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 state, national, and international institutions. Our work is largely focused on DOI trust species residing in Arctic and subarctic ecosystems but is broadly based. We consult with partner agencies on monitoring plan design and the application of existing statistical methods, and conduct research to develop innovative analytical techniques and statistical models that generally advance the field of statistical ecology. Work products improve our understanding of ecosystem function and population dynamics, provide management authorities with critical information to support decision-making, and are often useful to forecast future population status.
Return to Ecosystems
View video about our ecosystems analytics group.
Group Member Research
Group members may be contacted individually with the information located at the right side or bottom of this page. If you are unsure who to contact, Emily Weiser will coordinate with other group members. If you need more information, clicking on each group member’s name will redirect you to their individual USGS page.
Emily Weiser
I develop and use quantitative tools to inform on-the-ground conservation and management of birds and other wildlife, often in close collaboration with partners such as the U.S. Fish and Wildlife Service. My areas of expertise include demographic analyses, population modeling, monitoring design, power analysis, data simulation, Bayesian modeling, and use of R for analysis and visualization.
Demography and population modeling – My work has involved estimating survival in a mark-recapture framework, quantifying daily survival rates, and building simulation-based or matrix-based population models to evaluate population trends. Recent examples include estimating annual adult survival, nest survival, and influence of vital rates on population trends in Arctic-breeding shorebirds.
Monitoring design and power analysis – I have a keen interest in designing monitoring programs or studies to effectively and safely address the question at hand. Previously, I’ve worked to inform the design of a continental-scale monitoring program for monarch butterflies, evaluated how markers or tracking tags affect shorebirds, and identified statistically robust options for monitoring nest survival of shorebirds. Current work includes evaluating the design of a photographic aerial survey for brant.
Programming and software – I have experience with high-performance computing on the USGS supercomputers and Bayesian analysis in JAGS. I use R extensively for data manipulation, simple or complex modeling, data simulation, spatial analysis and mapping, producing publication-quality graphics, and interfacing with JAGS.
Vijay Patil
I conduct wildlife and ecosystems research with collaborators at the Alaska Science Center, Department of Interior agencies, and other state and local partners. Like Dr. Weiser, I provide statistical and programming support to partners at all stages of the research process, from study design to manuscript preparation.
Demographic rate estimation and population modeling - Much of my research involves vital rate estimation and modeling to identify demographic and environmental drivers of population growth. My recent work has included estimating survival costs of reproduction in marmots, testing tag effects and evaluating management strategies for shorebirds, and estimating waterfowl age-ratios. Current projects include a Bayesian hierarchical integrated population model (IPM) to evaluate the effects of phenology mismatch on Arctic-breeding goose populations.
GIS/remote sensing/spatial analysis - The recent proliferation of online datasets has created unprecedented opportunities for ecological and wildlife research at large spatial scales. Recently, I have used field and remote sensing data to model the distribution and abundance of polar bear dens, measure goose forage availability in Arctic wetlands, and design habitat protection scenarios to help mitigate potential impacts of oil and gas development on Alaskan wildlife.
Ecosystems research- I use field data and process-based models to investigate carbon and nutrient dynamics in terrestrial and aquatic systems, and to understand how community composition/biodiversity and physical ecosystem properties interact. For example, I am part of a collaborative effort to understand how climate change and extreme weather events affect lake ecosystems and phytoplankton communities.
Programming and software – I primarily use R for data analysis, modeling, visualization, and interfacing with other analytical tools such as JAGS and program MARK. More recently, I have begun exploring the world of R package development. I also have limited experience with Python, C++, and various flavors of SQL, and can provide assistance with Linux command line tools for data processing and automated data analysis.
Rebecca Taylor
(Credit: Rebecca Taylor, USGS. Public domain.)
I am a principal investigator who develops new statistical techniques and modifies state-of the-art analytical approaches for complex problems and intractable data, which are frequently sparse, biased and/or imprecise, possibly with large knowledge gaps. I focus on critical management decisions involving hard to study species, often in a changing environment. I routinely work in both Bayesian and frequentist paradigms.
Estimating demographic rates and abundance with emerging methods and multiple data types - Recent work under this theme includes evaluation of survival rate estimators based on standing age structure data that relax the (often used but generally unrealistic) stable age structure assumption, and integrated population modeling to estimate demographic rates using multiple data types, sparsely scattered over a multi-decade timespan. For example, the integrated population models have provided the only rigorous, robust estimates of Pacific walrus demographic rates and population trend to date. Current projects include work with age at death distributions, state-misclassification (as opposed to state-uncertainty) in multistate mark recapture models, developing explicit maximum likelihood estimators that combine capture-mark-recapture data with other data types, and close kin mark recapture estimation.
Mechanistic models and causal inference methods - This theme is geared toward to understanding and predicting effects of environmental change and anthropogenic disturbance on wildlife populations. Recent work has forecasted effects of sea ice loss on Pacific walruses and evaluated effects of increased vessel traffic (which occurs secondary to sea ice loss), also on walruses. The mechanistic models link environmental change and anthropogenic influences to 1) animal movement and behavior, 2) bioenergetics and body condition and 3) demography and population dynamics. Causal inference methods focus on obtaining unbiased estimates of a single link in the chain in the presence of multiple confounding factors: they use a combination of treatment and outcome modeling, including techniques such as propensity score-based matching that are rarely used in wildlife studies.
Jeff Bromaghin
(Credit: Mike Lockhart, USGS. Public domain.)
My research involves the development and application of statistical methods and models to improve our understanding of the ecology and population dynamics of species residing in Arctic and sub-Arctic ecosystems, with an emphasis on polar bears and other DOI trust species. The remote and harsh habitats, rapid rate of environmental change, and paucity of data on ecological drivers present tremendous challenges that require innovative solutions to overcome. Research products provide critical information to the public and management authorities from local to international levels, and many have broad applicability that advance the discipline of statistical ecology.
Modeling Population Dynamics - Research in this area generally involves the development and application of models to estimate key demographic rates, such as reproduction and survival, that underly change in population abundance and composition through time. Past work has included mark-recapture methodology, the integration of multiple data sources to estimate the timing and abundance of migrating mixtures of salmon populations, and the effects of animal capture and handling. Current research involves mark-recapture models that integrate multiple data sources and spatial multistate mark-recapture models for polar bear populations.
Methods in Statistical Ecology - I develop and test the performance of new models and analytical techniques in quantitative ecology. Past work has involved nest survival models, statistical methods in genetics, and size-selectivity in fishery harvests. Most recent research in this area has concerned the use of biotracers (e.g., fatty acids, stable isotopes) to estimate consumer diet composition and animal origins and movements. This research is timely because the diversity and complexity of biotracer methods in ecology is expanding rapidly.
Joe Eisaguirre
My research generally involves developing and applying Bayesian hierarchical models and other quantitative methods to better understand the ecology and inform management of wildlife, in close collaboration with other Department of Interior agencies and state and local partners. This includes spatiotemporal models of population growth and spread, movement models, resource and habitat selection models, and integrated data models. Currently, my primary interests relate to advancing spatiotemporal models to better understand the mechanisms governing the growth and spread of populations, as well as forecast changes in distribution and abundance, and developing new movement modeling tools to directly incorporate individual animal movement data into population models.

Spatiotemporal models for wildlife populations - Mechanistic spatiotemporal population models explicitly account for how things like movement and habitat selection affect local and global population processes. They can also provide more precise inference than descriptive or phenomenological techniques, especially when forecasting ecological processes is of interest. My work continues to improve mechanistic spatiotemporal models for understanding wildlife population and movement ecology. I’m particularly interested in accounting for effects of humans (e.g., harvest) in spatiotemporal population processes, as well as combining data streams to better estimate process parameters.
Mechanistic movement models for informing demographic parameters - The rapidly growing field of movement ecology, in part fueled by rapidly advancing animal telemetry technologies, has led to the development of numerous modeling tools for inferring things like behavioral changes and habitat selection. However, my interests lie in adapting existing tools and developing new ones to identify key life history events from movement data and scale inference to inform parameters in population models, such as reproductive success and cause-specific mortality.
Bayesian computation for combining data streams in hierarchical models - Most traditional methods for estimating parameters in Bayesian models applied in ecology rely on computationally intensive algorithms (e.g., MCMC). However, recent advances in computing techniques, such as recursive Bayesian inference, offer potential avenues for improving computation. These improvements are becoming increasingly important as we continue along the path of developing and applying more complex integrated data models (e.g., integrated population models) to refine inferences about ecological processes. My interests with this lie at the interface of mathematical statistics and computing to find ways to efficiently combine different data streams and scale inference in complex hierarchical statistical models.
Below are other science projects associated with this project.
Walrus Research
Q&A: Improving Aerial Surveys of Geese in Alaska with Aerial Imagery
Annual Data and Model-based Estimates of Pacific Black Brant Age Ratios
Polar Bear Population Dynamics
Below are data or web applications associated with this project.
Walrus Haulout and In-water Activity Levels Relative to Vessel Interactions in the Chukchi Sea, 2012-2015
Polar Bear Continuous Time-Correlated Random Walk (CTCRW) Location Data Derived from Satellite Location Data, Chukchi and Beaufort Seas, July-November 1985-2017
Aerial Photo Imagery from Fall Waterfowl Surveys, Izembek Lagoon, Alaska, 2017-2019
Counts of Birds in Aerial Photos from Fall Waterfowl Surveys, Izembek Lagoon, Alaska, 2017-2019
Arthropod Abundance Data from the Colville River Delta, Alaska
Environmental Data from the Colville River Delta, Alaska
Avian Demographic Data from the Colville River Delta, Alaska
Polar Bear Continuous Time-Correlated Random Walk (CTCRW) Location Data Derived from Satellite Location Data, Southern Beaufort Sea, 1986-2016
Temporal Viral Viability Data from Avian Influenza A Viruses Maintained in Alaska Wetlands Under Experimental and Environmental Conditions
Data and Model-based Estimates from Black Brant (Branta bernicla nigricans) Fall Age Ratio Surveys at Izembek Lagoon, Alaska
Multistate capture and search data from the southern Beaufort Sea polar bear population in Alaska, 2001-2016
Habitat Selection Scenarios for Molting Waterfowl in the Goose Molting Area of the Teshekpuk Lake Special Area, for NPR-A Integrated Activity Plan/Environmental Impact Statement (2020)
Below are publications associated with this project.
Informing management of recovering predators and their prey with ecological diffusion models
A hierarchical modelling framework for estimating individual- and population-level reproductive success from movement data
Optimizing surveys of fall-staging geese using aerial imagery and automated counting
Estimating reproductive and juvenile survival rates when offspring ages are uncertain: A novel multievent mark-resight model with beluga whale case study
Brown bear–sea otter interactions along the Katmai coast: Terrestrial and nearshore communities linked by predation
Barrier islands influence the assimilation of terrestrial energy in nearshore fishes
Diet energy density estimated from isotopes in predator hair associated with survival, habitat, and population dynamics
Estimating Pacific walrus abundance and survival with multievent mark-recapture models
Modeling the spatial and temporal dynamics of land-based polar bear denning in Alaska
Prioritizing habitats based on abundance and distribution of molting waterfowl in the Teshekpuk Lake Special Area of the National Petroleum Reserve, Alaska
Prioritizing habitats based on abundance and distribution of molting waterfowl in the Teshekpuk Lake Special Area of the National Petroleum Reserve, Alaska
Summer/fall diet and macronutrient assimilation in an Arctic predator
Below are software products associated with this project.
Reproductive Success from Movement Data
QFASA Robustness to Assumption Violations: Computer Code
R scripts for analysis of fall photographic waterfowl surveys, Izembek NWR, Alaska, 2017-2019
Code for analysis of polar bear maternal den abundance and distribution in four regions of northern Alaska and Canada within the Southern Beaufort Sea subpopulation boundary (1982-2015)
Nest Survival Bias Analysis
This R script will run one replicate of one scenario used by Weiser (in review) to quantify biases in estimates of nest survival when nests are not found at the beginning of the nesting interval (age 0). The script simulates nest monitoring histories based on input parameters, applies models with or without an age effect to estimate daily survival rates, and calculates nest survival (to the end of
Arctic Shorebird Population Model
qfasar: Quantitative Fatty Acid Signature Analysis in R
- Overview
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 state, national, and international institutions. Our work is largely focused on DOI trust species residing in Arctic and subarctic ecosystems but is broadly based. We consult with partner agencies on monitoring plan design and the application of existing statistical methods, and conduct research to develop innovative analytical techniques and statistical models that generally advance the field of statistical ecology. Work products improve our understanding of ecosystem function and population dynamics, provide management authorities with critical information to support decision-making, and are often useful to forecast future population status.
Return to Ecosystems
View video about our ecosystems analytics group.
Group Member Research
Group members may be contacted individually with the information located at the right side or bottom of this page. If you are unsure who to contact, Emily Weiser will coordinate with other group members. If you need more information, clicking on each group member’s name will redirect you to their individual USGS page.
Emily Weiser
Example of a photo from the USFWS fall aerial survey for Black Brant at Izembek Lagoon. Inset shows a closer view of four Black Brant (bottom) with a Cackling Goose (top) foraging on eelgrass. We can use artificial intelligence to automate counting birds in each photo to develop population estimates. I develop and use quantitative tools to inform on-the-ground conservation and management of birds and other wildlife, often in close collaboration with partners such as the U.S. Fish and Wildlife Service. My areas of expertise include demographic analyses, population modeling, monitoring design, power analysis, data simulation, Bayesian modeling, and use of R for analysis and visualization.
Demography and population modeling – My work has involved estimating survival in a mark-recapture framework, quantifying daily survival rates, and building simulation-based or matrix-based population models to evaluate population trends. Recent examples include estimating annual adult survival, nest survival, and influence of vital rates on population trends in Arctic-breeding shorebirds.
Monitoring design and power analysis – I have a keen interest in designing monitoring programs or studies to effectively and safely address the question at hand. Previously, I’ve worked to inform the design of a continental-scale monitoring program for monarch butterflies, evaluated how markers or tracking tags affect shorebirds, and identified statistically robust options for monitoring nest survival of shorebirds. Current work includes evaluating the design of a photographic aerial survey for brant.
Programming and software – I have experience with high-performance computing on the USGS supercomputers and Bayesian analysis in JAGS. I use R extensively for data manipulation, simple or complex modeling, data simulation, spatial analysis and mapping, producing publication-quality graphics, and interfacing with JAGS.
Animated plot of migration tracks for adult Snow Geese in the Western Arctic Population, from Fall 2018 to Winter 2019. Each colored dot represents an individual goose. The red polygon on the north slope of Alaska represents the 1002 area of the Arctic National Wildlife Refuge, where these geese briefly stage each fall. Locations are derived from GPS/GSM collars that were deployed on adult Snow Geese from Wrangel Island (n=9) and the Colville River Delta (n=13) in August 2018. These GPS data are being used to better understand the factors that control the timing of spring and fall migrations, to compare the migration pathways of geese from different nesting areas, and to learn about fine-scale patterns of habitat use on their wintering grounds. Vijay Patil
I conduct wildlife and ecosystems research with collaborators at the Alaska Science Center, Department of Interior agencies, and other state and local partners. Like Dr. Weiser, I provide statistical and programming support to partners at all stages of the research process, from study design to manuscript preparation.
Demographic rate estimation and population modeling - Much of my research involves vital rate estimation and modeling to identify demographic and environmental drivers of population growth. My recent work has included estimating survival costs of reproduction in marmots, testing tag effects and evaluating management strategies for shorebirds, and estimating waterfowl age-ratios. Current projects include a Bayesian hierarchical integrated population model (IPM) to evaluate the effects of phenology mismatch on Arctic-breeding goose populations.
GIS/remote sensing/spatial analysis - The recent proliferation of online datasets has created unprecedented opportunities for ecological and wildlife research at large spatial scales. Recently, I have used field and remote sensing data to model the distribution and abundance of polar bear dens, measure goose forage availability in Arctic wetlands, and design habitat protection scenarios to help mitigate potential impacts of oil and gas development on Alaskan wildlife.
Ecosystems research- I use field data and process-based models to investigate carbon and nutrient dynamics in terrestrial and aquatic systems, and to understand how community composition/biodiversity and physical ecosystem properties interact. For example, I am part of a collaborative effort to understand how climate change and extreme weather events affect lake ecosystems and phytoplankton communities.
Programming and software – I primarily use R for data analysis, modeling, visualization, and interfacing with other analytical tools such as JAGS and program MARK. More recently, I have begun exploring the world of R package development. I also have limited experience with Python, C++, and various flavors of SQL, and can provide assistance with Linux command line tools for data processing and automated data analysis.
Rebecca Taylor
Walrus reflections in the water. Taken from a USGS research cruise in the Chukchi Sea.
(Credit: Rebecca Taylor, USGS. Public domain.)I am a principal investigator who develops new statistical techniques and modifies state-of the-art analytical approaches for complex problems and intractable data, which are frequently sparse, biased and/or imprecise, possibly with large knowledge gaps. I focus on critical management decisions involving hard to study species, often in a changing environment. I routinely work in both Bayesian and frequentist paradigms.
Estimating demographic rates and abundance with emerging methods and multiple data types - Recent work under this theme includes evaluation of survival rate estimators based on standing age structure data that relax the (often used but generally unrealistic) stable age structure assumption, and integrated population modeling to estimate demographic rates using multiple data types, sparsely scattered over a multi-decade timespan. For example, the integrated population models have provided the only rigorous, robust estimates of Pacific walrus demographic rates and population trend to date. Current projects include work with age at death distributions, state-misclassification (as opposed to state-uncertainty) in multistate mark recapture models, developing explicit maximum likelihood estimators that combine capture-mark-recapture data with other data types, and close kin mark recapture estimation.
Mechanistic models and causal inference methods - This theme is geared toward to understanding and predicting effects of environmental change and anthropogenic disturbance on wildlife populations. Recent work has forecasted effects of sea ice loss on Pacific walruses and evaluated effects of increased vessel traffic (which occurs secondary to sea ice loss), also on walruses. The mechanistic models link environmental change and anthropogenic influences to 1) animal movement and behavior, 2) bioenergetics and body condition and 3) demography and population dynamics. Causal inference methods focus on obtaining unbiased estimates of a single link in the chain in the presence of multiple confounding factors: they use a combination of treatment and outcome modeling, including techniques such as propensity score-based matching that are rarely used in wildlife studies.
Jeff Bromaghin
Large polar bear
(Credit: Mike Lockhart, USGS. Public domain.)My research involves the development and application of statistical methods and models to improve our understanding of the ecology and population dynamics of species residing in Arctic and sub-Arctic ecosystems, with an emphasis on polar bears and other DOI trust species. The remote and harsh habitats, rapid rate of environmental change, and paucity of data on ecological drivers present tremendous challenges that require innovative solutions to overcome. Research products provide critical information to the public and management authorities from local to international levels, and many have broad applicability that advance the discipline of statistical ecology.
Modeling Population Dynamics - Research in this area generally involves the development and application of models to estimate key demographic rates, such as reproduction and survival, that underly change in population abundance and composition through time. Past work has included mark-recapture methodology, the integration of multiple data sources to estimate the timing and abundance of migrating mixtures of salmon populations, and the effects of animal capture and handling. Current research involves mark-recapture models that integrate multiple data sources and spatial multistate mark-recapture models for polar bear populations.
Methods in Statistical Ecology - I develop and test the performance of new models and analytical techniques in quantitative ecology. Past work has involved nest survival models, statistical methods in genetics, and size-selectivity in fishery harvests. Most recent research in this area has concerned the use of biotracers (e.g., fatty acids, stable isotopes) to estimate consumer diet composition and animal origins and movements. This research is timely because the diversity and complexity of biotracer methods in ecology is expanding rapidly.
Joe Eisaguirre
My research generally involves developing and applying Bayesian hierarchical models and other quantitative methods to better understand the ecology and inform management of wildlife, in close collaboration with other Department of Interior agencies and state and local partners. This includes spatiotemporal models of population growth and spread, movement models, resource and habitat selection models, and integrated data models. Currently, my primary interests relate to advancing spatiotemporal models to better understand the mechanisms governing the growth and spread of populations, as well as forecast changes in distribution and abundance, and developing new movement modeling tools to directly incorporate individual animal movement data into population models.
Sources/Usage: Public Domain. Visit Media to see details.A sea otter mom nursing her pup. Photo taken in Prince William Sound, Alaska. A newborn sea otter needs to stay with its mother for six months to learn how to survive on its own. Spatiotemporal models for wildlife populations - Mechanistic spatiotemporal population models explicitly account for how things like movement and habitat selection affect local and global population processes. They can also provide more precise inference than descriptive or phenomenological techniques, especially when forecasting ecological processes is of interest. My work continues to improve mechanistic spatiotemporal models for understanding wildlife population and movement ecology. I’m particularly interested in accounting for effects of humans (e.g., harvest) in spatiotemporal population processes, as well as combining data streams to better estimate process parameters.
Mechanistic movement models for informing demographic parameters - The rapidly growing field of movement ecology, in part fueled by rapidly advancing animal telemetry technologies, has led to the development of numerous modeling tools for inferring things like behavioral changes and habitat selection. However, my interests lie in adapting existing tools and developing new ones to identify key life history events from movement data and scale inference to inform parameters in population models, such as reproductive success and cause-specific mortality.
Bayesian computation for combining data streams in hierarchical models - Most traditional methods for estimating parameters in Bayesian models applied in ecology rely on computationally intensive algorithms (e.g., MCMC). However, recent advances in computing techniques, such as recursive Bayesian inference, offer potential avenues for improving computation. These improvements are becoming increasingly important as we continue along the path of developing and applying more complex integrated data models (e.g., integrated population models) to refine inferences about ecological processes. My interests with this lie at the interface of mathematical statistics and computing to find ways to efficiently combine different data streams and scale inference in complex hierarchical statistical models.
- Science
Below are other science projects associated with this project.
Walrus Research
The USGS Alaska Science Center conducts long-term research on the Pacific walrus to provide scientific information to Department of Interior management agencies and Alaska Native co-management partners. In addition, the USGS Pacific walrus research program collaborates with the U.S. Fish and Wildlife Service (USFWS) and the State of Alaska’s Department of Fish and Game and Alaska Native co...Q&A: Improving Aerial Surveys of Geese in Alaska with Aerial Imagery
Thousands of geese gather at Izembek Lagoon in southwestern Alaska every fall where they “stage”, meaning that they rest and eat in preparation for migration to lower latitudes. Izembek Lagoon is especially important for Pacific brant geese, as the entire Pacific Flyway population is thought to use the lagoon in fall. This provides an opportunity to efficiently survey the population to track...Annual Data and Model-based Estimates of Pacific Black Brant Age Ratios
Pacific brant are an Arctic-breeding sea goose that stage and feed on seagrasses during the non-breeding season in coastal areas of Alaska. Brant are an important subsistence and sport harvest species and the focus of several population surveys by state and federal agencies. Each fall the entire population stages during migration in Izembek Lagoon, Alaska, presenting a unique opportunity to survey...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
Below are data or web applications associated with this project.
Filter Total Items: 16Walrus Haulout and In-water Activity Levels Relative to Vessel Interactions in the Chukchi Sea, 2012-2015
These data were used to evaluate effects of vessel exposure on Pacific walrus (Odobenus rosmarus divergens) behaviors. We obtained greater than 120,000 hours of location and behavior (foraging, in-water not foraging, hauled out) data from 218 satellite-tagged walruses and linked them to vessel locations from the marine Automated Information System. This yielded 206 vessel-exposed walrus telemetryPolar 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 instrumenteAerial Photo Imagery from Fall Waterfowl Surveys, Izembek Lagoon, Alaska, 2017-2019
The imagery and annotations presented here were generated while testing an aerial photographic survey design to improve repeatability, transparency, and estimation of variance for annual population estimates of geese staging at Izembek Lagoon, Alaska. This dataset includes 1) 131,031 .JPG images captured from a small fixed-wing occupied aircraft, usually at an altitude of about 457 m, over IzembekCounts of Birds in Aerial Photos from Fall Waterfowl Surveys, Izembek Lagoon, Alaska, 2017-2019
This dataset includes tables summarizing image information and bird counts from the aerial digital images taken over open water at Izembek Lagoon in Alaska in fall 2017-2019. These summaries list one record per image and provide the camera parameters, latitude, longitude, altitude, and automated and manual counts representing the total number of birds in each taxon (brant, white-cheeked geese, empArthropod Abundance Data from the Colville River Delta, Alaska
This data release contains information on the seasonal diversity and abundance of arthropods collected at the Colville River Delta, Alaska, 2011-2012 and 2014-2107. Researchers with the US Geological Survey began studying the reproductive ecology of birds at a site on the Colville River near the Beaufort Sea coast in 2011. Researchers concurrently collected arthropods at 3-day intervals to understEnvironmental Data from the Colville River Delta, Alaska
This data release contains two tables with information on seasonal values for temperature, wind, and snow cover collected at the Colville River Delta, Alaska, 2011-2018. Researchers with the U.S. Geological Survey used an on-site weather station to automatically record the temperature and speed and direction of the wind across the duration of their field season. Researchers also established permanAvian Demographic Data from the Colville River Delta, Alaska
This data release contains multiple tables with information on avian demographics collected at the Colville River Delta, Alaska, 2011-2018. Researchers with the U.S. Geological Survey began studying the reproductive ecology of birds at a site on the Colville River near the Beaufort Sea coast in 2011. Researchers monitored the nests of geese, shorebirds, and landbirds at this study site, determininPolar 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.Temporal Viral Viability Data from Avian Influenza A Viruses Maintained in Alaska Wetlands Under Experimental and Environmental Conditions
Data sets containing: (1) sample collection and influenza A virus (IAV) screening information for wild ducks, (2) water temperature data from four wetlands within the Izembek National Wildlife Refuge in Alaska, USA (3) water quality measurement from four wetlands within the Izembek National Wildlife Refuge in Alaska, USA, (4) genetic sequence data for IAVs recovered from replicate samples of wildData and Model-based Estimates from Black Brant (Branta bernicla nigricans) Fall Age Ratio Surveys at Izembek Lagoon, Alaska
These data are in two tables relating to fall age ratios (number of juvenile birds : total birds aged) of Black brant (Branta bernicla nigricans) staging in Izembek Lagoon, Alaska since 1963. The first file is observation data for the birds' age classes during surveys and associated survey characteristics. The second file contains model-based estimates of age ratios by year along with SE, and 95%Multistate 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.Habitat Selection Scenarios for Molting Waterfowl in the Goose Molting Area of the Teshekpuk Lake Special Area, for NPR-A Integrated Activity Plan/Environmental Impact Statement (2020)
The dataset consists of a polygon shapefile. Each polygon represents a set of molt units (interconnected lakes used as habitat by molting waterfowl) within the Goose Molting Area of the Teshekpuk Lake Special Area in northern Alaska, in addition to a half-mile or 1-mile wide buffer, that were selected for restrictions on new surface occupancy or infrastructure development by the oil and gas indust - Multimedia
- Publications
Below are publications associated with this project.
Filter Total Items: 105Informing management of recovering predators and their prey with ecological diffusion models
The reintroduction and recovery of predators can be ecologically beneficial as well as socially and economically controversial. However, the growth and expansion of predator populations, and thus their ecological, social, and economic impacts, are not static but rather they vary in space and time. We propose a spatiotemporal statistical modeling framework based on ecological diffusion to better inAuthorsJoseph Michael Eisaguirre, Perry J. Williams, Xinyi Lu, Michelle L. Kissling, Paul A Schutte, Benjamin P Weitzman, William S. Beatty, George G. Esslinger, Jamie N. Womble, Mevin B. HootenA hierarchical modelling framework for estimating individual- and population-level reproductive success from movement data
Rapidly advancing animal telemetry technologies paired with new statistical models can provide insight into the behaviour of otherwise unobservable free-living animals. Changes in behaviour apparent from pairing telemetry with statistical models often occur as animals undertake key life-history activities, such as reproduction. For many species that are secretive or occupy remote areas, these lifeAuthorsJoseph Michael Eisaguirre, Perry J. Williams, Julia C. Brockman, Stephen B. Lewis, Christopher P. Barger, Greg A. Breed, Travis L. BoomsOptimizing surveys of fall-staging geese using aerial imagery and automated counting
Ocular aerial surveys allow efficient coverage of large areas and can be used to monitor abundance and distribution of wild populations. However, uncertainty around resulting population estimates can be large due to difficulty in visually identifying and counting animals from aircraft, as well as logistical challenges in estimating detection probabilities. Photographic aerial surveys can mitigateAuthorsEmily L. Weiser, Paul L. Flint, Dennis K Marks, Brad S Shults, Heather M. Wilson, Sarah J Thompson, Julian B. FischerEstimating reproductive and juvenile survival rates when offspring ages are uncertain: A novel multievent mark-resight model with beluga whale case study
Understanding the survival and reproductive rates of a population is critical to determining its long-term dynamics and viability. Mark-resight models are often used to estimate these demographic rates, but estimation of survival and reproductive rates is challenging, especially for wide-ranging, patchily distributed, or cryptic species. In particular, existing mark-resight models cannot accommodaAuthorsGina K Himes Boor, Tamara L McGuire, Amanda J. Warlick, Rebecca L. Taylor, Sarah J. Converse, John R McClung, Amber D StephensBrown bear–sea otter interactions along the Katmai coast: Terrestrial and nearshore communities linked by predation
Sea otters were extirpated throughout much of their range by the maritime fur trade in the 18th and 19th centuries, including the coast of Katmai National Park and Preserve in southcentral Alaska. Brown bears are an important component of the Katmai ecosystem where they are the focus of a thriving ecotourism bear-viewing industry as they forage in sedge meadows and dig clams in the extensive tidalAuthorsDaniel Monson, Rebecca L. Taylor, Grant Hilderbrand, Joy Erlenbach, Heather Coletti, James L. BodkinBarrier islands influence the assimilation of terrestrial energy in nearshore fishes
We examined the relative importance of landscape features on estuarine fish trophic structure and dependence on terrestrial organic matter (OMterr) in four barrier island lagoon systems along the Alaskan Beaufort Sea coast. Our study compared two relatively large lagoon systems characterized by high river discharge and relatively free ocean water exchanges (central region near Prudhoe Bay, Alaska)AuthorsAshley E. Stanek, Vanessa R. von Biela, Sarah M. Laske, Rebecca L. Taylor, Kenneth H. DuntonDiet 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. BromaghinEstimating Pacific walrus abundance and survival with multievent mark-recapture models
Arctic marine ecosystems are undergoing rapid physical and biological change associated with climate warming and loss of sea ice. Sea ice loss will impact many species through altered spatial and temporal availability of resources. In the Bering and Chukchi Seas, the Pacific walrus Odobenus rosmarus divergens is one species that could be impacted by rapid environmental change, and thus, populationAuthorsWilliam S. Beatty, Patrick R. Lemons, Jason P. Everett, Cara J. Lewis, Rebecca L. Taylor, Robert J. Lynn, Suresh A. Sethi, Lori T. Quakenbush, John J. Citta, Michelle Kissling, Natalia Kryukova, John K. WennburgModeling 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. AtwoodPrioritizing habitats based on abundance and distribution of molting waterfowl in the Teshekpuk Lake Special Area of the National Petroleum Reserve, Alaska
The National Petroleum Reserve in Alaska (NPR-A) encompasses more than 9.5 million hectares of federally managed land on the Arctic Coastal Plain of northern Alaska, where it supports a diversity of wildlife, including millions of migratory birds. Within the NPR-A, Teshekpuk Lake and the surrounding area provide important habitat for migratory birds and this area has been designated by the BureauAuthorsPaul L. Flint, Vijay P. Patil, Bradley Shults, Sarah J. ThompsonPrioritizing habitats based on abundance and distribution of molting waterfowl in the Teshekpuk Lake Special Area of the National Petroleum Reserve, Alaska
The National Petroleum Reserve in Alaska (NPR-A) encompasses more than 9.5 million hectares of federally managed land on the Arctic Coastal Plain of northern Alaska, where it supports a diversity of wildlife, including millions of migratory birds. Within the NPR-A, Teshekpuk Lake and the surrounding area provide important habitat for migratory birds and this area has been designated by the BureauAuthorsPaul L. Flint, Vijay P. Patil, Bradley Shults, Sarah J. ThompsonSummer/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. Quakenbush - Software
Below are software products associated with this project.
Reproductive Success from Movement Data
This software release includes code to conduct analyses presented in the manuscript titled: A hierarchical modeling framework for estimating individual- and population-level reproductive success from movement dataQFASA 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. SimulaR scripts for analysis of fall photographic waterfowl surveys, Izembek NWR, Alaska, 2017-2019
This code repo contains three novel scripts used in Weiser et al. (2022): one to calculate the footprint of an aerial photo (01_function_photo_footprint.r), one to run a simulation to evaluate sample sizes for the photographic survey (02_photo_sample_size_sim.r), and one to run a simulation to evaluate sample sizes for the ocular survey (03_ocular_sample_size_sim.r). For more information on the baCode for analysis of polar bear maternal den abundance and distribution in four regions of northern Alaska and Canada within the Southern Beaufort Sea subpopulation boundary (1982-2015)
We have archived the derived data files and R/JAGS code for our analysis as a U.S. Geological Survey data release (link ). The code is divided into three R scripts: 1) pbdens_landdens_JWM.r contains R code for fitting hierarchical Bayesian models of polar bear maternal den abundance and distribution for the Southern Beaufort Sea (SBS) subpopulation, 1982-2015. This script requires the installationNest Survival Bias Analysis
This R script will run one replicate of one scenario used by Weiser (in review) to quantify biases in estimates of nest survival when nests are not found at the beginning of the nesting interval (age 0). The script simulates nest monitoring histories based on input parameters, applies models with or without an age effect to estimate daily survival rates, and calculates nest survival (to the end of
Arctic Shorebird Population Model
R script to run one example of the stochastic matrix models run by Weiser et al. to simulate shorebird population trends and elasticities.qfasar: 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 - News