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.
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
Group Member Research
Group members may be contacted individually with the information located at bottom of this page or by clicking "View Staff Page" below. If you are unsure who to contact, Emily Weiser is the primary point of contact and can coordinate inquiries with other group members.
Emily Weiser
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.
Sources/Usage: Public Domain. View Media Details
Vijay Patil
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.
Media
Sources/Usage: Public Domain. View Media Details
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.
Sources/Usage: Public Domain. View Media Details
Rebecca Taylor
Rebecca Taylor
I am a principal investigator who develops new statistical techniques and modifies state-of the-art analytical approaches for complex problems and intractable data. I focus on hard to study species, and I routinely work in both Bayesian and frequentist paradigms. I create explanatory and predictive models, and I also use methods such as causal inference techniques (directed acyclic graphs, propensity score matching), decision tree algorithms and boosting methods, and nonparametric methods. I program in compiled and interpreted languages, including R. I collaborate locally, nationally, and internationally, with other scientists and statisticians in federal agencies, state agencies, academia, and the private sector.
Sources/Usage: Public Domain. View Media Details
Joe Eisaguirre
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 selection and space use 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, developing new movement modeling tools to directly incorporate individual animal movement data into population models, and expanding wildlife populations in Alaska.
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 ecology and movement ecology. I’m particularly interested in accounting for effects of humans (e.g., harvest) in spatiotemporal population processes, combining data streams to better estimate process parameters, and forecasting future spread of populations in Alaska.
Movement ecology and population dynamics - 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, survival, and cause-specific mortality.
Expanding wildlife populations in Alaska – Climate change and human activity are causing the distribution and abundance of wildlife populations to change in Alaska, resulting in ecosystem change and management challenges. For example, sea otter populations have recently experienced profound growth and spread following near extirpation from the maritime fur trade. However, their return is threatening commercial and subsistence fisheries. Additionally, barred owls are a newcomer to southeast Alaska, following their westward spread across North America, and could be having profound effects on other species (e.g., western screech owl) as has occurred in other regions. My interests in these areas relate to modeling and forecasting change to better inform monitoring activities and management plans. This also includes coupling spatiotemporal population models with bioeconomic models to inform “socially optimal” management strategies.
Sources/Usage: Public Domain. View Media Details
Below are other science projects associated with this project.
Expanding Wildlife Populations in Alaska
Changing environmental conditions and human activity are causing the distribution and abundance of wildlife populations in Alaska to change, resulting in challenges for wildlife and ecosystem management. For example, sea otter populations have recently experienced profound growth and spread following near extirpation from the maritime fur trade. However, while their recovery is widely considered a...
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...
Chugach Imaq Research Collaborative
Imaq comes from the Sugt’stun language meaning the ocean and the contents within it. The Chugach Imaq Project was founded by Chugach Regional Resources Commission (CRRC) to support Indigenous-led research and harvest management of marine mammals within the Chugach Region, while safeguarding subsistence needs of the Eyak and Sugpiaq tribes.
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...
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...
USGS 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.
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
Group Member Research
Group members may be contacted individually with the information located at bottom of this page or by clicking "View Staff Page" below. If you are unsure who to contact, Emily Weiser is the primary point of contact and can coordinate inquiries with other group members.
Emily Weiser
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.
Sources/Usage: Public Domain. View Media Details
Vijay Patil
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.
Media
Sources/Usage: Public Domain. View Media Details
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.
Sources/Usage: Public Domain. View Media Details
Rebecca Taylor
Rebecca Taylor
I am a principal investigator who develops new statistical techniques and modifies state-of the-art analytical approaches for complex problems and intractable data. I focus on hard to study species, and I routinely work in both Bayesian and frequentist paradigms. I create explanatory and predictive models, and I also use methods such as causal inference techniques (directed acyclic graphs, propensity score matching), decision tree algorithms and boosting methods, and nonparametric methods. I program in compiled and interpreted languages, including R. I collaborate locally, nationally, and internationally, with other scientists and statisticians in federal agencies, state agencies, academia, and the private sector.
Sources/Usage: Public Domain. View Media Details
Joe Eisaguirre
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 selection and space use 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, developing new movement modeling tools to directly incorporate individual animal movement data into population models, and expanding wildlife populations in Alaska.
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 ecology and movement ecology. I’m particularly interested in accounting for effects of humans (e.g., harvest) in spatiotemporal population processes, combining data streams to better estimate process parameters, and forecasting future spread of populations in Alaska.
Movement ecology and population dynamics - 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, survival, and cause-specific mortality.
Expanding wildlife populations in Alaska – Climate change and human activity are causing the distribution and abundance of wildlife populations to change in Alaska, resulting in ecosystem change and management challenges. For example, sea otter populations have recently experienced profound growth and spread following near extirpation from the maritime fur trade. However, their return is threatening commercial and subsistence fisheries. Additionally, barred owls are a newcomer to southeast Alaska, following their westward spread across North America, and could be having profound effects on other species (e.g., western screech owl) as has occurred in other regions. My interests in these areas relate to modeling and forecasting change to better inform monitoring activities and management plans. This also includes coupling spatiotemporal population models with bioeconomic models to inform “socially optimal” management strategies.
Sources/Usage: Public Domain. View Media Details
Below are other science projects associated with this project.
Expanding Wildlife Populations in Alaska
Changing environmental conditions and human activity are causing the distribution and abundance of wildlife populations in Alaska to change, resulting in challenges for wildlife and ecosystem management. For example, sea otter populations have recently experienced profound growth and spread following near extirpation from the maritime fur trade. However, while their recovery is widely considered a...
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...
Chugach Imaq Research Collaborative
Imaq comes from the Sugt’stun language meaning the ocean and the contents within it. The Chugach Imaq Project was founded by Chugach Regional Resources Commission (CRRC) to support Indigenous-led research and harvest management of marine mammals within the Chugach Region, while safeguarding subsistence needs of the Eyak and Sugpiaq tribes.
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...
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...
USGS 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.