{"pageNumber":"56","pageRowStart":"1375","pageSize":"25","recordCount":11370,"records":[{"id":70198103,"text":"70198103 - 2018 - Effect of climate change on disease spread in wildlife","interactions":[],"lastModifiedDate":"2020-08-19T20:23:59.281937","indexId":"70198103","displayToPublicDate":"2018-06-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"36","title":"Effect of climate change on disease spread in wildlife","docAbstract":"A growing body of evidence indicates that climate change alone, or acting synergistically with current anthropogenic threats, is affecting the health of wild populations of aquatic and terrestrial wildlife. Measurable by-products of climate change include elevated atmospheric concentrations of greenhouse gases, higher average global temperatures; variations in global precipitation patterns, rising and warming oceans, altered hydrographs of rivers, and increased mid-continental drying during summer. These consequences affect the terrestrial environment through shifts in phenology, vegetation cover, and fire regimes. Warmer ocean temperatures, increased acidification, rise in sea levels, and reduction in sea ice cover are also leading to widespread ecological changes in marine systems. Wildlife populations face a variety of climate-related pressures, such as changes in animal distribution or density, limitation of food resources, and alteration to critical habitats. \nThe increased potential for emergence and resurgence of diseases that are responsive to environmental conditions also has implications for wildlife populations. Shifts in temperature or other climatic factors may directly affect the incidence of disease in wildlife by altering host-pathogen interactions, promoting vector populations or allowing new ranges for vectors, or reducing development times for parasites. A number of examples from both field and laboratory studies have demonstrated a clear link between warming environments and disease spread. Many climate-related environmental changes also influence wildlife health indirectly. For example, increasing temperatures, in combination with shifts in rainfall and humidity, may aggravate current trends for water resource limitation and habitat degradation or destruction and lead to increased crowding of animal populations, thereby promoting transmission opportunities of pathogens within populations or across species. \nAlthough it may be difficult to disentangle the influences of other anthropogenic changes from the direct effects of warming, some ecosystems provide especially useful models for studying climate-related disease spread in wildlife. For example, the effects of climate change on parasite dynamics may be easily observed in the Arctic, where environmental changes are occurring rapidly, anthropogenic influences are relatively limited, and biodiversity is generally low. Marine ecosystems are also undergoing rapid rates of change and may be vulnerable to a variety of natural and anthropogenic perturbations. Although many factors affect the health of organisms in ocean environments, temperature has been clearly linked to an increase in disease prevalence among sessile organisms such as corals. \nIn this chapter, we discuss observed and predicted changes to wildlife health resulting from climate change. Our review will not include all aspects of wildlife health, but will instead focus on established or suspected links between climate drivers and disease spread and discuss examples from the current literature. Here, we define disease spread to include: 1) change in geographical or altitudinal distribution of pathogens, parasites, and vectors and the diseases they cause; 2) change in prevalence or severity of disease; and 3) emergence of novel diseases. Additionally, because wildlife species serve as reservoirs for zoonotic diseases that affect both animals and humans, we include select examples of the effect of climate change on the capacity of wildlife to harbor and spread these disease agents.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Fowler's Zoo and Wild Animal Medicine Current Therapy","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","isbn":"9780323552288","usgsCitation":"Hofmeister, E.K., and Van Hemert, C.R., 2018, Effect of climate change on disease spread in wildlife, chap. 36 of Fowler's Zoo and Wild Animal Medicine Current Therapy, p. 247-254.","productDescription":"8 p.","startPage":"247","endPage":"254","ipdsId":"IP-084742","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":355686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":355684,"type":{"id":15,"text":"Index Page"},"url":"https://www.us.elsevierhealth.com/miller-fowlers-zoo-and-wild-animal-medicine-current-therapy-volume-9-9780323552288.html"}],"publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc41ce4b0f5d57878e9f9","contributors":{"authors":[{"text":"Hofmeister, Erik K. 0000-0002-6360-3912 ehofmeister@usgs.gov","orcid":"https://orcid.org/0000-0002-6360-3912","contributorId":3230,"corporation":false,"usgs":true,"family":"Hofmeister","given":"Erik","email":"ehofmeister@usgs.gov","middleInitial":"K.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":740032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Hemert, Caroline R. 0000-0002-6858-7165 cvanhemert@usgs.gov","orcid":"https://orcid.org/0000-0002-6858-7165","contributorId":3592,"corporation":false,"usgs":true,"family":"Van Hemert","given":"Caroline","email":"cvanhemert@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":740033,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197916,"text":"70197916 - 2018 - Using stereo satellite imagery to account for ablation, entrainment, and compaction in volume calculations for rock avalanches on Glaciers: Application to the 2016 Lamplugh Rock Avalanche in Glacier Bay National Park, Alaska","interactions":[],"lastModifiedDate":"2018-06-26T14:06:50","indexId":"70197916","displayToPublicDate":"2018-06-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Using stereo satellite imagery to account for ablation, entrainment, and compaction in volume calculations for rock avalanches on Glaciers: Application to the 2016 Lamplugh Rock Avalanche in Glacier Bay National Park, Alaska","docAbstract":"The use of preevent and postevent digital elevation models (DEMs) to estimate the volume of rock avalanches on glaciers is complicated by ablation of ice before and after the rock avalanche, scour of material during rock avalanche emplacement, and postevent ablation and compaction of the rock avalanche deposit. We present a model to account for these processes in volume estimates of rock avalanches on glaciers. We applied our model by calculating the volume of the 28 June 2016 Lamplugh rock avalanche in Glacier Bay National Park, Alaska. We derived preevent and postevent 2‐m resolution DEMs from WorldView satellite stereo imagery. Using data from DEM differencing, we reconstructed the rock avalanche and adjacent surfaces at the time of occurrence by accounting for elevation changes due to ablation and scour of the ice surface, and postevent deposit changes. We accounted for uncertainties in our DEMs through precise coregistration and an assessment of relative elevation accuracy in bedrock control areas. The rock avalanche initially displaced 51.7 ± 1.5 Mm3 of intact rock and then scoured and entrained 13.2 ± 2.2 Mm3 of snow and ice during emplacement. We calculated the total deposit volume to be 69.9 ± 7.9 Mm3. Volume estimates that did not account for topographic changes due to ablation, scour, and compaction underestimated the deposit volume by 31.0–46.8 Mm3. Our model provides an improved framework for estimating uncertainties affecting rock avalanche volume measurements in glacial environments. These improvements can contribute to advances in the understanding of rock avalanche hazards and dynamics.","language":"English","publisher":"Wiley","doi":"10.1002/2017JF004512","usgsCitation":"Bessette-Kirton, E., Coe, J.A., and Zhou, W., 2018, Using stereo satellite imagery to account for ablation, entrainment, and compaction in volume calculations for rock avalanches on Glaciers: Application to the 2016 Lamplugh Rock Avalanche in Glacier Bay National Park, Alaska: Journal of Geophysical Research B: Solid Earth, v. 123, no. 4, p. 622-641, https://doi.org/10.1002/2017JF004512.","productDescription":"20 p.","startPage":"622","endPage":"641","ipdsId":"IP-094586","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468630,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jf004512","text":"Publisher Index Page"},{"id":355368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Glacier 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 -154.423828125,\n 50.3454604086048\n ],\n [\n -125.24414062499999,\n 50.3454604086048\n ],\n [\n -125.24414062499999,\n 64.62387720204688\n ],\n [\n -154.423828125,\n 64.62387720204688\n ],\n [\n -154.423828125,\n 50.3454604086048\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-06","publicationStatus":"PW","scienceBaseUri":"5b46e54ee4b060350a15d0b9","contributors":{"authors":[{"text":"Bessette-Kirton, Erin 0000-0002-2797-0694 ebessette-kirton@usgs.gov","orcid":"https://orcid.org/0000-0002-2797-0694","contributorId":177153,"corporation":false,"usgs":true,"family":"Bessette-Kirton","given":"Erin","email":"ebessette-kirton@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":739093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":739094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhou, Wendy","contributorId":205989,"corporation":false,"usgs":false,"family":"Zhou","given":"Wendy","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":739095,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197873,"text":"70197873 - 2018 - Evidence for haemosporidian parasite infections in Spectacled Eiders (Somateria fischeri) sampled in Alaska during the breeding season","interactions":[],"lastModifiedDate":"2018-10-12T16:04:22","indexId":"70197873","displayToPublicDate":"2018-06-22T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evidence for haemosporidian parasite infections in Spectacled Eiders (Somateria fischeri) sampled in Alaska during the breeding season","title":"Evidence for haemosporidian parasite infections in Spectacled Eiders (Somateria fischeri) sampled in Alaska during the breeding season","docAbstract":"

We assessed hematozoa infection in Spectacled Eiders (Somateria fischeri) at two areas in Alaska. No Haemoproteus or Plasmodium species were detected. Leucocytozoon prevalence was 6.5% for adults across sites and 41.9% for juveniles sampled in the Arctic, providing evidence for local transmission. All Leucocytozoon haplotypes were previously detected in waterfowl.

","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2018-01-012","usgsCitation":"Reed, J.A., Sexson, M.G., Smith, M.M., Schmutz, J.A., and Ramey, A.M., 2018, Evidence for haemosporidian parasite infections in Spectacled Eiders (Somateria fischeri) sampled in Alaska during the breeding season: Journal of Wildlife Diseases, v. 54, no. 4, p. 877-880, https://doi.org/10.7589/2018-01-012.","productDescription":"4 p.","startPage":"877","endPage":"880","ipdsId":"IP-094145","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":437847,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CDBRDC","text":"USGS data release","linkHelpText":"Blood Parasite Infection Data from Spectacled Eiders (Somateria fischeri), Alaska (USA), 2008-2012"},{"id":355316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"54","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e552e4b060350a15d0cf","contributors":{"authors":[{"text":"Reed, John A. 0000-0002-3239-6906 jareed@usgs.gov","orcid":"https://orcid.org/0000-0002-3239-6906","contributorId":127683,"corporation":false,"usgs":true,"family":"Reed","given":"John","email":"jareed@usgs.gov","middleInitial":"A.","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":738844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sexson, Matthew G. 0000-0002-1078-0835 msexson@usgs.gov","orcid":"https://orcid.org/0000-0002-1078-0835","contributorId":5544,"corporation":false,"usgs":true,"family":"Sexson","given":"Matthew","email":"msexson@usgs.gov","middleInitial":"G.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":738845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Matthew M. 0000-0002-2259-5135 mmsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-2259-5135","contributorId":5115,"corporation":false,"usgs":true,"family":"Smith","given":"Matthew","email":"mmsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":738846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":738847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":738848,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227705,"text":"70227705 - 2018 - Experimental evidence of long-term reproductive costs in a colonial nesting seabird","interactions":[],"lastModifiedDate":"2022-01-27T14:30:59.155631","indexId":"70227705","displayToPublicDate":"2018-06-21T08:24:36","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Experimental evidence of long-term reproductive costs in a colonial nesting seabird","docAbstract":"

Trade-offs between current and future reproduction are central to the evolution of life histories. Experiments that manipulate brood size provide an effective approach to investigating future costs of current reproduction. Most manipulative studies to date, however, have addressed only the short-term effects of brood size manipulation. Our goal was to determine whether survival or breeding costs of reproduction in a long-lived species manifest beyond the subsequent breeding season. To this end, we investigated long-term survival and breeding effects of a multi-year reproductive cost experiment conducted on black-legged kittiwakes Rissa tridactyla, a long-lived colonial nesting seabird. We used multi-state capture–recapture modeling to assess hypotheses regarding the role of experimentally reduced breeding effort and other factors, including climate phase and colony size and productivity, on future survival and breeding probabilities during the 16-yr period following the experiment. We found that forced nest failures had a positive effect on breeding probability over time, but had no effect on long-term survival. This apparent canalization of survival suggests that adult survival is the most important parameter influencing fitness in this long-lived species, and that adults should pay reproductive costs in ways that do not compromise this critical life history parameter. When declines in adult survival rate are observed, they may indicate populations of conservation concern.

","language":"English","publisher":"Wiley","doi":"10.1111/jav.01779","usgsCitation":"McKnight, A., Blomberg, E.J., Golet, G.H., Irons, D.B., Loftin, C., and McKinney, S.T., 2018, Experimental evidence of long-term reproductive costs in a colonial nesting seabird: Journal of Avian Biology, v. 49, no. 8, e01779, 14 p., https://doi.org/10.1111/jav.01779.","productDescription":"e01779, 14 p.","ipdsId":"IP-075525","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":394966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -148.86474609375,\n 59.77852198502987\n ],\n [\n -145.5,\n 59.77852198502987\n ],\n [\n -145.5,\n 61.29398784561188\n ],\n [\n -148.86474609375,\n 61.29398784561188\n ],\n [\n -148.86474609375,\n 59.77852198502987\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"8","noUsgsAuthors":false,"publicationDate":"2018-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"McKnight, Aly","contributorId":220818,"corporation":false,"usgs":false,"family":"McKnight","given":"Aly","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":831948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blomberg, Erik J.","contributorId":17543,"corporation":false,"usgs":false,"family":"Blomberg","given":"Erik","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":831949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Golet, Gregory H.","contributorId":89844,"corporation":false,"usgs":false,"family":"Golet","given":"Gregory","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":831950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irons, David B.","contributorId":220820,"corporation":false,"usgs":false,"family":"Irons","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":831951,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":831842,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKinney, Shawn T. smckinney@usgs.gov","contributorId":5175,"corporation":false,"usgs":true,"family":"McKinney","given":"Shawn","email":"smckinney@usgs.gov","middleInitial":"T.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":831952,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197820,"text":"70197820 - 2018 - Avian keratin disorder of Alaska black-capped chickadees is associated with Poecivirus infection","interactions":[],"lastModifiedDate":"2018-06-20T19:33:20","indexId":"70197820","displayToPublicDate":"2018-06-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3697,"text":"Virology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Avian keratin disorder of Alaska black-capped chickadees is associated with Poecivirus infection","docAbstract":"

Background

Avian keratin disorder (AKD) is an epizootic of debilitating beak deformities, first documented in black-capped chickadees (Poecile atricapillus) in Alaska during the late 1990s. Similar deformities have now been recorded in dozens of species of birds across multiple continents. Despite this, the etiology of AKD has remained elusive, making it difficult to assess the impacts of this disease on wild populations. We previously identified an association between infection with a novel picornavirus, Poecivirus, and AKD in a small cohort of black-capped chickadees.


Methods

To test if the association between Poecivirus and AKD holds in a larger study population, we used targeted PCR followed by Sanger sequencing to screen 124 symptomatic and asymptomatic black-capped chickadees for Poecivirus infection. We further compared the efficacy of multiple non-terminal field sampling methods (buccal swabs, cloacal swabs, fecal samples, and blood samples) for Poecivirus screening. Finally, we used both in situ hybridization and a strand-specific expression assay to localize Poecivirus to beak tissue of AKD-positive individuals and to determine if virus is actively replicating in beak tissue.


Results

Poecivirus was detected in 28/28 (100%) individuals with AKD, but only 9/96 (9.4%) asymptomatic individuals with apparently normal beaks (p < 0.0001). We found that cloacal swabs are the most sensitive of these sample types for detecting Poecivirus in birds with AKD, but that buccal swabs should be combined with cloacal swabs in evaluating the infection status of asymptomatic birds. Finally, we used both in situ hybridization and a strand-specific expression assay to localize Poecivirus to beak tissue of AKD-positive individuals and to provide evidence of active viral replication.


Conclusion

The data presented here show a strong, statistically significant relationship between Poecivirus infection and AKD, and provide evidence that Poecivirus is indeed an avian virus, infecting and actively replicating in beak tissue of AKD-affected BCCH. Taken together, these data corroborate and extend the evidence for a potential causal association between Poecivirus and AKD in the black-capped chickadee. Poecivirus continues to warrant further investigation as a candidate agent of AKD.

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cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":738652,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeRisi, Joseph L.","contributorId":172863,"corporation":false,"usgs":false,"family":"DeRisi","given":"Joseph","email":"","middleInitial":"L.","affiliations":[{"id":27105,"text":"University of California San Francisco; Howard Hughes Medical Institute","active":true,"usgs":false}],"preferred":false,"id":738653,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199152,"text":"70199152 - 2018 - Energetic costs of locomotion in bears: is plantigrade locomotion energetically economical?","interactions":[],"lastModifiedDate":"2018-09-07T16:01:21","indexId":"70199152","displayToPublicDate":"2018-06-19T16:01:12","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2275,"text":"Journal of Experimental Biology","active":true,"publicationSubtype":{"id":10}},"title":"Energetic costs of locomotion in bears: is plantigrade locomotion energetically economical?","docAbstract":"

Ursids are the largest mammals to retain a plantigrade posture. This primitive posture has been proposed to result in reduced locomotor speed and economy relative to digitigrade and unguligrade species, particularly at high speeds. Previous energetics research on polar bears (Ursus maritimus) found locomotor costs were more than double predictions for similarly sized quadrupedal mammals, which could be a result of their plantigrade posture or due to adaptations to their Arctic marine existence. To evaluate whether polar bears are representative of terrestrial ursids or distinctly uneconomical walkers, this study measured the mass-specific metabolism, overall dynamic body acceleration, and gait kinematics of polar bears and grizzly bears (Ursus arctos) trained to rest and walk on a treadmill. At routine walking speeds, we found polar bears and grizzly bears exhibited similar costs of locomotion and gait kinematics, but differing measures of overall dynamic body acceleration. Minimum cost of transport while walking in the two species (2.21 J kg−1 m−1) was comparable to predictions for similarly sized quadrupedal mammals, but these costs doubled (4.42 J kg−1 m−1) at speeds ≥5.4 km h−1. Similar to humans, another large plantigrade mammal, bears appear to exhibit a greater economy while moving at slow speeds.

","language":"English","publisher":"The Company of Biologists","doi":"10.1242/jeb.175372","usgsCitation":"Pagano, A.M., Carnahan, A.M., Robbins, C.T., Owen, M.A., Batson, T., Wagner, N., Cutting, A., Nicassio-Hiskey, N., Hash, A., and Williams, T.M., 2018, Energetic costs of locomotion in bears: is plantigrade locomotion energetically economical?: Journal of Experimental Biology, v. 221, no. 12, p. 1-9, https://doi.org/10.1242/jeb.175372.","productDescription":"9 p.","startPage":"1","endPage":"9","ipdsId":"IP-092794","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":468645,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1242/jeb.175372","text":"Publisher Index Page"},{"id":437852,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QR4W91","text":"USGS data release","linkHelpText":"Energetic Costs of Locomotion in Bears"},{"id":357132,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"221","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-19","publicationStatus":"PW","scienceBaseUri":"5b98a2aee4b0702d0e842faf","contributors":{"authors":[{"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":744377,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carnahan, Anthony M.","contributorId":207641,"corporation":false,"usgs":false,"family":"Carnahan","given":"Anthony","email":"","middleInitial":"M.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":744378,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":744379,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Owen, Megan A.","contributorId":138918,"corporation":false,"usgs":false,"family":"Owen","given":"Megan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":744380,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Batson, Tammy","contributorId":207642,"corporation":false,"usgs":false,"family":"Batson","given":"Tammy","email":"","affiliations":[{"id":37593,"text":"San Diego Zoo","active":true,"usgs":false}],"preferred":false,"id":744381,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, Nate","contributorId":207643,"corporation":false,"usgs":false,"family":"Wagner","given":"Nate","email":"","affiliations":[{"id":37593,"text":"San Diego Zoo","active":true,"usgs":false}],"preferred":false,"id":744382,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cutting, Amy","contributorId":200751,"corporation":false,"usgs":false,"family":"Cutting","given":"Amy","email":"","affiliations":[],"preferred":false,"id":744383,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nicassio-Hiskey, Nicole","contributorId":150616,"corporation":false,"usgs":false,"family":"Nicassio-Hiskey","given":"Nicole","email":"","affiliations":[{"id":18050,"text":"Oregon Zoo","active":true,"usgs":false}],"preferred":false,"id":744384,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hash, Amy","contributorId":200755,"corporation":false,"usgs":false,"family":"Hash","given":"Amy","email":"","affiliations":[],"preferred":false,"id":744385,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Williams, Terrie M.","contributorId":191735,"corporation":false,"usgs":false,"family":"Williams","given":"Terrie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":744386,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70200630,"text":"70200630 - 2018 - A method to value nature-related webcam viewing: The value of virtual use with application to brown bear webcam viewing","interactions":[],"lastModifiedDate":"2018-10-26T09:47:55","indexId":"70200630","displayToPublicDate":"2018-06-18T12:37:08","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5771,"text":"Journal of Environmental Economics and Policy","active":true,"publicationSubtype":{"id":10}},"title":"A method to value nature-related webcam viewing: The value of virtual use with application to brown bear webcam viewing","docAbstract":"

There are an estimated 16,000 nature related remote web cameras that provide users around the world with an opportunity to view wildlife. Because there is no monetary price to view the webcams, we utilise variations in the viewers’ opportunity cost of time to estimate consumer surplus. We apply this model to a large sample (n = 2649) of the more than 10 million viewers of Alaska's Katmai National Park and Preserve brown bear webcams. The resulting consumer surplus is around \\$11 per hour of viewing. When applied to the 2.42 million viewer hours, this yields a benefit of \\$27 million annually. Since there are limits on the number of visitors as well as high costs of visiting this remote site, the aggregate webcam viewing value is more than twice the aggregate on-site viewing value. With minimal survey data required to apply this model, we believe it has broad applicability to other nature-related webcams around the world.

","language":"English","publisher":"Taylor and Francis","doi":"10.1080/21606544.2018.1483842","usgsCitation":"Loomis, J.B., Richardson, L., Huber, C., Skibins, J., and Sharp, R., 2018, A method to value nature-related webcam viewing: The value of virtual use with application to brown bear webcam viewing: Journal of Environmental Economics and Policy, v. 7, no. 4, p. 452-462, https://doi.org/10.1080/21606544.2018.1483842.","productDescription":"11 p.","startPage":"452","endPage":"462","ipdsId":"IP-090967","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":358820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-18","publicationStatus":"PW","scienceBaseUri":"5c10a99ae4b034bf6a7e5359","contributors":{"authors":[{"text":"Loomis, John B.","contributorId":197268,"corporation":false,"usgs":false,"family":"Loomis","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":749758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richardson, Leslie","contributorId":197525,"corporation":false,"usgs":false,"family":"Richardson","given":"Leslie","affiliations":[],"preferred":false,"id":749759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huber, Christopher 0000-0001-8446-8134 chuber@usgs.gov","orcid":"https://orcid.org/0000-0001-8446-8134","contributorId":127600,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":749757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skibins, Jeffrey","contributorId":210077,"corporation":false,"usgs":false,"family":"Skibins","given":"Jeffrey","email":"","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":749760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sharp, Ryan","contributorId":168598,"corporation":false,"usgs":false,"family":"Sharp","given":"Ryan","email":"","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":749761,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216336,"text":"70216336 - 2018 - Evolving environmental and geometric controls on Columbia Glacier’s continued retreat","interactions":[],"lastModifiedDate":"2020-11-12T15:31:39.238099","indexId":"70216336","displayToPublicDate":"2018-06-11T09:27:01","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7354,"text":"Journal of Geophysical Research- Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Evolving environmental and geometric controls on Columbia Glacier’s continued retreat","docAbstract":"

Geometry strongly controls the dynamic behavior of marine‐terminating (tidewater) glaciers, significantly influencing advance and retreat cycles independent of climate. Yet the recent, nearly ubiquitous retreat of tidewater glaciers suggests that changes in atmospheric and oceanic forcing may also drive dynamic change. To isolate the influence of geometry on tidewater glacier dynamics, we analyzed detailed observational time series from 2012 to 2016 for two tidewater glaciers with shared dynamic histories and environmental forcing: Columbia Glacier and its former tributary (Post Glacier) in southcentral Alaska. We find that although terminus retreat has driven decadal‐scale changes in dynamics of the Columbia‐Post system, environmental factors contribute to short‐term (i.e., seasonal) dynamic variability. In particular, analysis of force balance time series indicates that observed variations in speed result from seasonal changes to the subglacial hydrologic system and associated changes in basal drag. Variations in terminus position only drive noticeable speed change when the terminus retreats from regions of relatively high basal drag. In agreement with long‐term analyses of Columbia Glacier, we find that terminus geometry can perturb the timing of seasonal ice flow patterns. Specifically, our data support the idea that retreat of a glacier terminus into deeper water is accompanied by a shift in the primary control on frontal ablation. Although our analysis focuses on two Alaskan glaciers, our data suggest that changes in the relative importance of surface meltwater and buoyancy effects on submarine melting and/or calving may manifest as a shift in terminus change seasonality and offer a mechanism to identify frontal ablation controls.

","language":"English","publisher":"Wiley","doi":"10.1029/2017JF004541","usgsCitation":"Enderlin, E., O’Neel, S., Bartholomaus, T.C., and Joughin, I., 2018, Evolving environmental and geometric controls on Columbia Glacier’s continued retreat: Journal of Geophysical Research- Earth Surface, v. 123, no. 7, p. 1528-1545, https://doi.org/10.1029/2017JF004541.","productDescription":"18 p.","startPage":"1528","endPage":"1545","ipdsId":"IP-092117","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":460895,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017jf004541","text":"Publisher Index Page"},{"id":380456,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Columbia Glacier","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -148.33740234375,\n 60.74842446462361\n ],\n [\n -146.05224609375,\n 60.74842446462361\n ],\n [\n -146.05224609375,\n 61.77312286453146\n ],\n [\n -148.33740234375,\n 61.77312286453146\n ],\n [\n -148.33740234375,\n 60.74842446462361\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"7","noUsgsAuthors":false,"publicationDate":"2018-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Enderlin, Ellyn","contributorId":187445,"corporation":false,"usgs":false,"family":"Enderlin","given":"Ellyn","email":"","affiliations":[],"preferred":false,"id":804740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":804741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartholomaus, Timothy C.","contributorId":147404,"corporation":false,"usgs":false,"family":"Bartholomaus","given":"Timothy","email":"","middleInitial":"C.","affiliations":[{"id":16840,"text":"U. Texas Austin","active":true,"usgs":false}],"preferred":false,"id":804742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Joughin, Ian","contributorId":244835,"corporation":false,"usgs":false,"family":"Joughin","given":"Ian","email":"","affiliations":[{"id":48995,"text":"U Washington","active":true,"usgs":false}],"preferred":false,"id":804743,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237325,"text":"70237325 - 2018 - Ongoing bedrock incision of the Fortymile River driven by Pliocene–Pleistocene Yukon River capture, eastern Alaska, USA, and Yukon, Canada","interactions":[],"lastModifiedDate":"2022-10-07T11:50:15.326428","indexId":"70237325","displayToPublicDate":"2018-06-07T06:44:31","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Ongoing bedrock incision of the Fortymile River driven by Pliocene–Pleistocene Yukon River capture, eastern Alaska, USA, and Yukon, Canada","docAbstract":"

Quantification of river incision via process rate laws represents a key goal of geomorphic research, but such models often fail to reproduce traits of natural rivers responding to base-level lowering. The Fortymile River flows from eastern Alaska in the United States to the Yukon River in Canada across a tectonically quiescent region with near-uniform precipitation and bedrock erosivity. We exploit these stable boundary conditions to quantify bedrock incision evident in a gravel-capped strath terrace that flanks the lower ∼175 km of the river and grades to the minimally incised headwaters. The terrace gravel yields a cosmogenic isochron burial age of 2.44 ± 0.24 Ma, consistent with abandonment triggered by late Pliocene–early Pleistocene Yukon River headwater capture. The deeply incised reach forms a linear knickzone where basin relief nearly doubles and inferred bedrock incision rates (∼19–110 m/m.y.) averaged since ca. 2.44 Ma increase downstream toward the Fortymile–Yukon River confluence. Basin-scale 10Be-based erosion rates of tributaries to the Fortymile River trunk nearly double from the headwaters (∼9 mm/k.y.) to the knickzone (average ∼16 mm/k.y.), revealing the pace of ongoing landscape response to knickzone incision over 104 yr. Our observations calibrate a stream-power model (erosion coefficient K ∼ 1.1 × 10–6 m0.2) that closely reproduces the knickzone profile and thus implies long-term (104–106 yr) efficacy of a simple stream-power bedrock incision law.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/G40203.1","usgsCitation":"Bender, A., Lease, R.O., Corbett, L.B., Bierman, P., and Caffee, M., 2018, Ongoing bedrock incision of the Fortymile River driven by Pliocene–Pleistocene Yukon River capture, eastern Alaska, USA, and Yukon, Canada: Geology, v. 46, no. 7, p. 635-638, https://doi.org/10.1130/G40203.1.","productDescription":"4 p.","startPage":"635","endPage":"638","ipdsId":"IP-097924","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":437873,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DRHQIS","text":"USGS data release","linkHelpText":"Charley River Cosmogenic Isotope Data Collected 2019-2021"},{"id":437872,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XVMTAK","text":"USGS data release","linkHelpText":"Fortymile River Cosmogenic Isotope and Luminescence Data Collected 2016-2019"},{"id":408080,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska","otherGeospatial":"Yukon, Yukon River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -144.404296875,\n 63.470144746565424\n ],\n [\n -137.98828125,\n 63.470144746565424\n ],\n [\n -137.98828125,\n 65.87472467098549\n ],\n [\n -144.404296875,\n 65.87472467098549\n ],\n [\n -144.404296875,\n 63.470144746565424\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"7","noUsgsAuthors":false,"publicationDate":"2018-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Bender, Adrian 0000-0001-7469-1957","orcid":"https://orcid.org/0000-0001-7469-1957","contributorId":219952,"corporation":false,"usgs":true,"family":"Bender","given":"Adrian","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":854132,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lease, Richard O. 0000-0003-2582-8966 rlease@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-8966","contributorId":5098,"corporation":false,"usgs":true,"family":"Lease","given":"Richard","email":"rlease@usgs.gov","middleInitial":"O.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":854133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corbett, Lee B.","contributorId":152123,"corporation":false,"usgs":false,"family":"Corbett","given":"Lee","email":"","middleInitial":"B.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":854134,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bierman, Paul R.","contributorId":198743,"corporation":false,"usgs":false,"family":"Bierman","given":"Paul R.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":854135,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caffee, Marc","contributorId":265488,"corporation":false,"usgs":false,"family":"Caffee","given":"Marc","affiliations":[{"id":54691,"text":"Purdue University, PRIME laboratory","active":true,"usgs":false}],"preferred":false,"id":854136,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197485,"text":"70197485 - 2018 - Mean composite fire severity metrics computed with Google Earth Engine offer improved accuracy and expanded mapping potential","interactions":[],"lastModifiedDate":"2018-06-07T09:49:46","indexId":"70197485","displayToPublicDate":"2018-06-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Mean composite fire severity metrics computed with Google Earth Engine offer improved accuracy and expanded mapping potential","docAbstract":"Landsat-based fire severity datasets are an invaluable resource for monitoring and research purposes. These gridded fire severity datasets are generally produced with pre-and post-fire imagery to estimate the degree of fire-induced ecological change. Here, we introduce methods to produce three Landsat-based fire severity metrics using the Google Earth Engine (GEE) platform: the delta normalized burn ratio (dNBR), the relativized delta normalized burn ratio (RdNBR), and the relativized burn ratio (RBR). Our methods do not rely on time-consuming a priori scene selection and instead use a mean compositing approach in which all valid pixels (e.g. cloud-free) over a pre-specified date range (pre- and post-fire) are stacked and the mean value for each pixel over each stack is used to produce the resulting fire severity datasets. This approach demonstrates that fire severity datasets can be produced with relative ease and speed compared the standard approach in which one pre-fire and post-fire scene are judiciously identified and used to produce fire severity datasets. We also validate the GEE-derived fire severity metrics using field-based fire severity plots for 18 fires in the western US. These validations are compared to Landsat-based fire severity datasets produced using only one pre- and post-fire scene, which has been the standard approach in producing such datasets since their inception. Results indicate that the GEE-derived fire severity datasets show improved validation statistics compared to parallel versions in which only one pre-fire and post-fire scene are used. We provide code and a sample geospatial fire history layer to produce dNBR, RdNBR, and RBR for the 18 fires we evaluated. Although our approach requires that a geospatial fire history layer (i.e. fire perimeters) be produced independently and prior to applying our methods, we suggest our GEE methodology can reasonably be implemented on hundreds to thousands of fires, thereby increasing opportunities for fire severity monitoring and research across the globe.","language":"English","publisher":"MDPI","publisherLocation":"Basel, Switzerland","doi":"10.3390/rs10060879","usgsCitation":"Parks, S., Holsinger, L.M., Voss, M., Loehman, R.A., and Robinson, N.P., 2018, Mean composite fire severity metrics computed with Google Earth Engine offer improved accuracy and expanded mapping potential: Remote Sensing, v. 10, no. 6, 876, 15 p., https://doi.org/10.3390/rs10060879.","productDescription":"876, 15 p.","ipdsId":"IP-097816","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":468676,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs10060879","text":"Publisher Index Page"},{"id":354799,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -130.78125,\n 31.952162238024975\n ],\n [\n -101.953125,\n 31.952162238024975\n ],\n [\n -101.953125,\n 50.51342652633956\n ],\n [\n -130.78125,\n 50.51342652633956\n ],\n [\n -130.78125,\n 31.952162238024975\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-05","publicationStatus":"PW","scienceBaseUri":"5b46e56ee4b060350a15d159","contributors":{"authors":[{"text":"Parks, Sean","contributorId":205458,"corporation":false,"usgs":false,"family":"Parks","given":"Sean","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":737367,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holsinger, Lisa M.","contributorId":187607,"corporation":false,"usgs":false,"family":"Holsinger","given":"Lisa","email":"","middleInitial":"M.","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":737368,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Voss, Morgan","contributorId":205459,"corporation":false,"usgs":false,"family":"Voss","given":"Morgan","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":737369,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":false,"id":737366,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robinson, Nathaniel P.","contributorId":205461,"corporation":false,"usgs":false,"family":"Robinson","given":"Nathaniel","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":737370,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198110,"text":"70198110 - 2018 - Dissolved organic carbon and nitrogen release from boreal Holocene permafrost and seasonally frozen soils of Alaska","interactions":[],"lastModifiedDate":"2018-07-17T10:12:15","indexId":"70198110","displayToPublicDate":"2018-06-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Dissolved organic carbon and nitrogen release from boreal Holocene permafrost and seasonally frozen soils of Alaska","docAbstract":"

Permafrost (perennially frozen) soils store vast amounts of organic carbon (C) and nitrogen (N) that are vulnerable to mobilization as dissolved organic carbon (DOC) and dissolved organic and inorganic nitrogen (DON, DIN) upon thaw. Such releases will affect the biogeochemistry of permafrost regions, yet little is known about the chemical composition and source variability of active-layer (seasonally frozen) and permafrost soil DOC, DON and DIN. We quantified DOC, total dissolved N (TDN), DON, and DIN leachate yields from deep active-layer and near-surface boreal Holocene permafrost soils in interior Alaska varying in soil C and N content and radiocarbon age to determine potential release upon thaw. Soil cores were collected at three sites distributed across the Alaska boreal region in late winter, cut in 15 cm thick sections, and deep active-layer and shallow permafrost sections were thawed and leached. Leachates were analyzed for DOC, TDN, nitrate (NO3−), and ammonium (NH4 +) concentrations, dissolved organic matter optical properties, and DOC biodegradability. Soils were analyzed for C, N, and radiocarbon (14C) content. Soil DOC, TDN, DON, and DIN yields increased linearly with soil C and N content, and decreased with increasing radiocarbon age. These relationships were significantly different for active-layer and permafrost soils such that for a given soil C or N content, or radiocarbon age, permafrost soils released more DOC and TDN (mostly as DON) per gram soil than active-layer soils. Permafrost soil DOC biodegradability was significantly correlated with soil Δ14C and DOM optical properties. Our results demonstrate that near-surface Holocene permafrost soils preserve greater relative potential DOC and TDN yields than overlying seasonally frozen soils that are exposed to annual leaching and decomposition. While many factors control the fate of DOC and TDN, the greater relative yields from newly thawed Holocene permafrost soils will have the largest potential impact in areas dominated by organic-rich soils.

","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/aac4ad","usgsCitation":"Wickland, K.P., Waldrop, M.P., Aiken, G.R., Koch, J.C., Jorgenson, M., and Striegl, R.G., 2018, Dissolved organic carbon and nitrogen release from boreal Holocene permafrost and seasonally frozen soils of Alaska: Environmental Research Letters, v. 13, no. 6, p. 1-11, https://doi.org/10.1088/1748-9326/aac4ad.","productDescription":"Article 065011; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-093757","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468678,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aac4ad","text":"Publisher Index Page"},{"id":437875,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GG07SD","text":"USGS data release","linkHelpText":"Dissolved organic carbon and nitrogen release from boreal Holocene 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Torre","contributorId":140457,"corporation":false,"usgs":false,"family":"Jorgenson","given":"M. Torre","affiliations":[{"id":13506,"text":"Alaska Ecoscience","active":true,"usgs":false}],"preferred":false,"id":740065,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":740066,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197447,"text":"70197447 - 2018 - Ichthyophonus in sport-caught groundfishes from southcentral Alaska","interactions":[],"lastModifiedDate":"2018-06-05T10:23:29","indexId":"70197447","displayToPublicDate":"2018-06-05T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Ichthyophonus in sport-caught groundfishes from southcentral Alaska","title":"Ichthyophonus in sport-caught groundfishes from southcentral Alaska","docAbstract":"

This report of Ichthyophonus in common sport-caught fishes throughout the marine waters of southcentral Alaska represents the first documentation of natural Ichthyophonus infections in lingcod Ophiodon elongates and yelloweye rockfish Sebastes ruberrimus. In addition, the known geographic range of Ichthyophonus in black rockfish S. melanops has been expanded northward to include southcentral Alaska. Among all species surveyed, the infection prevalence was highest (35%, n = 334) in Pacific halibut Hippoglossus stenolepis. There were no gross indications of high-level infections or clinically diseased individuals. These results support the hypothesis that under typical conditions Ichthyophonus can occur at high infection prevalence accompanied with low-level infection among a variety of fishes throughout the eastern North Pacific Ocean, including southcentral Alaska.

","language":"English","publisher":"Inter-Research","doi":"10.3354/dao03218","usgsCitation":"Harris, B.P., Webster, S., Wolf, N., Gregg, J.L., and Hershberger, P., 2018, Ichthyophonus in sport-caught groundfishes from southcentral Alaska: Diseases of Aquatic Organisms, v. 128, no. 2, p. 169-173, https://doi.org/10.3354/dao03218.","productDescription":"5 p.","startPage":"169","endPage":"173","ipdsId":"IP-086885","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468684,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/dao03218","text":"Publisher Index Page"},{"id":354715,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -152,\n 59\n ],\n [\n -145,\n 59\n ],\n [\n -145,\n 61.5\n ],\n [\n -152,\n 61.5\n ],\n [\n -152,\n 59\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"128","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e574e4b060350a15d185","contributors":{"authors":[{"text":"Harris, Bradley P.","contributorId":205407,"corporation":false,"usgs":false,"family":"Harris","given":"Bradley","email":"","middleInitial":"P.","affiliations":[{"id":37100,"text":"Alaska Pacific University, Fisheries Aquatic Science and Technology (FAST) Laboratory 4101 University Drive, Anchorage, AK 99508","active":true,"usgs":false}],"preferred":false,"id":737189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webster, Sarah R.","contributorId":205408,"corporation":false,"usgs":false,"family":"Webster","given":"Sarah R.","affiliations":[{"id":37100,"text":"Alaska Pacific University, Fisheries Aquatic Science and Technology (FAST) Laboratory 4101 University Drive, Anchorage, AK 99508","active":true,"usgs":false}],"preferred":false,"id":737190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wolf, Nathan","contributorId":205409,"corporation":false,"usgs":false,"family":"Wolf","given":"Nathan","affiliations":[{"id":37100,"text":"Alaska Pacific University, Fisheries Aquatic Science and Technology (FAST) Laboratory 4101 University Drive, Anchorage, AK 99508","active":true,"usgs":false}],"preferred":false,"id":737191,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gregg, Jacob L. 0000-0001-5328-5482 jgregg@usgs.gov","orcid":"https://orcid.org/0000-0001-5328-5482","contributorId":203912,"corporation":false,"usgs":true,"family":"Gregg","given":"Jacob","email":"jgregg@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":737192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hershberger, Paul 0000-0002-2261-7760 phershberger@usgs.gov","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":150816,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","email":"phershberger@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":737188,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198673,"text":"70198673 - 2018 - Variation in age ratio of midcontinent greater white-fronted geese during fall migration","interactions":[],"lastModifiedDate":"2018-08-15T13:49:28","indexId":"70198673","displayToPublicDate":"2018-06-01T13:49:17","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Variation in age ratio of midcontinent greater white-fronted geese during fall migration","docAbstract":"

Annual productivity is an important parameter for the management of waterfowl populations. Fall age ratio (juveniles:total birds) is an index of productivity of the preceding breeding season. However, differences in the timing of migration between family groups and nonbreeding birds may bias age-ratio estimates. We examined temporal variation in age ratios of midcontinent greater white-fronted geese Anser albifrons frontalis from interior and northwestern Alaska at a northern autumn staging area near Delta Junction, Alaska. Photographic sampling conducted near Delta Junction resulted in an annual age ratio of 0.388 ± 0.004 (mean ± SE) in 2010 and 0.390 ± 0.001 in 2011. Our study demonstrated temporal variation in age ratios over the duration of the migration period during August and September. We recommend that sampling be conducted for 3-d periods at the beginning, middle, and end of the migration period to account for temporal variation in migration of family groups.

","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/112015-JFWM-117","usgsCitation":"Schock, W.G., Fischer, J., Ely, C.R., Stehn, R.A., Welker, J.M., and Causey, D., 2018, Variation in age ratio of midcontinent greater white-fronted geese during fall migration: Journal of Fish and Wildlife Management, v. 9, no. 1, p. 340-347, https://doi.org/10.3996/112015-JFWM-117.","productDescription":"8 p.","startPage":"340","endPage":"347","ipdsId":"IP-082512","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468698,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/112015-jfwm-117","text":"Publisher Index Page"},{"id":356516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-02","publicationStatus":"PW","scienceBaseUri":"5b98a2bae4b0702d0e842fc7","contributors":{"authors":[{"text":"Schock, Wade G.","contributorId":207040,"corporation":false,"usgs":false,"family":"Schock","given":"Wade","email":"","middleInitial":"G.","affiliations":[{"id":36971,"text":"University of Alaska","active":true,"usgs":false}],"preferred":false,"id":742516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fischer, Julian B.","contributorId":207042,"corporation":false,"usgs":false,"family":"Fischer","given":"Julian B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":742519,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ely, Craig R. 0000-0003-4262-0892 cely@usgs.gov","orcid":"https://orcid.org/0000-0003-4262-0892","contributorId":3214,"corporation":false,"usgs":true,"family":"Ely","given":"Craig","email":"cely@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":742515,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stehn, Robert A.","contributorId":83986,"corporation":false,"usgs":true,"family":"Stehn","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":742721,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welker, Jeffery M.","contributorId":43654,"corporation":false,"usgs":true,"family":"Welker","given":"Jeffery","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":742517,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Causey, Douglas","contributorId":207041,"corporation":false,"usgs":false,"family":"Causey","given":"Douglas","email":"","affiliations":[{"id":36971,"text":"University of Alaska","active":true,"usgs":false}],"preferred":false,"id":742518,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202651,"text":"70202651 - 2018 - A multi-species synthesis of satellite telemetry data in the Pacific Arctic (1987–2015): Overlap of marine mammal distributions and core use areas","interactions":[],"lastModifiedDate":"2019-03-15T10:55:23","indexId":"70202651","displayToPublicDate":"2018-06-01T10:55:17","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5536,"text":"Deep Sea Research Part II: Topical Studies in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"A multi-species synthesis of satellite telemetry data in the Pacific Arctic (1987–2015): Overlap of marine mammal distributions and core use areas","docAbstract":"

We collated available satellite telemetry data for six species of ice-associated marine mammals in the Pacific Arctic: ringed seals (Pusa hispida; n = 118), bearded seals(Erignathus barbatus, n = 51), spotted seals (Phoca largha, n = 72), Pacific walruses (Odobenus rosmarus divergens, n = 389); bowhead whales (Balaena mysticetus, n = 46), and five Arctic and sub-arctic stocks of beluga whales (Delphinapterus leucas, n = 103). We also included one seasonal resident, eastern North Pacific gray whales (Eschrichtius robustus, n = 12). This review summarized the distribution of daily locations from satellite-linked transmitters during two analysis periods, summer (May–November) and winter (December–April), and then examined the overlap among species. Six multi-species core use areas were identified during the summer period: 1) Chukotka/Bering Strait; 2) Norton Sound; 3) Kotzebue Sound; 4) the northeastern Chukchi Sea; 5) Mackenzie River Delta/Amundsen Gulf; and 6) Viscount Melville Sound. During the winter period, we identified four multi-species core use areas: 1) Anadyr Gulf/Strait; 2) central Bering Sea; 3) Nunivak Island; and 4) Bristol Bay. During the summer period, four of the six areas were centered on the greater Bering Strait region and the northwestern coast of Alaska and included most of the species we examined. The two remaining summer areas were in the western Canadian Arctic and were largely defined by the seasonal presence of Bering-Chukchi-Beaufort stock bowhead whales and Eastern Beaufort Sea stock beluga whales, whose distribution overlapped during both summer and winter periods. During the winter period, the main multi-species core use area was located near the Gulf of Anadyr and extended northwards through Anadyr and Bering Straits. This area is contained within the Bering Sea “green belt”, an area of enhanced primary and secondary productivity in the Bering Sea. We also described available telemetry data and where they can be found as of 2017. These data are important for understanding ice-associated marine mammal movements and habitat use in the Pacific Arctic and should be archived, with appropriate metadata, to ensure they are available for future retrospective analyses.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2018.02.006","usgsCitation":"Citta, J.J., Lowry, L., Quakenbush, L.T., Kelly, B.P., Fischbach, A., London, J.M., Jay, C.V., Frost, K.J., Crowe, G.O., Crawford, J.A., Boveng, P.L., Cameron, M., Von Duyke, A.L., Nelson, M., Harwood, L.A., Richard, P., Suydam, R., Heide-Jorgensen, M.P., Hobbs, R.C., Litovka, D.I., Marcoux, M., Whiting, A., Kennedy, A.S., George, J., Orr, J., and Gray, T., 2018, A multi-species synthesis of satellite telemetry data in the Pacific Arctic (1987–2015): Overlap of marine mammal distributions and core use areas: Deep Sea Research Part II: Topical Studies in Oceanography, v. 152, p. 132-153, https://doi.org/10.1016/j.dsr2.2018.02.006.","productDescription":"22 p.","startPage":"132","endPage":"153","ipdsId":"IP-086975","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":468707,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index 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ChukotTINRO","active":true,"usgs":false}],"preferred":false,"id":759364,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Marcoux, Marianne","contributorId":214216,"corporation":false,"usgs":false,"family":"Marcoux","given":"Marianne","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":759365,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Whiting, Alex","contributorId":214217,"corporation":false,"usgs":false,"family":"Whiting","given":"Alex","email":"","affiliations":[{"id":38998,"text":"Native Village of Kotzebue","active":true,"usgs":false}],"preferred":false,"id":759366,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Kennedy, Amy S.","contributorId":214218,"corporation":false,"usgs":false,"family":"Kennedy","given":"Amy","email":"","middleInitial":"S.","affiliations":[{"id":38999,"text":"Joint Institute for the Study of the Atmosphere and Ocean, University of Washington","active":true,"usgs":false}],"preferred":false,"id":759367,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"George, John C.","contributorId":201128,"corporation":false,"usgs":false,"family":"George","given":"John C.","affiliations":[],"preferred":false,"id":759368,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Orr, Jack","contributorId":214219,"corporation":false,"usgs":false,"family":"Orr","given":"Jack","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":759369,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Gray, Tom","contributorId":214220,"corporation":false,"usgs":false,"family":"Gray","given":"Tom","email":"","affiliations":[{"id":39000,"text":"Alaska Beluga Whale Committee","active":true,"usgs":false}],"preferred":false,"id":759370,"contributorType":{"id":1,"text":"Authors"},"rank":26}]}} ,{"id":70198672,"text":"70198672 - 2018 - Whole-genome analysis of Mustela erminea finds that pulsed hybridization impacts evolution at high latitudes","interactions":[],"lastModifiedDate":"2018-08-15T13:45:20","indexId":"70198672","displayToPublicDate":"2018-05-31T13:45:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5729,"text":"Communications Biology","active":true,"publicationSubtype":{"id":10}},"title":"Whole-genome analysis of Mustela erminea finds that pulsed hybridization impacts evolution at high latitudes","docAbstract":"

At high latitudes, climatic shifts hypothetically initiate recurrent episodes of divergence by isolating populations in glacial refugia—ice-free regions that enable terrestrial species persistence. Upon glacial recession, populations subsequently expand and often come into contact with other independently diverging populations, resulting in gene flow. To understand how recurrent periods of isolation and contact may have impacted evolution at high latitudes, we investigated introgression dynamics in the stoat (Mustela erminea), a Holarctic mammalian carnivore, using whole-genome sequences. We identify two spatio-temporally distinct episodes of introgression coincident with large-scale climatic shifts: contemporary introgression in a mainland contact zone and ancient contact ~200 km south of the contemporary zone, in the archipelagos along North America’s North Pacific Coast. Repeated episodes of gene flow highlight the central role of cyclic climates in structuring high-latitude diversity, through refugial divergence and introgressive hybridization. When introgression is followed by allopatric isolation (e.g., insularization) it may ultimately expedite divergence.

","language":"English","publisher":"Nature","doi":"10.1038/s42003-018-0058-y","usgsCitation":"Colella, J.P., Lan, T., Schuster, S.C., Talbot, S.L., Cook, J.A., and Lindqvist, C., 2018, Whole-genome analysis of Mustela erminea finds that pulsed hybridization impacts evolution at high latitudes: Communications Biology, v. 1, p. 1-10, https://doi.org/10.1038/s42003-018-0058-y.","productDescription":"Article number: 51; 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-087006","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468714,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s42003-018-0058-y","text":"Publisher Index Page"},{"id":356515,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-31","publicationStatus":"PW","scienceBaseUri":"5b98a2bbe4b0702d0e842fcd","contributors":{"authors":[{"text":"Colella, Jocelyn P.","contributorId":190332,"corporation":false,"usgs":false,"family":"Colella","given":"Jocelyn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":742510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lan, Tianying","contributorId":207037,"corporation":false,"usgs":false,"family":"Lan","given":"Tianying","email":"","affiliations":[{"id":37434,"text":"Department of Biological Scineces, State University of New York at Buffalo","active":true,"usgs":false}],"preferred":false,"id":742511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schuster, Stephen C.","contributorId":207039,"corporation":false,"usgs":false,"family":"Schuster","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":37435,"text":"Singapore Centre on Environmental Life Sciences Engineering","active":true,"usgs":false}],"preferred":false,"id":742513,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":742509,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cook, Joseph A.","contributorId":8323,"corporation":false,"usgs":false,"family":"Cook","given":"Joseph","email":"","middleInitial":"A.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":742514,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lindqvist, Charlotte","contributorId":207038,"corporation":false,"usgs":false,"family":"Lindqvist","given":"Charlotte","email":"","affiliations":[{"id":37434,"text":"Department of Biological Scineces, State University of New York at Buffalo","active":true,"usgs":false}],"preferred":false,"id":742512,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198335,"text":"70198335 - 2018 - Remotely sensing the morphometrics and dynamics of a cold region dune field using historical aerial photography and airborne LiDAR data","interactions":[],"lastModifiedDate":"2018-07-30T16:11:03","indexId":"70198335","displayToPublicDate":"2018-05-30T15:39:29","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Remotely sensing the morphometrics and dynamics of a cold region dune field using historical aerial photography and airborne LiDAR data","docAbstract":"

This study uses an airborne Light Detection and Ranging (LiDAR) survey, historical aerial photography and historical climate data to describe the character and dynamics of the Nogahabara Sand Dunes, a sub-Arctic dune field in interior Alaska’s discontinuous permafrost zone. The Nogahabara Sand Dunes consist of a 43-km2 area of active transverse and barchanoid dunes within a 3200-km2 area of vegetated dune and sand sheet deposits. The average dune height in the active portion of the dune field is 5.8 m, with a maximum dune height of 28 m. Dune spacing is variable with average crest-to-crest distances for select transects ranging from 66–132 m. Between 1952 and 2015, dunes migrated at an average rate of 0.52 m a−1. Dune movement was greatest between 1952 and 1978 (0.68 m a−1) and least between 1978 and 2015 (0.43 m a−1). Dunes migrated predominantly to the southeast; however, along the dune field margin, net migration was towards the edge of the dune field regardless of heading. Better constraining the processes controlling dune field dynamics at the Nogahabara dunes would provide information that can be used to model possible reactivation of more northerly dune fields and sand sheets in response to climate change, shifting fire regimes and permafrost thaw.

","language":"English","publisher":"Multidisciplinary Digital Publishing Institute","doi":"10.3390/rs10050792","usgsCitation":"Baughman, C., Jones, B.M., Bodony, K.L., Mann, D.H., Larsen, C.F., Himmelstoss, E., and Smith, J., 2018, Remotely sensing the morphometrics and dynamics of a cold region dune field using historical aerial photography and airborne LiDAR data: Remote Sensing, v. 10, no. 5, p. 1-19, https://doi.org/10.3390/rs10050792.","productDescription":"Article 792; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-082492","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468719,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs10050792","text":"Publisher Index Page"},{"id":356010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"5","noUsgsAuthors":false,"publicationDate":"2018-05-19","publicationStatus":"PW","scienceBaseUri":"5b6fc444e4b0f5d57878ea3b","contributors":{"authors":[{"text":"Baughman, Carson 0000-0002-9423-9324 cbaughman@usgs.gov","orcid":"https://orcid.org/0000-0002-9423-9324","contributorId":169657,"corporation":false,"usgs":true,"family":"Baughman","given":"Carson","email":"cbaughman@usgs.gov","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":741101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":741124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bodony, Karin L.","contributorId":206563,"corporation":false,"usgs":false,"family":"Bodony","given":"Karin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":741125,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mann, Daniel H.","contributorId":67010,"corporation":false,"usgs":true,"family":"Mann","given":"Daniel","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":741126,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Larsen, Christopher F.","contributorId":147408,"corporation":false,"usgs":false,"family":"Larsen","given":"Christopher","email":"","middleInitial":"F.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":741127,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Himmelstoss, Emily A. ehimmelstoss@usgs.gov","contributorId":2508,"corporation":false,"usgs":true,"family":"Himmelstoss","given":"Emily A.","email":"ehimmelstoss@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":741128,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Jeremy","contributorId":62919,"corporation":false,"usgs":true,"family":"Smith","given":"Jeremy","affiliations":[],"preferred":false,"id":741129,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70200590,"text":"70200590 - 2018 - The Mystic subterrane (partly) demystified: New data from the Farewell terrane and adjacent rocks, interior Alaska","interactions":[],"lastModifiedDate":"2018-10-25T11:50:24","indexId":"70200590","displayToPublicDate":"2018-05-30T11:50:16","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"The Mystic subterrane (partly) demystified: New data from the Farewell terrane and adjacent rocks, interior Alaska","docAbstract":"

The youngest part of the Farewell terrane in interior Alaska (USA) is the enigmatic Devonian–Cretaceous Mystic subterrane. New U-Pb detrital zircon, fossil, geochemical, neodymium isotopic, and petrographic data illuminate the origin of the rocks of this subterrane. The Devonian–Permian Sheep Creek Formation yielded youngest detrital zircons of Devonian age, major detrital zircon age probability peaks between ca. 460 and 405 Ma, and overall age spectra like those from the underlying Dillinger subterrane. Samples are sandstones rich in sedimentary lithic clasts, and differ from approximately coeval strata to the east that have abundant volcanic lithic clasts and late Paleozoic detrital zircons. The Permian Mount Dall conglomerate has mainly carbonate and chert clasts and yielded youngest detrital zircons of latest Pennsylvanian age. Permian quartz-carbonate sandstone in the northern Farewell terrane yielded abundant middle to late Permian detrital zircons.

Late Triassic–Early Jurassic mafic igneous rocks occur in the central and eastern Mystic subterrane. New whole-rock geochemical and isotopic data indicate that magmas were rift related and derived from subcontinental mantle. Triassic and Jurassic strata have detrital zircon age spectra much like those of the Sheep Creek Formation, with major age populations between ca. 430 and 410 Ma. These rocks include conglomerate with clasts of carbonate ± chert and youngest detrital zircons of Late Triassic age and quartz-carbonate sandstone with youngest detrital zircons of Early Jurassic age. Lithofacies indicating highly productive oceanographic conditions (upwelling?) bracket the main part of the Mystic succession: Upper Devonian bedded barite and phosphatic Upper Devonian and Lower Jurassic rocks.

The youngest part of the Mystic subterrane consists of Lower Cretaceous (Valanginian–Aptian) limestone, calcareous sandstone, and related strata. These rocks are partly coeval with the oldest parts of the Kahiltna assemblage, an overlap succession exposed along the southern margin of the Farewell terrane.

Our findings support previous models suggesting that the Farewell terrane was proximal to the Alexander-Wrangellia-Peninsular composite terrane during the late Paleozoic, and further suggest that such proximity continued into (or recurred during) the Late Triassic–Early Jurassic. But middle to late Permian detrital zircons in northern Farewell require another source; the Yukon-Tanana terrane is one possibility.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01588.1","usgsCitation":"Dumoulin, J.A., Jones, J.V., Box, S.E., Bradley, D., Ayuso, R.A., and O’Sullivan, P.B., 2018, The Mystic subterrane (partly) demystified: New data from the Farewell terrane and adjacent rocks, interior Alaska: Geosphere, v. 14, no. 4, p. 1501-1543, https://doi.org/10.1130/GES01588.1.","productDescription":"43 p.","startPage":"1501","endPage":"1543","ipdsId":"IP-095640","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":468720,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01588.1","text":"Publisher Index Page"},{"id":437889,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7765DN7","text":"USGS data release","linkHelpText":"U-Pb Isotopic Data and Ages of Detrital Zircon Grains, Whole Rock Major and Trace-element Geochemistry, and Whole Rock Isotopic Data from Selected Rocks from the Western Alaska Range, Medfra area, and Livengood area, Alaska"},{"id":358807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"14","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-30","publicationStatus":"PW","scienceBaseUri":"5c10a9abe4b034bf6a7e53b3","contributors":{"authors":[{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":749660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, James V. III 0000-0002-6602-5935 jvjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6602-5935","contributorId":201245,"corporation":false,"usgs":true,"family":"Jones","given":"James","suffix":"III","email":"jvjones@usgs.gov","middleInitial":"V.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":749661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Box, Stephen E. 0000-0002-5268-8375 sbox@usgs.gov","orcid":"https://orcid.org/0000-0002-5268-8375","contributorId":1843,"corporation":false,"usgs":true,"family":"Box","given":"Stephen","email":"sbox@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":749662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradley, Dwight 0000-0001-9116-5289 bradleyorchard2@gmail.com","orcid":"https://orcid.org/0000-0001-9116-5289","contributorId":2358,"corporation":false,"usgs":true,"family":"Bradley","given":"Dwight","email":"bradleyorchard2@gmail.com","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ayuso, Robert A. 0000-0002-8496-9534 rayuso@usgs.gov","orcid":"https://orcid.org/0000-0002-8496-9534","contributorId":2654,"corporation":false,"usgs":true,"family":"Ayuso","given":"Robert","email":"rayuso@usgs.gov","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":749664,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Sullivan, Paul B.","contributorId":193544,"corporation":false,"usgs":false,"family":"O’Sullivan","given":"Paul","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":749665,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70237793,"text":"70237793 - 2018 - Tundra be dammed: Beaver colonization of the Arctic","interactions":[],"lastModifiedDate":"2022-10-24T15:32:03.784703","indexId":"70237793","displayToPublicDate":"2018-05-30T10:29:12","publicationYear":"2018","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":"Tundra be dammed: Beaver colonization of the Arctic","docAbstract":"

Increasing air temperatures are changing the arctic tundra biome. Permafrost is thawing, snow duration is decreasing, shrub vegetation is proliferating, and boreal wildlife is encroaching. Here we present evidence of the recent range expansion of North American beaver (Castor canadensis) into the Arctic, and consider how this ecosystem engineer might reshape the landscape, biodiversity, and ecosystem processes. We developed a remote sensing approach that maps formation and disappearance of ponds associated with beaver activity. Since 1999, 56 new beaver pond complexes were identified, indicating that beavers are colonizing a predominantly tundra region (18,293 km2) of northwest Alaska. It is unclear how improved tundra stream habitat, population rebound following overtrapping for furs, or other factors are contributing to beaver range expansion. We discuss rates and likely routes of tundra beaver colonization, as well as effects on permafrost, stream ice regimes, and freshwater and riparian habitat. Beaver ponds and associated hydrologic changes are thawing permafrost. Pond formation increases winter water temperatures in the pond and downstream, likely creating new and more varied aquatic habitat, but specific biological implications are unknown. Beavers create dynamic wetlands and are agents of disturbance that may enhance ecosystem responses to warming in the Arctic.

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.14332","usgsCitation":"Tape, K.D., Jones, B.M., Arp, C.D., Nitze, I., and Grosse, G., 2018, Tundra be dammed: Beaver colonization of the Arctic: Global Change Biology, v. 24, no. 10, p. 4478-4488, https://doi.org/10.1111/gcb.14332.","productDescription":"11 p.","startPage":"4478","endPage":"4488","ipdsId":"IP-090358","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":468721,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://epic.awi.de/id/eprint/47723/1/Tape_etal_2018.pdf","text":"External Repository"},{"id":408648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Lower Noatak River, Wulik, and Kivalina River watersheds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -166.63101775418127,\n 68.8694953372669\n ],\n [\n -166.63101775418127,\n 66.85108524558379\n ],\n [\n -160.3609756043501,\n 66.85108524558379\n ],\n [\n -160.3609756043501,\n 68.8694953372669\n ],\n [\n -166.63101775418127,\n 68.8694953372669\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"24","issue":"10","noUsgsAuthors":false,"publicationDate":"2018-06-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Tape, Ken D.","contributorId":297109,"corporation":false,"usgs":false,"family":"Tape","given":"Ken","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":855655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":855656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":855657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nitze, Ingemar","contributorId":298467,"corporation":false,"usgs":false,"family":"Nitze","given":"Ingemar","email":"","affiliations":[{"id":62783,"text":"Alfred Wegener Institute","active":true,"usgs":false}],"preferred":false,"id":855658,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grosse, Guido","contributorId":146182,"corporation":false,"usgs":false,"family":"Grosse","given":"Guido","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":855659,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198755,"text":"70198755 - 2018 - The role of environmental driving factors in historical and projected carbon dynamics of wetland ecosystems in Alaska","interactions":[],"lastModifiedDate":"2022-04-22T16:31:43.931967","indexId":"70198755","displayToPublicDate":"2018-05-29T10:07:39","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"The role of environmental driving factors in historical and projected carbon dynamics of wetland ecosystems in Alaska","docAbstract":"

Wetlands are critical terrestrial ecosystems in Alaska, covering ~177,000 km2, an area greater than all the wetlands in the remainder of the United States. To assess the relative influence of changing climate, atmospheric carbon dioxide (CO2) concentration, and fire regime on carbon balance in wetland ecosystems of Alaska, a modeling framework that incorporates a fire disturbance model and two biogeochemical models was used. Spatially explicit simulations were conducted at 1‐km resolution for the historical period (1950–2009) and future projection period (2010–2099). Simulations estimated that wetland ecosystems of Alaska lost 175 Tg carbon (C) in the historical period. Ecosystem C storage in 2009 was 5,556 Tg, with 89% of the C stored in soils. The estimated loss of C as CO2 and biogenic methane (CH4) emissions resulted in wetlands of Alaska increasing the greenhouse gas forcing of climate warming. Simulations for the projection period were conducted for six climate change scenarios constructed from two climate models forced under three CO2 emission scenarios. Ecosystem C storage averaged among climate scenarios increased 3.94 Tg C/yr by 2099, with variability among the simulations ranging from 2.02 to 4.42 Tg C/yr. These increases were driven primarily by increases in net primary production (NPP) that were greater than losses from increased decomposition and fire. The NPP increase was driven by CO2 fertilization (~5% per 100 parts per million by volume increase) and by increases in air temperature (~1% per °C increase). Increases in air temperature were estimated to be the primary cause for a projected 47.7% mean increase in biogenic CH4 emissions among the simulations (~15% per °C increase). Ecosystem CO2 sequestration offset the increase in CH4 emissions during the 21st century to decrease the greenhouse gas forcing of climate warming. However, beyond 2100, we expect that this forcing will ultimately increase as wetland ecosystems transition from being a sink to a source of atmospheric CO2 because of (1) decreasing sensitivity of NPP to increasing atmospheric CO2, (2) increasing availability of soil C for decomposition as permafrost thaws, and (3) continued positive sensitivity of biogenic CH4 emissions to increases in soil temperature.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1755","usgsCitation":"Lyu, Z., Genet, H., He, Y., Zhuang, Q., McGuire, A.D., Bennett, A., Breen, A., Clein, J., Euskirchen, E.S., Johnson, K., Kurkowski, T., Pastick, N.J., Rupp, T.S., Wylie, B.K., and Zhu, Z., 2018, The role of environmental driving factors in historical and projected carbon dynamics of wetland ecosystems in Alaska: Ecological Applications, v. 28, no. 6, p. 1377-1395, https://doi.org/10.1002/eap.1755.","productDescription":"19 p.","startPage":"1377","endPage":"1395","ipdsId":"IP-091563","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":490053,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1457077","text":"External 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Loess is widespread over Alaska, and its accumulation has traditionally been associated with glacial periods. Surprisingly, loess deposits securely dated to the last glacial period are rare in Alaska, and paleowind reconstructions for this time period are limited to inferences from dune orientations. We report a rare occurrence of loess deposits dating to the last glacial period, ~19 ka to ~12 ka, in the Yukon-Tanana Upland. Loess in this area is very coarse grained (abundant coarse silt), with decreases in particle size moving south of the Yukon River, implying that the drainage basin of this river was the main source. Geochemical data show, however, that the Tanana River valley to the south is also a likely distal source. The occurrence of last-glacial loess with sources to both the south and north is explained by both regional, synoptic-scale winds from the northeast and opposing katabatic winds that could have developed from expanded glaciers in both the Brooks Range to the north and the Alaska Range to the south. Based on a comparison with recent climate modeling for the last glacial period, seasonality of dust transport may also have played a role in bringing about contributions from both northern and southern sources.

","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2018.11","usgsCitation":"Muhs, D., Pigati, J.S., Budahn, J.R., Skipp, G.L., Bettis, E.A., and Jensen, B., 2018, Origin of last-glacial loess in the western Yukon-Tanana Upland, central Alaska, USA: Quaternary Research, v. 89, no. 3, p. 797-819, https://doi.org/10.1017/qua.2018.11.","productDescription":"23 p.","startPage":"797","endPage":"819","ipdsId":"IP-086762","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":354407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150,\n 65.5\n ],\n [\n -148.75,\n 65.5\n ],\n [\n -148.75,\n 66\n ],\n [\n -150,\n 66\n ],\n [\n -150,\n 65.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"89","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-10","publicationStatus":"PW","scienceBaseUri":"5b155d78e4b092d9651e1b3e","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":168575,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel R.","email":"dmuhs@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":736257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":201167,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey","email":"jpigati@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":736258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Budahn, James R. 0000-0001-9794-8882 jbudahn@usgs.gov","orcid":"https://orcid.org/0000-0001-9794-8882","contributorId":1175,"corporation":false,"usgs":true,"family":"Budahn","given":"James","email":"jbudahn@usgs.gov","middleInitial":"R.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":736259,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skipp, Gary L. 0000-0002-9404-0980","orcid":"https://orcid.org/0000-0002-9404-0980","contributorId":201777,"corporation":false,"usgs":true,"family":"Skipp","given":"Gary","email":"","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":736260,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bettis, E. Arthur III 0000-0002-6137-1433","orcid":"https://orcid.org/0000-0002-6137-1433","contributorId":204005,"corporation":false,"usgs":false,"family":"Bettis","given":"E.","suffix":"III","email":"","middleInitial":"Arthur","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":736261,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jensen, Britta","contributorId":184164,"corporation":false,"usgs":false,"family":"Jensen","given":"Britta","affiliations":[],"preferred":false,"id":736262,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197221,"text":"70197221 - 2018 - Enhancement of a parsimonious water balance model to simulate surface hydrology in a glacierized watershed","interactions":[],"lastModifiedDate":"2018-10-11T15:00:36","indexId":"70197221","displayToPublicDate":"2018-05-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Enhancement of a parsimonious water balance model to simulate surface hydrology in a glacierized watershed","docAbstract":"

The U.S. Geological Survey monthly water balance model (MWBM) was enhanced with the capability to simulate glaciers in order to make it more suitable for simulating cold region hydrology. The new model, MWBMglacier, is demonstrated in the heavily glacierized and ecologically important Copper River watershed in Southcentral Alaska. Simulated water budget components compared well to satellite‐based observations and ground measurements of streamflow, evapotranspiration, snow extent, and total water storage, with differences ranging from 0.2% to 7% of the precipitation flux. Nash Sutcliffe efficiency for simulated and observed streamflow was greater than 0.8 for six of eight stream gages. Snow extent matched satellite‐based observations with Nash Sutcliffe efficiency values of greater than 0.89 in the four Copper River ecoregions represented. During the simulation period 1949 to 2009, glacier ice melt contributed 25% of total runoff, ranging from 12% to 45% in different tributaries, and glacierized area was reduced by 6%. Statistically significant (p < 0.05) decreasing and increasing trends in annual glacier mass balance occurred during the multidecade cool and warm phases of the Pacific Decadal Oscillation, respectively, reinforcing the link between climate perturbations and glacier mass balance change. The simulations of glaciers and total runoff for a large, remote region of Alaska provide useful data to evaluate hydrologic, cryospheric, ecologic, and climatic trends. MWBM glacier is a valuable tool to understand when, and to what extent, streamflow may increase or decrease as glaciers respond to a changing climate.

","language":"English","publisher":"AGU","doi":"10.1029/2017JF004482","usgsCitation":"Valentin, M.M., Viger, R.J., Van Beusekom, A.E., Hay, L.E., Hogue, T.S., and Foks, N.L., 2018, Enhancement of a parsimonious water balance model to simulate surface hydrology in a glacierized watershed: Journal of Geophysical Research F: Earth Surface, v. 123, no. 5, p. 1116-1132, https://doi.org/10.1029/2017JF004482.","productDescription":"17 p.","startPage":"1116","endPage":"1132","ipdsId":"IP-094374","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":468839,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017jf004482","text":"Publisher Index Page"},{"id":354424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-23","publicationStatus":"PW","scienceBaseUri":"5b155d78e4b092d9651e1b3c","contributors":{"authors":[{"text":"Valentin, Melissa M.","contributorId":205172,"corporation":false,"usgs":false,"family":"Valentin","given":"Melissa","email":"","middleInitial":"M.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":736281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":147818,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":false,"id":736280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Beusekom, Ashley E. 0000-0002-6996-978X beusekom@usgs.gov","orcid":"https://orcid.org/0000-0002-6996-978X","contributorId":3992,"corporation":false,"usgs":true,"family":"Van Beusekom","given":"Ashley","email":"beusekom@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":736282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":736283,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hogue, Terri S.","contributorId":205175,"corporation":false,"usgs":false,"family":"Hogue","given":"Terri","email":"","middleInitial":"S.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":736284,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foks, Nathan Leon","contributorId":194012,"corporation":false,"usgs":false,"family":"Foks","given":"Nathan","email":"","middleInitial":"Leon","affiliations":[],"preferred":false,"id":736285,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70200455,"text":"70200455 - 2018 - Alaska snowpack response to climate change: Statewide snowfall equivalent and snowpack water scenarios","interactions":[],"lastModifiedDate":"2018-10-18T13:45:55","indexId":"70200455","displayToPublicDate":"2018-05-22T13:45:44","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Alaska snowpack response to climate change: Statewide snowfall equivalent and snowpack water scenarios","docAbstract":"

Climatically driven changes in snow characteristics (snowfall, snowpack, and snowmelt) will affect hydrologic and ecological systems in Alaska over the coming century, yet there exist no projections of downscaled future snow pack metrics for the state of Alaska. We updated historical and projected snow day fraction (PSF, the fraction of days with precipitation falling as snow) from McAfee et al. We developed modeled snowfall equivalent (SFE) derived from the product of snow-day fraction (PSF) and existing gridded precipitation for Alaska from Scenarios Network for Alaska and Arctic Planning (SNAP). We validated the assumption that modeled SFE approximates historical decadally averaged snow water equivalent (SWE) observations from snowcourse and Snow Telemetry (SNOTEL) sites. We present analyses of future downscaled PSF and two new products, October–March SFE and ratio of snow fall equivalent to precipitation (SFE:P) based on bias-corrected statistically downscaled projections of Coupled Model Intercomparison Project 5 (CMIP5) Global Climate Model (GCM) temperature and precipitation for the state of Alaska. We analyzed mid-century (2040–2069) and late-century (2070–2099) changes in PSF, SFE, and SFE:P relative to historical (1970–1999) mean temperature and present results for Alaska climate divisions and 12-digit Hydrologic Unit Code (HUC12) watersheds. Overall, estimated historical the SFE is reasonably well related to the observed SWE, with correlations over 0.75 in all decades, and correlations exceeding 0.9 in the 1960s and 1970s. In absolute terms, SFE is generally biased low compared to the observed SWE. PSF and SFE:P decrease universally across Alaska under both Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 emissions scenarios, with the smallest changes for RCP 4.5 in 2040–2069 and the largest for RCP 8.5 in 2070–2099. The timing and magnitude of maximum decreases in PSF vary considerably with regional average temperature, with the largest changes in months at the beginning and end of the snow season. Mean SFE changes vary widely among climate divisions, ranging from decreases between −17 and −58% for late twenty-first century in southeast, southcentral, west coast and southwest Alaska to increases up to 21% on the North Slope. SFE increases most at highest elevations and latitudes and decreases most in coastal southern Alaska. SFE:P ratios indicate a broad switch from snow-dominated to transitional annual hydrology across most of southern Alaska by mid-century, and from transitional to rain-dominated watersheds in low elevation parts of southeast Alaska by the late twenty-first century. 

","language":"English","publisher":"MDPI","doi":"10.3390/w10050668","usgsCitation":"Littell, J., McAfee, S., and Hayward, G.D., 2018, Alaska snowpack response to climate change: Statewide snowfall equivalent and snowpack water scenarios: Water, v. 10, no. 5, p. 1-16, https://doi.org/10.3390/w10050668.","productDescription":"Article 668; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-097141","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"links":[{"id":468739,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w10050668","text":"Publisher Index Page"},{"id":358537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"10","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-22","publicationStatus":"PW","scienceBaseUri":"5c10a9b9e4b034bf6a7e5403","contributors":{"authors":[{"text":"Littell, Jeremy S. 0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":205907,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":748948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAfee, Stephanie A.","contributorId":167115,"corporation":false,"usgs":false,"family":"McAfee","given":"Stephanie A.","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":748949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayward, Gregory D.","contributorId":209846,"corporation":false,"usgs":false,"family":"Hayward","given":"Gregory","email":"","middleInitial":"D.","affiliations":[{"id":38010,"text":"US Forest Service, Alaska Region","active":true,"usgs":false}],"preferred":false,"id":748950,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197094,"text":"70197094 - 2018 - Design considerations for estimating survival rates with standing age structures","interactions":[],"lastModifiedDate":"2018-05-17T13:03:10","indexId":"70197094","displayToPublicDate":"2018-05-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Design considerations for estimating survival rates with standing age structures","docAbstract":"Survival rate estimates are critical to understanding the dynamics and status of a population, and\nthey are often inferred from samples of the population’s age structure. A recently developed method uses time\nseries of standing age-structure data with information about population growth rate or fecundity to provide\nexplicit maximum likelihood estimators of age-specific survival rates, without assuming population stability or\nstationarity. We explored properties of these estimators and determined sample size requirements for the\nestimators to achieve desired levels of precision, limit bias, and limit the probability a rate will be inestimable or\nits estimate inadmissible (>1).We show that estimating combined rates for adjacent age classes is an effective\nmethod of overcoming sensitivity to sampling noise in situations where collecting a larger sample of data is not\nfeasible.","language":"English","publisher":"Wiley","doi":"10.1002/wsb.858","usgsCitation":"Taylor, R.L., and Udevitz, M.S., 2018, Design considerations for estimating survival rates with standing age structures: Wildlife Society Bulletin, v. 42, no. 1, p. 32-39, https://doi.org/10.1002/wsb.858.","productDescription":"8 p.","startPage":"32","endPage":"39","ipdsId":"IP-087500","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":468749,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doaj.org/article/4c029ee673ec49f1acfa3af7a5df9962","text":"Publisher Index Page"},{"id":354264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","scienceBaseUri":"5afee6b7e4b0da30c1bfbd5c","contributors":{"authors":[{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":735565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Udevitz, Mark S. 0000-0003-4659-138X mudevitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4659-138X","contributorId":3189,"corporation":false,"usgs":true,"family":"Udevitz","given":"Mark","email":"mudevitz@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":735566,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197007,"text":"70197007 - 2018 - Generalist feeding strategies in Arctic freshwater fish: A mechanism for dealing with extreme environments","interactions":[],"lastModifiedDate":"2018-06-12T14:04:32","indexId":"70197007","displayToPublicDate":"2018-05-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Generalist feeding strategies in Arctic freshwater fish: A mechanism for dealing with extreme environments","docAbstract":"

Generalist feeding strategies are favoured in stressful or variable environments where flexibility in ecological traits is beneficial. Species that feed across multiple habitat types and trophic levels may impart stability on food webs through the use of readily available, alternative energy pools. In lakes, generalist fish species may take advantage of spatially and temporally variable prey by consuming both benthic and pelagic prey to meet their energy demands. Using stomach content and stable isotope analyses, we examined the feeding habits of fish species in Alaska's Arctic Coastal Plain (ACP) lakes to determine the prevalence of generalist feeding strategies as a mechanism for persistence in extreme environments (e.g. low productivity, extreme cold and short growing season). Generalist and flexible feeding strategies were evident in five common fish species. Fish fed on benthic and pelagic (or nektonic) prey and across trophic levels. Three species were clearly omnivorous, feeding on fish and their shared invertebrate prey. Dietary differences based on stomach content analysis often exceeded 70%, and overlap in dietary niches based on shared isotopic space varied from zero to 40%. Metrics of community‐wide trophic structure varied with the number and identity of species involved and on the dietary overlap and niche size of individual fishes. Accumulation of energy from shared carbon sources by Arctic fishes creates redundancy in food webs, increasing likely resistance to perturbations or stochastic events. Therefore, the generalist and omnivorous feeding strategies employed by ACP fish may maintain energy flow and food web stability in extreme environments.

","language":"English","publisher":"Wiley","doi":"10.1111/eff.12391","usgsCitation":"Laske, S.M., Rosenberger, A.E., Wipfli, M.S., and Zimmerman, C.E., 2018, Generalist feeding strategies in Arctic freshwater fish: A mechanism for dealing with extreme environments: Ecology of Freshwater Fish, v. 27, no. 3, p. 767-784, https://doi.org/10.1111/eff.12391.","productDescription":"18 p.","startPage":"767","endPage":"784","ipdsId":"IP-088949","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":437892,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TQ60CH","text":"USGS data release","linkHelpText":"Fish Species Composition and Diet Information in Lakes of the Arctic Coastal Plain, Alaska, 2011-2013"},{"id":354274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-08","publicationStatus":"PW","scienceBaseUri":"5afee6b9e4b0da30c1bfbd6a","contributors":{"authors":[{"text":"Laske, Sarah M. 0000-0002-6096-0420 slaske@usgs.gov","orcid":"https://orcid.org/0000-0002-6096-0420","contributorId":204872,"corporation":false,"usgs":true,"family":"Laske","given":"Sarah","email":"slaske@usgs.gov","middleInitial":"M.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"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":735291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":735292,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":735293,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":735290,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197057,"text":"70197057 - 2018 - A rapid assessment method to estimate the distribution of juvenile Chinook Salmon in tributary habitats using eDNA and occupancy estimation","interactions":[],"lastModifiedDate":"2018-05-17T14:57:44","indexId":"70197057","displayToPublicDate":"2018-05-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"A rapid assessment method to estimate the distribution of juvenile Chinook Salmon in tributary habitats using eDNA and occupancy estimation","docAbstract":"

Identification and protection of water bodies used by anadromous species are critical in light of increasing threats to fish populations, yet often challenging given budgetary and logistical limitations. Noninvasive, rapid‐assessment, sampling techniques may reduce costs and effort while increasing species detection efficiencies. We used an intrinsic potential (IP) habitat model to identify high‐quality rearing habitats for Chinook Salmon Oncorhynchus tshawytscha and select sites to sample throughout the Chena River basin, Alaska, for juvenile occupancy using an environmental DNA (eDNA) approach. Water samples were collected from 75 tributary sites in 2014 and 2015. The presence of Chinook Salmon DNA in water samples was assessed using a species‐specific quantitative PCR (qPCR) assay. The IP model predicted over 900 stream kilometers in the basin to support high‐quality (IP ≥ 0.75) rearing habitat. Occupancy estimation based on eDNA samples indicated that 80% and 56% of previously unsampled sites classified as high or low IP (IP < 0.75), respectively, were occupied. The probability of detection (p) of Chinook Salmon DNA from three replicate water samples was high (p = 0.76) but varied with drainage area (km2). A power analysis indicated high power to detect proportional changes in occupancy based on parameter values estimated from eDNA occupancy models, although power curves were not symmetrical around zero, indicating greater power to detect positive than negative proportional changes in occupancy. Overall, the combination of IP habitat modeling and occupancy estimation provided a useful, rapid‐assessment method to predict and subsequently quantify the distribution of juvenile salmon in previously unsampled tributary habitats. Additionally, these methods are flexible and can be modified for application to other species and in other locations, which may contribute towards improved population monitoring and management.

","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10014","usgsCitation":"Matter, A., Falke, J.A., Lopez, J.A., and Savereide, J.W., 2018, A rapid assessment method to estimate the distribution of juvenile Chinook Salmon in tributary habitats using eDNA and occupancy estimation: North American Journal of Fisheries Management, v. 38, no. 1, p. 223-236, https://doi.org/10.1002/nafm.10014.","productDescription":"14 p.","startPage":"223","endPage":"236","ipdsId":"IP-082148","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chena River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -152.34741210937497,\n 62.935234870604695\n ],\n [\n -143.2177734375,\n 62.935234870604695\n ],\n [\n -143.2177734375,\n 66.08491099733617\n ],\n [\n -152.34741210937497,\n 66.08491099733617\n ],\n [\n -152.34741210937497,\n 62.935234870604695\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-11","publicationStatus":"PW","scienceBaseUri":"5afee6b9e4b0da30c1bfbd66","contributors":{"authors":[{"text":"Matter, A.","contributorId":68879,"corporation":false,"usgs":true,"family":"Matter","given":"A.","email":"","affiliations":[],"preferred":false,"id":735707,"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":735390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lopez, J. Andres","contributorId":14306,"corporation":false,"usgs":true,"family":"Lopez","given":"J.","email":"","middleInitial":"Andres","affiliations":[],"preferred":false,"id":735708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Savereide, James W.","contributorId":204591,"corporation":false,"usgs":false,"family":"Savereide","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":735709,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}