModifiedDate":"2018-03-28T11:31:36","indexId":"70196238","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Historical biogeography sets the foundation for contemporary conservation of martens (genus Martes) in northwestern North America","title":"Historical biogeography sets the foundation for contemporary conservation of martens (genus Martes) in northwestern North America","docAbstract":"Effective conservation of insular populations requires careful consideration of biogeography, including colonization histories and patterns of endemism. Across the Pacific Northwest of North America, Pacific martens (Martes caurina) and American pine martens (Martes americana) are parapatric sister species with distinctive postglacial histories. Using mitochondrial DNA and 12 nuclear microsatellite loci, we examine processes of island colonization and anthropogenic introductions across 25 populations of martens. Along the North Pacific Coast (NPC), M. caurina is now found on only 2 islands, whereas M. americana occurs on mainland Alaska and British Columbia and multiple associated islands. Island populations of M. caurina have a longer history of isolation reflected in divergent haplotypes, private microsatellite alleles, and relatively low within-population diversity. In contrast, insular M. americanahave lower among-population divergence and higher metrics of within-population diversity. On some NPC islands, introductions of M. americana may be related to decline of M. caurina. Long-term persistence of these species likely has been influenced by anthropogenic manipulations, including wildlife translocations and industrial-scale deforestation, yet, the distinctive histories of these martens have not been incorporated into natural resource policies.
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This change prompted a sustained effort to improve the accuracy of ash-cloud model forecasts. In this paper we describe how this goal is being advanced on three fronts: (1) assessing current capabilities and establishing best practices; (2) improving the accuracy of model inputs; and (3) developing strategies to automatically compare model output with observations and adjust inputs to produce the best match. Progress has been made on all three fronts. A key lesson is that accuracy can only be quantified by comparison with reliable observations, which are often elusive. 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