The USGS Alaska Science Center Ecosystems Analytics program is a group of quantitative biologists and research statisticians who provide analytical support to USGS scientists to answer challenging ecological topics and management questions for USGS partners.
Jeffrey Bromaghin, Ph.D.
My research broadly encompasses the development and application of statistical methods and models to improve our understanding of ecological processes that influence the survival, behavior, and reproduction of individual animals, and how individual-animal outcomes ultimately scale upward to shape the dynamics and demographics of entire populations and communities through time and space.
My research involves the development and application of new analytical methods and models to improve our understanding of wildlife population ecology, with a current emphasis on polar bears and other DOI trust species residing in Arctic and sub-Arctic ecosystems. Past work has included nest survival models, applications of genetics in wildlife models, size selectivity and the effects of selective exploitation, animal response to capture and handling, and mark-recapture methodology. Most current research involves the development of mark-recapture and integrated population models to improve our understanding of polar bear population dynamics in a warming Arctic and the use of biotracers (e.g. fatty acids, stable isotopes) to estimate predator diet composition and animal origins and movements. Research products provide valuable information to the public and management authorities from local to international levels, and many have broad applicability that advance the discipline of statistical ecology.
Professional Experience
2009 - Present Research Statistician, U.S. Geological Survey, Alaska Science Center
2000 - 2009 Statistician, U.S. Fish and Wildlife Service, Fisheries and Ecological Services, Alaska Region
1990 - 2000 Regional Biometrician, Alaska Dept. of Fish and Game, Commercial Fisheries Division
Education and Certifications
Ph.D. 1991 University of Wyoming Statistics
M.S. 1988 University of Wyoming Statistics
B.S. 1985 University of Alaska Wildlife Management
Affiliations and Memberships*
The International Biometric Society
The Wildlife Society
Ecological Society of America
Honors and Awards
2014 U. S. Geological Survey, Quality step increase for exceptional performance
2014 U. S. Geological Survey, STAR award for special achievement
2012 U. S. Geological Survey, STAR award for special achievement
2012 Stevan Phelps Award, American Fisheries Society (Bromaghin et al., 2011, TAFS 140:235-249)
2011 U. S. Geological Survey, STAR award for special achievement
2010 U. S. Geological Survey, STAR award for special achievement
2007 U. S. Fish and Wildlife Service, STAR award for exceptional performance
2007 U. S. Fish and Wildlife Service, Regional Director’s award for Science Excellence
2004 U. S. Fish and Wildlife Service, quality step increase for sustained exceptional performance
2001 U. S. Fish and Wildlife Service, STAR award for outstanding performance
1993 Letter of commendation, Alaska Dept. Fish and Game
1992 Deming Award for distinguished graduate program. Dept. of Statistics, University of Wyoming
Science and Products
Ecosystems Analytics
Polar Bear Population Dynamics
Southern Beaufort Sea Polar Bear Fatty Acid Data, Spring Samples 2004-2016
Diet Composition of Southern Beaufort Sea Polar Bears Sampled in Spring from 2004 to 2016 Estimated with Quantitative Fatty Acid Signature Analysis
Polar Bear Continuous Time-Correlated Random Walk (CTCRW) Location Data Derived from Satellite Location Data, Chukchi and Beaufort Seas, July-November 1985-2017
Multistate capture and search data from the southern Beaufort Sea polar bear population in Alaska, 2001-2016
Fatty acid signature data of potential yellow-billed loon prey in the Arctic coastal plain of Alaska, 2009-2011
Assessing the robustness of quantitative fatty acid signature analysis to assumption violations (Supplementary data)
U.S. Geological Survey Polar Bear Mark-Recapture Records, Alaska Portion of the Southern Beaufort Sea, 2001-2010
The USGS Alaska Science Center Ecosystems Analytics program is a group of quantitative biologists and research statisticians who provide analytical support to USGS scientists to answer challenging ecological topics and management questions for USGS partners.
This is a graphical abstract for a publication by the USGS and collaborators that examines the role of diet and food intake affecting polar bear population dynamics. Polar bears consume diets consisting of high proportions of marine mammal blubber that they access from the sea ice.
This is a graphical abstract for a publication by the USGS and collaborators that examines the role of diet and food intake affecting polar bear population dynamics. Polar bears consume diets consisting of high proportions of marine mammal blubber that they access from the sea ice.
Incremental evolution of modeling a prognosis for polar bears in a rapidly changing Arctic
Diet energy density estimated from isotopes in predator hair associated with survival, habitat, and population dynamics
Summer/fall diet and macronutrient assimilation in an Arctic predator
Long-term variation in polar bear body condition and maternal investment relative to a changing environment
Survival and abundance of polar bears in Alaska’s Beaufort Sea, 2001–2016
Diet composition and body condition of polar bears (Ursus maritimus) in relation to sea ice habitat in the Canadian High Arctic
Seal body condition and atmospheric circulation patterns influence polar bear body condition, recruitment, and feeding ecology in the Chukchi Sea
Analyses on subpopulation abundance and annual number of maternal dens for the U.S. Fish and Wildlife Service on polar bears (Ursus maritimus) in the southern Beaufort Sea, Alaska
Drivers and consequences of apex predator diet composition in the Canadian Beaufort Sea
Dietary fat concentrations influence fatty acid assimilation patterns in Atlantic pollock (Pollachius virens)
Energy-rich mesopelagic fishes revealed as a critical prey resource for a deep-diving predator using quantitative fatty acid signature analysis
QFASAR: Quantitative fatty acid signature analysis with R
Tests of multistate CJS models to estimate survival conditioned on a partially-observed latent state
QFASA Robustness to Assumption Violations: Computer Code
qfasar: Quantitative Fatty Acid Signature Analysis in R
Science and Products
- Science
Ecosystems Analytics
Ecosystems Analytics is a group of quantitative biologists and research statisticians with a diverse range of expertise and experience (summarized below). We collaborate with internal and external partners to answer challenging ecological questions that are a high priority of the U.S. Geological Survey Alaska Science Center, sister agencies within the Department of the Interior (DOI), and various...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
Southern Beaufort Sea Polar Bear Fatty Acid Data, Spring Samples 2004-2016
These data consist of the fatty acid composition (percent of mass) of adipose tissue samples from polar bears in Alaska's southern Beaufort Sea. Fat biopsy samples were collected from polar bears that were either captured or biopsy darted along the north coast of Alaska or on offshore ice during March, April, or May from 2004 to 2016. The data also include an identification code unique to an indivDiet Composition of Southern Beaufort Sea Polar Bears Sampled in Spring from 2004 to 2016 Estimated with Quantitative Fatty Acid Signature Analysis
These data are estimates of the proportional contributions of bearded seal, beluga whale, bowhead whale, and ringed seal to the diets of southern Beaufort Sea polar bears. Fat biopsy samples were collected from polar bears captured or biopsy darted along the north coast of Alaska or on offshore ice during March, April, and May from 2004 to 2016. Fatty acid data of the above four prey species werePolar 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 instrumenteMultistate 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.Fatty acid signature data of potential yellow-billed loon prey in the Arctic coastal plain of Alaska, 2009-2011
This dataset contains fatty acid data expressed as mass percent of total fatty acids for several species potentially preyed upon by yellow-billed loons. These data were utilized in a quantitative fatty acid signature analysis to estimate the diet of yellow-billed loons nesting on the Arctic Coastal Plain of Alaska (Haynes et al. 2015).Assessing the robustness of quantitative fatty acid signature analysis to assumption violations (Supplementary data)
This dataset contains fatty acid (FA) data expressed as mass percent of total FA for bearded seals, ringed seals and walrus. This is one of many datasets used in Bromaghin et al., In press, Assessing the robustness of quantitative fatty acid signature analysis to assumption violations, Methods in Ecology and Evolution. These supplemental data were used in computer simulations to compare the bias oU.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
USGS Alaska Science Center Ecosystems Analytics ProgramUSGS Alaska Science Center Ecosystems Analytics ProgramUSGS Alaska Science Center Ecosystems Analytics Program
The USGS Alaska Science Center Ecosystems Analytics program is a group of quantitative biologists and research statisticians who provide analytical support to USGS scientists to answer challenging ecological topics and management questions for USGS partners.
The USGS Alaska Science Center Ecosystems Analytics program is a group of quantitative biologists and research statisticians who provide analytical support to USGS scientists to answer challenging ecological topics and management questions for USGS partners.
Role of Diet and Food Intake Affecting Polar Bear Population Dynamics in Southern Beaufort SeaRole of Diet and Food Intake Affecting Polar Bear Population Dynamics in Southern Beaufort SeaThis is a graphical abstract for a publication by the USGS and collaborators that examines the role of diet and food intake affecting polar bear population dynamics. Polar bears consume diets consisting of high proportions of marine mammal blubber that they access from the sea ice.
This is a graphical abstract for a publication by the USGS and collaborators that examines the role of diet and food intake affecting polar bear population dynamics. Polar bears consume diets consisting of high proportions of marine mammal blubber that they access from the sea ice.
- Publications
Filter Total Items: 30
Incremental evolution of modeling a prognosis for polar bears in a rapidly changing Arctic
Updating predictions of the response of high-profile, at-risk species to climate change and anthropogenic stressors is vital for informing effective conservation action. Here, we review two prior generations of Bayesian network probability models predicting changes in global polar bear (Ursus maritimus) population status, and provide a contemporary update based on recent research findings and sea-AuthorsBruce G. Marcot, Todd C. Atwood, David C. Douglas, Jeffrey F. Bromaghin, Anthony M. Pagano, Steven C. AmstrupDiet 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. BromaghinSummer/fall diet and macronutrient assimilation in an Arctic predator
Free-ranging predator diet estimation is commonly achieved by applying molecular-based tracers because direct observation is not logistically feasible or robust. However, tracers typically do not represent all dietary macronutrients, which likely obscures resource use as prey proximate composition varies and tissue consumption can be specific. For example, polar bears (Ursus maritimus) preferentiaAuthorsCraig A. Stricker, Karyn D. Rode, Brian D. Taras, Jeffrey F. Bromaghin, Lara Horstmann, Lori T. QuakenbushLong-term variation in polar bear body condition and maternal investment relative to a changing environment
In the Arctic, warming air and ocean temperatures have resulted in substantial changes to sea ice, which is primary habitat for polar bears (Ursus maritimus). Reductions in extent, duration, and thickness have altered sea ice dynamics, which influences the ability of polar bears to reliably access marine mammal prey. Because nutritional condition is closely linked to population vital rates, a progAuthorsTodd C. Atwood, Karyn D. Rode, David C. Douglas, Kristin S. Simac, Anthony Pagano, Jeffrey F. BromaghinSurvival and abundance of polar bears in Alaska’s Beaufort Sea, 2001–2016
The Arctic Ocean is undergoing rapid transformation toward a seasonally ice-free ecosystem. As ice-adapted apex predators, polar bears (Ursus maritimus) are challenged to cope with ongoing habitat degradation and changes in their prey base driven by food-web response to climate warming. Knowledge of polar bear response to environmental change is necessary to understand ecosystem dynamics and inforAuthorsJeffrey F. Bromaghin, David C. Douglas, George M. Durner, Kristin S. Simac, Todd C. AtwoodDiet composition and body condition of polar bears (Ursus maritimus) in relation to sea ice habitat in the Canadian High Arctic
Polar bears (Ursus maritimus) rely on sea ice for hunting marine mammal prey. Declining sea ice conditions associated with climate warming have negatively affected polar bears, especially in the southern portion of their range. At higher latitudes, the transition from multi-year ice to thinner annual ice has been hypothesized to increase biological productivity and potentially improve polar bear fAuthorsKatie R. N. Florko, Gregory W. Thiemann, Jeffrey F. Bromaghin, Evan S. RichardsonSeal body condition and atmospheric circulation patterns influence polar bear body condition, recruitment, and feeding ecology in the Chukchi Sea
Polar bears (Ursus maritimus) are experiencing loss of sea ice habitats used to access their marine mammal prey. Simultaneously, ocean warming is changing ecosystems that support marine mammal populations. The interactive effects of sea ice and prey are not well understood yet may explain spatial‐temporal variation in the response of polar bears to sea ice loss. Here, we examined the potential comAuthorsKaryn D. Rode, Eric V. Regehr, Jeffrey F. Bromaghin, Ryan H. Wilson, Michelle St. Martin, Justin A. Crawford, Lori T. QuakenbushAnalyses on subpopulation abundance and annual number of maternal dens for the U.S. Fish and Wildlife Service on polar bears (Ursus maritimus) in the southern Beaufort Sea, Alaska
The long-term persistence of polar bears (Ursus maritimus) is threatened by sea-ice loss due to climate change, which is concurrently providing an opportunity in the Arctic for increased anthropogenic activities including natural resource extraction. Mitigating the risk of those activities, which can adversely affect the population dynamics of the southern Beaufort Sea (SBS) subpopulation, is an eAuthorsTodd C. Atwood, Jeffrey F. Bromaghin, Vijay P. Patil, George M. Durner, David C. Douglas, Kristin S. SimacDrivers and consequences of apex predator diet composition in the Canadian Beaufort Sea
Polar bears (Ursus maritimus) rely on annual sea ice as their primary habitat for hunting marine mammal prey. Given their long lifespan, wide geographic distribution, and position at the top of the Arctic marine food web, the diet composition of polar bears can provide insights into temporal and spatial ecosystem dynamics related to climate-mediated sea ice loss. Polar bears with the greatest ecolAuthorsKatie R. N. Florko, Gregory W. Thiemann, Jeffrey F. BromaghinDietary fat concentrations influence fatty acid assimilation patterns in Atlantic pollock (Pollachius virens)
A key aspect in the use of fatty acids (FA) to estimate predator diets using Quantitative FA Signature Analysis (QFASA) is the ability to account for FA assimilation through the use of calibration coefficients (CC). Here, we tested the assumption that CC are independent of dietary fat concentrations by feeding Atlantic pollock (Pollachius virens) three formulated diets with very similar FA proportAuthorsSuzanne M. Budge, Katherine Townsend, Santosh P Lall, Jeffrey F. BromaghinEnergy-rich mesopelagic fishes revealed as a critical prey resource for a deep-diving predator using quantitative fatty acid signature analysis
Understanding the diet of deep-diving predators can provide essential insight to the trophic structure of the mesopelagic ecosystem. Comprehensive population-level diet estimates are exceptionally difficult to obtain for elusive marine predators due to the logistical challenges involved in observing their feeding behavior and collecting samples for traditional stomach content or fecal analyses. WeAuthorsChandra Goetsch, Melinda G. Conners, Suzanne M. Budge, Yoko Mitani, William A Walker, Jeffrey F. Bromaghin, Samantha E. Simmons, Colleen Reichmuth, Daniel P. CostaQFASAR: Quantitative fatty acid signature analysis with R
Knowledge of predator diets provides essential insights into their ecology, yet diet estimation is challenging and remains an active area of research.Quantitative fatty acid signature analysis (QFASA) is a popular method of estimating diet composition that continues to be investigated and extended. However, software to implement QFASA has only recently become publicly available.I summarize a new RAuthorsJeffrey F. Bromaghin - Software
Tests of multistate CJS models to estimate survival conditioned on a partially-observed latent state
Polar bears (Ursus maritimus) of the Southern Beaufort Sea (SBS) historically spent nearly the entire year on the sea ice but are increasingly using land habitat as sea ice becomes less available seasonally due to climate warming. The U.S. Geological Survey, Alaska Science Center maintains a research program on the SBS polar bear subpopulation and one important research question is whether habitatQFASA Robustness to Assumption Violations: Computer Code
Quantitative fatty acid signature analysis (QFASA; Iverson et al. 2004) has become a common method of estimating diet composition, especially for marine mammals, but the performance of the method has received limited investigation. Bromaghin et al. (In press) used computer simulation to compare the bias of several QFASA estimators and developed recommendations regarding estimator selection. Simulaqfasar: Quantitative Fatty Acid Signature Analysis in R
Knowledge of predator diets provides numerous insights into their ecology. Diet estimation therefore remains an active area of research in quantitative ecology. Quantitative Fatty Acid Signature Analysis (QFASA) is a method of estimating the diet composition of predators. The fundamental unit of information in QFASA is a fatty acid signature (signature), which is a vector of proportions describing
*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