Todd Atwood, Ph.D.
Spatial ecology, population ecology, predator-prey dynamics, polar bear ecology
Professional Experience
2012 - Present Research Wildlife Biologist and Project Leader, USGS Alaska Science Center, Anchorage, AK
2008 - 2012 Research Wildlife Biologist, USDA/APHIS/WS/National Wildlife Research Center, Fort Collins, CO
2006 - 2008 Research Biologist, Research Branch, Arizona Game and Fish Department, Phoenix, AZ
2006 Biological Technician, USDA/National Wildlife Research Center, Fort Collins, CO
Education and Certifications
Ph.D. 2006 Utah State University Wildlife Biology
M.S. 2002 Purdue University Wildlife Ecology
B.S. 1999 Purdue University Wildlife Ecology
Affiliations and Memberships*
The Wildlife Society
International Association for Bear Research and Management
American Society of Mammalogists
Science and Products
Serum Urea and Creatinine Levels of Spring-Caught Polar Bears (Ursus maritimus) in the Southern Beaufort and Chukchi Seas
Multistate capture and search data from the southern Beaufort Sea polar bear population in Alaska, 2001-2016
Polar Bear Microsatellite Data Southern Beaufort Sea 2010-2013
Polar Bear Hair Mercury Concentrations Southern Beaufort Sea 2004-2011
Satellite Location and Tri-axial Accelerometer Data from Adult Female Polar Bears (Ursus maritimus) in the Southern Beaufort Sea, April-October 2014
Locations Collected 1985-2015 from Female Polar Bears (Ursus maritimus) with Dependent Young Instrumented in the Southern Beaufort Sea with Satellite-linked Transmitters by the USGS
Serological Data on Influenza A from Birds and Mammals on the Arctic Coastal Plain of Northern Alaska, 2011-2017
U.S. Geological Survey Polar Bear Mark-Recapture Records, Alaska Portion of the Southern Beaufort Sea, 2001-2010
Observed and forecasted changes in land use by polar bears in the Beaufort and Chukchi Seas, 1985–2040
A serological survey of Francisella tularensis exposure in wildlife on the Arctic Coastal Plain of Alaska
Pleistocene–Holocene vicariance, not Anthropocene landscape change, explains the genetic structure of American black bear (Ursus americanus) populations in the American Southwest and northern Mexico
Diet energy density estimated from isotopes in predator hair associated with survival, habitat, and population dynamics
Modeling the spatial and temporal dynamics of land-based polar bear denning in Alaska
Comparisons of Coupled Model Intercomparison Project Phase 5 (CMIP5) and Coupled Model Intercomparison Project Phase 6 (CMIP6) sea-ice projections in polar bear (Ursus maritimus) ecoregions during the 21st century
Using in situ/ex situ research collaborations to support polar bear conservation
Evaluating the efficacy of aerial infrared surveys to detect artificial polar bear dens
Marine mammal hotspots across the circumpolar Arctic
The role of satellite telemetry data in 21st century conservation of polar bears (Ursus maritimus)
Distinct gut microbiomes in two polar bear subpopulations inhabiting different sea ice ecoregions
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Science and Products
- Science
- Data
Filter Total Items: 20
Serum Urea and Creatinine Levels of Spring-Caught Polar Bears (Ursus maritimus) in the Southern Beaufort and Chukchi Seas
These data are serum urea nitrogen and creatinine levels for polar bears captured in the southern Beaufort Sea 1983-2016 and the Chukchi Sea 1987-1993 and 2008-2017. The dataset includes relevant information about the bears that were captured including the latitude and longitude of their capture location, capture date, age class and sex, the age and number of cubs accompanying an adult female, andMultistate capture and search data from the southern Beaufort Sea polar bear population in Alaska, 2001-2016
This data release contains two tables of information on polar bear distributions in the southern Beaufort Sea during spring, from 2001 to 2016. One table provides location (classified into 5 broad regions) of individual bears during the spring. The other table presents the aerial search effort by year and area.Polar Bear Microsatellite Data Southern Beaufort Sea 2010-2013
This data set provides Polar Bear microsatellite genotypes derived from twenty loci (G1A, G10B, G10C, CXX110, G1D, G10H, G10J, G10L, G10M, MSUT2, MU59, G10P, 145P07, CPH9, CXX20, MU50, MU51, G10X, CXX173, G10U). Samples for microsatellite genetic analysis were collected from polar bears from the southern Beaufort Sea during the spring and fall, 2010-2013. Tissue samples were collected from capturePolar Bear Hair Mercury Concentrations Southern Beaufort Sea 2004-2011
These are data collected from polar bears from the southern Beaufort Seas during the spring and fall between 2004 and 2011. Data include individual ID, sex and age class, presence of dependent young, season of sample collection, total mercury concentration derived from a hair sample, estimate of annual diet proportion, and indices of body condition.Satellite Location and Tri-axial Accelerometer Data from Adult Female Polar Bears (Ursus maritimus) in the Southern Beaufort Sea, April-October 2014
These data are from 5 adult female polar bears instrumented in the southern Beaufort Sea, April to October 2014. The dataset is comprised of two data packages: 1) contains GPS and Argos locations collected by satellite-linked GPS receivers mounted on external collars, and 2) contains archival logger data including measures of tri-axial acceleration and conductivity. These data were collected to gaLocations Collected 1985-2015 from Female Polar Bears (Ursus maritimus) with Dependent Young Instrumented in the Southern Beaufort Sea with Satellite-linked Transmitters by the USGS
This dataset contains a select subset of Argos and GPS locations collected by satellite data collection systems from collared adult female polar bears that were instrumented in the southern Beaufort Sea between 1985-2015. These data were collected to gain insights into movements of southern Beaufort Sea polar bears. These data were collected from adult female polar bears who had dependent young atSerological Data on Influenza A from Birds and Mammals on the Arctic Coastal Plain of Northern Alaska, 2011-2017
These data (in two spreadsheets) are the results of screening for influenza A viruses (IAV) in blood from wild animals that utilize the Arctic region of Alaska. 758 blood samples from nine wildlife species (3 mammal, 6 waterbird) were collected in Arctic Alaska, 2011-2017. Two different tests were used and the results are presented in separate spreadsheets. All blood samples were screened for IAVU.S. Geological Survey Polar Bear Mark-Recapture Records, Alaska Portion of the Southern Beaufort Sea, 2001-2010
These data were collected by the U.S. Geological Survey, Alaska Science Center, Polar Bear Research Program as part of long-term on the southern Beaufort Sea polar bear population. - Multimedia
- Publications
Filter Total Items: 81
Observed and forecasted changes in land use by polar bears in the Beaufort and Chukchi Seas, 1985–2040
Monitoring changes in the distribution of large carnivores is important for managing human safety and supporting conservation. Throughout much of their range, polar bears (Ursus maritimus) are increasingly using terrestrial habitats in response to Arctic sea ice decline. Their increased presence in coastal areas has implications for bear-human conflict, inter-species interactions, and polar bear hAuthorsKaryn D. Rode, David C. Douglas, Todd C. Atwood, George M. Durner, Ryan R. Wilson, Anthony M. PaganoA serological survey of Francisella tularensis exposure in wildlife on the Arctic Coastal Plain of Alaska
Tularemia is an infectious zoonotic disease caused by one of several subspecies of Francisella tularensis bacteria. Infections by F. tularensis are common throughout the northern hemisphere and have been detected in more than 250 wildlife species. In Alaska, US, where the pathogen was first identified in 1938, studies have identified F. tularensis antibodies in a diverse suite of taxa, including iAuthorsMatthew M. Smith, Caroline R. Van Hemert, Todd C. Atwood, David R. Sinnett, Jerry W. Hupp, Brandt W Meixell, David D. Gustine, Layne G. Adams, Andrew M. RameyPleistocene–Holocene vicariance, not Anthropocene landscape change, explains the genetic structure of American black bear (Ursus americanus) populations in the American Southwest and northern Mexico
The phylogeography of the American black bear (Ursus americanus) is characterized by isolation into glacial refugia, followed by population expansion and genetic admixture. Anthropogenic activities, including overharvest, habitat loss, and transportation infrastructure, have also influenced their landscape genetic structure. We describe the genetic structure of the American black bear in the AmeriAuthorsMatthew J. Gould, James W. Cain III, Todd C. Atwood, Larisa E. Harding, Heather E. Johnson, Dave P. Onorato, Frederic S. Winslow, Gary W. RoemerDiet energy density estimated from isotopes in predator hair associated with survival, habitat, and population dynamics
Sea ice loss is fundamentally altering the Arctic marine environment. Yet there is a paucity of data on the adaptability of food webs to ecosystem change, including predator-prey interactions. Polar bears (Ursus maritimus) are an important subsistence resource for Indigenous people and an apex predator that relies entirely on the under-ice food web to meet their energy needs. Here, we assessed wheAuthorsKaryn D. Rode, Brian D. Taras, Craig A. Stricker, Todd C. Atwood, Nicole P Boucher, George M. Durner, Andrew E. Derocher, Evan S. Richardson, Seth Cherry, Lori T. Quakenbush, Lara Horstmann, Jeffrey F. BromaghinModeling the spatial and temporal dynamics of land-based polar bear denning in Alaska
Although polar bears (Ursus maritimus) of the Southern Beaufort Sea (SBS) subpopulation have commonly created maternal dens on sea ice in the past, maternal dens on land have become increasingly prevalent as sea ice declines. This trend creates conditions for increased human–bear interactions associated with local communities and industrial activity. Maternal denning is a vulnerable period in theAuthorsVijay P. Patil, George M. Durner, David C. Douglas, Todd C. AtwoodComparisons of Coupled Model Intercomparison Project Phase 5 (CMIP5) and Coupled Model Intercomparison Project Phase 6 (CMIP6) sea-ice projections in polar bear (Ursus maritimus) ecoregions during the 21st century
Climate model projections are commonly used to assess potential impacts of global warming on a breadth of social, economic, and environmental topics. Modeling centers throughout the world coordinate to apply a consistent suite of radiative forcing experiments so that all model outputs can be collectively analyzed and compared. Three generations of model outputs have been produced and made availablAuthorsDavid C. Douglas, Todd C. AtwoodUsing in situ/ex situ research collaborations to support polar bear conservation
A warming Arctic threatens the long-term persistence of polar bears (Ursus maritimus) in the wild. Historically, little collaboration existed between the in situ and ex situ polar bear scientific communities. However, for the past decade, zoo professionals, government agencies, and non-governmental organizations (NGO’s) have partnered to leverage resources and expertise with the goal of addressingAuthorsRandi Meyerson, Todd C. AtwoodEvaluating the efficacy of aerial infrared surveys to detect artificial polar bear dens
The need to balance economic development with impacts to Arctic wildlife has been a prominent subject since petroleum exploration began on the North Slope of Alaska, USA, in the late 1950s. The North Slope region includes polar bears (Ursus maritimus) of the southern Beaufort Sea subpopulation, which has experienced a long-term decline in abundance. Pregnant polar bears dig dens in snow drifts durAuthorsSusannah P Woodruff, Justin J Blank, Sheyna S Wisdom, Ryan H. Wilson, George M. Durner, Todd C. Atwood, Craig J Perham, Christina HM PohlMarine mammal hotspots across the circumpolar Arctic
AimIdentify hotspots and areas of high species richness for Arctic marine mammals.LocationCircumpolar Arctic.MethodsA total of 2115 biologging devices were deployed on marine mammals from 13 species in the Arctic from 2005 to 2019. Getis-Ord Gi* hotspots were calculated based on the number of individuals in grid cells for each species and for phylogenetic groups (nine pinnipeds, three cetaceans, aAuthorsCharmain Hamilton, Christian Lydersen, Jon Aars, Mario Acquarone, Todd C. Atwood, Alastair Baylis, Martin Biuw, Andrei N. Boltunov, Erik W. Born, Peter L. Boveng, Tanya M. Brown, Michael Cameron, John J. Citta, Justin A. Crawford, Rune Dietz, Jim Elias, Steven H. Ferguson, Aaron T. Fisk, Lars P. Folkow, Kathryn J. Frost, Dmitri M. Glazov, Sandra M. Granquist, Rowenna Gryba, Lois A. Harwood, Tore Haug, Mads Peter Heide-Jørgensen, Nigel E. Hussey, Jimmy Kalinek, Kristin L. Laidre, Dennis I. Litovka, Josh M. London, Lisa Loseto, Shannon MacPhee, Marianne Marcoux, Cory J. D. Matthews, Kjell J Nilssen, Erling S. Nordøy, Greg O’Corry-Crowe, Nils Øien, Morten Tange Olsen, Lori T. Quakenbush, Aqqalu Rosing-Asvid, Varvara Semenova, Kim E. W. Shelden, Olga V. Shpak, Garry Stenson, Luke Storrie, Signe Sveegaard, Jonas Teilmann, Fernando Ugarte, Andrew L. Von Duyke, Cortney Watt, Øystein Wiig, Ryan R. Wilson, David J. Yurkowski, Kit M. KovacsThe role of satellite telemetry data in 21st century conservation of polar bears (Ursus maritimus)
Satellite telemetry (ST) has played a critical role in the management and conservation of polar bears (Ursus maritimus) over the last 50 years. ST data provide biological information relevant to subpopulation delineation, movements, habitat use, maternal denning, health, human-bear interactions, and accurate estimates of vital rates and abundance. Given that polar bears are distributed at low densAuthorsKristin L. Laidre, George M. Durner, Nicholas J Lunn, Eric V. Regehr, Todd C. Atwood, Karyn D. Rode, Jon Aars, Heli Routti, Øystein Wiig, Markus Dyck, Evan S. Richardson, Stephen D Atkinson, Stanislav Belikov, Ian StirlingDistinct gut microbiomes in two polar bear subpopulations inhabiting different sea ice ecoregions
Gut microbiomes were analyzed by 16S rRNA gene metabarcoding for polar bears (Ursus maritimus) from the southern Beaufort Sea (SB), where sea ice loss has led to increased use of land-based food resources by bears, and from East Greenland (EG), where persistent sea ice has allowed hunting of ice-associated prey nearly year-round. SB polar bears showed a higher number of total (940 vs. 742) and uniAuthorsMegan Franz, Lyle White, Todd C. Atwood, Kristin L. Laidre, Denis Roy, Sophie Watson, Esteban Gongora, Melissa McKinneyNon-USGS Publications**
Algeo, T. P., D. Slate, R. M. Caron, T. C. Atwood, S. Recuenco, M. Ducey, R. B. Chipman, and M. Palace. 2017. Modeling raccoon (Procyon lotor) habitat connectivity to identify potential corridors for rabies spread. Tropical Medicine and Infectious Diseases 44. doi:10.3390/tropicalmed203044.Atwood, T. C., E. Peacock, K. M. Lillie, R. R. Wilson, and S. Miller. 2015. Demographic composition and behavior of polar bears summering on shore in Alaska. USGS Administrative Report, 26 p.Beasley, J. C., T. C. Atwood, M. E. Byrne, K. C. VerCauteren, S. R. Johnson, and O. E. Rhodes, Jr. 2015. A behaviorally-explicit approach for evaluating vaccine baits to mesopredators to control epizootics in fragmented landscapes. PLoS One 10:e0113206. doi:10.1371/journal.pone.0113206.Anderson, A., S. A. Shwiff, R. B. Chipman, T. C. Atwood, T. Cozzens, F. Fillo, R. Hale, B. Hatch, J. Maki, O. E. Rhodes, Jr, E. E. Rees, C. E. Rupprecht, R. Tinline, K. C. VerCauteren, and D. Slate. 2014. Forecasting the spread of raccoon rabies using a purpose-specific group decision-making process. Human-Wildlife Interactions 8(1):130-138.Slate, D., R. B. Chipman, T. P. Algeo, S. A. Mills, K. M. Nelson, C. K. Croson, E. J. Dubovi, R. W. Renshaw, K. C. VerCauteren, T. C. Atwood, S. Johnson, and C. E. Rupprecht. 2014. Safety and immunogenicity in the first field trial with ONRAB in raccoons in the United States. Journal of Wildlife Diseases 50(3):582-595. doi:10.7589/2013-08-207.Kunkel, K. E., T. K. Ruth, T. C. Atwood, D. H. Pletscher, and M. G. Hornocker. 2013. Assessing the value of wolves and cougars as conservation surrogates by linking carnivore hunting success with landscape characteristics. Animal Conservation 16:32-40. doi:10.1111/j.1469-1795.2012.00568.x.Beasley, J. D., W. S. Beatty, T. C. Atwood, S. Johnson, and O. E. Rhodes, Jr. 2012. A comparison of methods for estimating raccoon abundance: Implications for disease vaccination programs. Journal of Wildlife Management 76(6):1290-1297. doi:10.1002/jwmg.379.Atwood, T. C. and S. W. Breck. 2012. Carnivores, Conflict, and Conservation: Defining the Landscape of Conflict. Pages 99-118 in F. I. Álvares and G. E. Mata, (eds.). Carnivores: Species, Conservation, and Management. Nova Publishers.Atwood, T. C., T. L. Fry, and B. R. Leland. 2011. Partitioning of a limited resource by sympatric carnivores in the Chihuahuan Desert and the implications for disease transmission. Journal of Wildlife Management 75:1609-1615.Atwood, T. C., J. K. Young, J. P. Beckmann, S. W. Breck, O. E. Rhodes, Jr, J. A. Fike, and K. D. Bristow. 2011. Modeling connectivity of black bears in a desert sky island archipelago. Biological Conservation 144(12):2851-2862. doi:10.1016/j.biocon.2011.08.002.Fry, T. L., T. C. Atwood, and M. R. Dunbar. 2010. Utility of rhodamine B as a biomarker in raccoons. Human-Wildlife Interactions 4:275-282.Atwood, T. C. and E. M. Gese. 2010. Importance of resource selection and social behaviour to partitioning of hostile space by sympatric canids. Journal of Mammalogy 91:490-499.Atwood, T. C., T. J. DeLiberto, H. J. Smith, J. Stevenson, and K. C. VerCauteren. 2009. Raccoon spatial ecology related to cattle and bovine tuberculosis. Journal of Wildlife Management 73:647-654.Atwood, T. C., E. M. Gese, and K. E. Kunkel. 2009. Spatial decomposition of predation risk in a multiple-predator multiple-prey system. Journal of Wildlife Management 73:876-884.Atwood, T. C. and E. M. Gese. 2008. Coyotes (Canis latrans) and recolonizing wolves (Canis lupus): Social rank mediates risk-conditional behaviour at ungulate carcasses. Animal Behaviour 75:753-762.VerCauteren, K. C., T. C. Atwood, T. J. DeLiberto, H. J. Smith, J. Stevenson, T. Gidlewski, and B. V. Thomsen. 2008. Sentinel-based surveillance of coyotes to detect bovine tuberculosis in Michigan. Emerging Infectious Diseases 14:1862-1869.Atwood, T. C., K. C. VerCauteren, T. J. DeLiberto, H. J. Smith, and J. Stevenson. 2007. Coyotes as a potential sentinel species to detect bovine tuberculosis (Mycobacterium bovis) infection in white-tailed deer in Michigan. Journal of Wildlife Management 71:1545-1554.Atwood, T. C., E. M. Gese, and K. E. Kunkel. 2007. Comparative patterns of predation by cougars and recolonizing wolves. Journal of Wildlife Management 71:1098-1106.Atwood, T. C. 2006. The influence of habitat patch attributes on coyote group size and interaction in a fragmented landscape. Canadian Journal of Zoology 84:80-87.Atwood, T. C. 2006. Behavioral interactions between wolves, Canis lupus, and coyotes, Canis latrans, at ungulate carcasses in southwest Montana. Western North American Naturalist 66:390-394.Atwood, T. C., H. P. Weeks, Jr., and T. M. Gehring. 2004. Spatial ecology of coyotes along a suburban-to-rural gradient. Journal of Wildlife Management 85:1000-1009.Swihart, R. K., T. C. Atwood, J. R. Goheen, D. A. Scheiman, K. E. Munroe, and T. M. Gehring. 2003. Patch occupancy in North American mammals: Is patchiness in the eye of the beholder? . Journal of Biogeography 30:1259-1279.Atwood, T. C. and H. P. Weeks, Jr.. 2003. Sex-specific patterns of mineral lick preference in white-tailed deer. Northeastern Naturalist 10:409-414.Atwood, T. C. and H. P. Weeks, Jr.. 2002. Sex- and age-specific patterns of mineral lick use by white-tailed deer. American Midland Naturalist 148:289-296.Atwood, T. C. and H. P. Weeks, Jr.. 2002. Facultative dyad formation in adult male coyotes. Northeastern Naturalist 9:353-358.**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
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*Disclaimer: Listing outside positions with professional scientific organizations on this Staff Profile are for informational purposes only and do not constitute an endorsement of those professional scientific organizations or their activities by the USGS, Department of the Interior, or U.S. Government