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
Polar Bear Research
Q&A: Recent Research on Southern Beaufort Sea Polar Bears
Polar Bear Maternal Denning
Distribution and Movements of Polar Bears
Health and Energetics of Polar Bears
Polar Bear Population Dynamics
Diet Estimates of Southern Beaufort Sea Polar Bears, 2004-2016
Mercury Concentrations, Diet, and Gut Microbiota Diversity of Southern Beaufort Sea Polar Bears, 2008-2019
Southern Beaufort Sea Polar Bear Blood Based Analyte Data, 1983-2018
Southern Beaufort Sea Polar Bear Diet and Gut Microbiota Data, 2015-2019
Polar Bear Continuous Time-Correlated Random Walk (CTCRW) Location Data Derived from Satellite Location Data, Chukchi and Beaufort Seas, July-November 1985-2017
Genetic structure of American black bear populations in the American Southwest and northern Mexico, 1994-2014
Polar Bear Fall Coastal Survey Data from the Southern Beaufort Sea of Alaska, 2010-2013
Mapping data of Polar Bear (Ursus maritimus) maternal den habitat, Arctic Coastal Plain, Alaska
Pathogen and Contaminant Exposure Data from Southern Beaufort Sea Polar Bears, 2007-2014
Polar Bear Continuous Time-Correlated Random Walk (CTCRW) Location Data Derived from Satellite Location Data, Southern Beaufort Sea, 1986-2016
Innate Immunity and Stress and Reproductive Hormone Metrics for Southern Beaufort Sea Polar Bears, 2013-2015
Serum Urea and Creatinine Levels of Spring-Caught Polar Bears (Ursus maritimus) in the Southern Beaufort and Chukchi Seas
Giardia and Cryptosporidium in resident wildlife species in Arctic Alaska
Forecasts of polar bear (Ursus maritimus) land use in the southern Beaufort and Chukchi Seas, 2040–65
High winds and melting sea ice trigger landward movement in a polar bear population of concern
Fecal DNA metabarcoding shows credible short-term prey detections and explains variation in the gut microbiome of two polar bear subpopulations
Efficacy of bear spray as a deterrent against polar bears
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
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
Polar Bear Research
Polar bears (Ursus maritimus) are one of 4 marine mammal species managed by the U.S. Department of Interior. The USGS Alaska Science Center leads long–term research on polar bears to inform local, state, national and international policy makers regarding conservation of the species and its habitat. Our studies, ongoing since 1985, are focused on population dynamics, health and energetics...Q&A: Recent Research on Southern Beaufort Sea Polar Bears
Polar bears are found throughout the circumpolar Arctic and roam across miles of sea ice and land. There are 19 recognized subpopulations of polar bears across the Arctic with two in Alaska: the Chukchi Sea and the Southern Beaufort Sea. The sea ice habitat of these subpopulations is changing with substantial recent declines in the extent of sea ice off the coast of Alaska. These changes are...Polar Bear Maternal Denning
Pregnant polar bears enter maternity dens in October/November, give birth to cubs in December/January, and exit dens in March/April. Historically, most polar bears from the Southern Beaufort Sea (SBS) population constructed maternity dens on the sea ice. Over the last three decades, as sea ice has become thinner and prone to fragmentation, there has been a landward shift in the distribution of...Distribution and Movements of Polar Bears
Polar bears are tied to the sea ice for nearly all of their life cycle functions. Most important of these is foraging, or access to food. Polar bears almost exclusively eat seals, and they are equally as dependent upon the sea for their nutrition as are seals, whales, and other aquatic mammals. Polar bears are not aquatic, however, and their only access to the seals is from the surface of the sea...Health and Energetics of Polar Bears
Research in this focal area is centered on (i) collecting data on a variety of systems that help determine and mediate polar bear health and energetics, and (ii) developing monitoring and surveillance programs for detecting changes in population health over time. Additionally, this work will allow us to develop an understanding of how polar bear populations will respond to a variety of stressors...Polar Bear Population Dynamics
Information on the status and trends of polar bear populations are needed to inform management of polar bears under US laws and international agreements. The USGS maintains a long-term research program focused on the population dynamics of the southern Beaufort Sea polar bear population. In addition, the USGS collaborates with the US Fish and Wildlife Service in population studies in the Chukchi... - Data
Filter Total Items: 19
Diet Estimates of Southern Beaufort Sea Polar Bears, 2004-2016
These were data collected from polar bears from the southern Beaufort Sea during the spring between 2004 and 2016. Data include individual bear identification, age and sex class, capture date, capture year, open water season lengths, melt season length, and diet composition (expressed as a percentage of prey species). These data were used to determine whether polar bear diets have recently changedMercury Concentrations, Diet, and Gut Microbiota Diversity of Southern Beaufort Sea Polar Bears, 2008-2019
This dataset is two tables with data collected and derived from polar bears sampled in Alaska's southern Beaufort Sea during 2008-2019. Collected data includes demographic and morphometric information and derived data includes mercury concentrations in hair samples. Ancillary data includes gut microbiome abundances, diversity indices, calculated body condition, and the proportions of prey speciesSouthern Beaufort Sea Polar Bear Blood Based Analyte Data, 1983-2018
This dataset is one table with data collected and derived from polar bears sampled in Alaska's southern Beaufort Sea during 1983-2018. Collected data includes demographic and morphometric information. Derived data includes blood-based analyte values determined from whole blood and serum samples. Serum samples were analyzed on an Abaxis VS2 Biochemistry Analyzer and whole blood samples were analyzeSouthern Beaufort Sea Polar Bear Diet and Gut Microbiota Data, 2015-2019
This dataset is one table with data collected and derived from polar bears sampled in Alaska's southern Beaufort Sea during 2015-2019. Data include demographic and morphometric information from each sampled polar bear, gut microbiome diversity indices derived from fecal DNA metabarcoding, and the proportion of prey species detected in individual bear diets derived from quantitative fatty acid analPolar Bear Continuous Time-Correlated Random Walk (CTCRW) Location Data Derived from Satellite Location Data, Chukchi and Beaufort Seas, July-November 1985-2017
his dataset consists of one table with estimated locations of adult female polar bears during July-November 1985-2017, used for quantifying changes in summer land use over time. Locations were estimated with a Continuous Time-Correlated Random Walk (CTCRW) model fit to satellite tracking from radio-collared adult female polar bears. All bears included in this data set were captured and instrumenteGenetic structure of American black bear populations in the American Southwest and northern Mexico, 1994-2014
Microsatellite genotypes for American black bears collected by Gould et al. 2002 and used to assess the genetic structure of American black bear populations in the American Southwest and northern Mexico. Genotypes are for Ursus americanus individuals.Polar Bear Fall Coastal Survey Data from the Southern Beaufort Sea of Alaska, 2010-2013
This data set is one table with observations of polar bears located during aerial surveys along the coast and barrier islands of the southern Beaufort Seas during fall, 2010-2013. Survey flights were conducted using A-Star B2 and Bell 206 helicopters at an average altitude of 300 feet AGL and an average speed of 50 miles per hour. Survey crews searched for polar bears using coastal and inland tranMapping data of Polar Bear (Ursus maritimus) maternal den habitat, Arctic Coastal Plain, Alaska
These are geospatial data that characterize the distribution of polar bear denning habitat on the National Petroleum Reserve-Alaska (NPR-A), the 1002 Area of the Arctic National Wildlife Refuge and the coastal plain of northern Alaska between the Colville River and the Alaska/Canada border.Pathogen and Contaminant Exposure Data from Southern Beaufort Sea Polar Bears, 2007-2014
These were data collected from polar bears from the Southern Beaufort Sea during the spring between 2007 and 2014. Data include individual ID, capture date, sex and age class, whether individuals visited bowhead whale carrion sites, exposure status relative to five pathogens, and concentrations of certain persistent organic pollutants.Polar Bear Continuous Time-Correlated Random Walk (CTCRW) Location Data Derived from Satellite Location Data, Southern Beaufort Sea, 1986-2016
This dataset consists of one table with predicted locations of adult female polar bears. Locations were derived by a Continuous Time-Correlated Random Walk (CTCRW) model using satellite tracking radio-collared adult female polar bears captured and instrumented in the southern Beaufort Sea, 1986–2016.Innate Immunity and Stress and Reproductive Hormone Metrics for Southern Beaufort Sea Polar Bears, 2013-2015
These were data collected from polar bears from the Southern Beaufort Sea during the spring between 2013 and 2015. Data include individual identification, demographic characteristics, year, status for the current and prior year regarding use of land, concentrations of stress response and reproductive hormones, blood-based biomarker measures indicative of fasting, body mass index, and body conditioSerum 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, and - Multimedia
- Publications
Filter Total Items: 75
Giardia and Cryptosporidium in resident wildlife species in Arctic Alaska
Giardia and Cryptosporidium are zoonotic protozoan parasites that can infect humans and other taxa, including wildlife, often causing gastrointestinal illness. Both have been identified as One Health priorities in the Arctic, where climate change is expected to influence the distribution of many wildlife and zoonotic diseases, but little is known about their prevalence in local wildlife. To help fAuthorsCaroline R. Van Hemert, Lora Ballweber, David R. Sinnett, Todd C. Atwood, Anthony S. Fischbach, David Gustine, Kristy PabiloniaForecasts of polar bear (Ursus maritimus) land use in the southern Beaufort and Chukchi Seas, 2040–65
This report provides analysis to extend the 2040 forecasts of polar bear (Ursus maritimus) land use for the southern Beaufort and Chukchi Sea populations presented in a recent publication (Rode and others, 2022) through the year 2065. To inform long-term polar bear management considerations, we provide point-estimate forecasts and 95-percent prediction intervals of the proportion of polar bear popAuthorsKaryn D. Rode, David C. Douglas, Todd C. Atwood, Ryan R. WilsonHigh winds and melting sea ice trigger landward movement in a polar bear population of concern
Some animal species are responding to climate change by altering the timing of events like mating and migration. Such behavioral plasticity can be adaptive, but it is not always. Polar bears (Ursus maritimus) from the southern Beaufort Sea subpopulation have mostly remained on ice year-round, but as the climate warms and summer sea ice declines, a growing proportion of the subpopulation is summeriAuthorsAnnie Kellner, Todd C. Atwood, David C. Douglas, Stewart Breck, George WittemyerFecal DNA metabarcoding shows credible short-term prey detections and explains variation in the gut microbiome of two polar bear subpopulations
This study developed and evaluated DNA metabarcoding to identify the presence of pinniped and cetacean prey DNA in fecal samples of East Greenland (EG) and Southern Beaufort Sea (SB) polar bears Ursus maritimus sampled in the spring of 2015-2019. Prey DNA was detected in half (49/92) of all samples, and when detected, ringed seal Pusa hispida was the predominant prey species, identified in 100% (2AuthorsMegan Franz, L Whyte, Todd C. Atwood, Damian M. Menning, Sarah A. Sonsthagen, Sandra Talbot, Kristin L. Laidre, Emmanuel Gonzalez, Melissa McKinneyEfficacy of bear spray as a deterrent against polar bears
Although there have been few attempts to systematically analyze information on the use of deterrents on polar bears (Ursus maritimus), understanding their effectiveness in mitigating human-polar bear conflicts is critical to ensuring both human safety and polar bear conservation. To fill this knowledge gap, we analyzed 19 incidents involving the use of bear spray on free-ranging polar bears from 1AuthorsJames Wilder, Lindsey Mangipane, Todd C. Atwood, Anatoly A. Kochnev, Tom Smith, Dag VongravenObserved 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. AtwoodNon-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