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      By Alaska Science Center      October 27, 2023    

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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

View Media Details

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.

 

View Media Details

### 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

View Media Details

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

View Media Details

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. 

View Media Details

**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.

 

### Study Area

### Contacts

#### Emily L Weiser, Ph.D.

##### Wildlife Biologist

Alaska Science Center

eweiser@usgs.gov

907-786-7089

#### Vijay P Patil, Ph.D.

##### Wildlife Biologist

Alaska Science Center

vpatil@usgs.gov

907-786-7178

#### Rebecca Taylor, Ph.D.

##### Research Statistician

Alaska Science Center

rebeccataylor@usgs.gov

907-786-7004

#### Jeffrey Bromaghin, Ph.D.

##### Research Statistician

Alaska Science Center

jbromaghin@usgs.gov

907-786-7086

#### Joseph Eisaguirre, Ph.D. 

##### Research Wildlife Biologist

Alaska Science Center

jeisaguirre@usgs.gov

907-786-7062

### Explore Search

                      - Ecosystems Analytics
                      - Ecosystems
                      - Biology
                      - Ecosystems

View All **

Below are other science projects associated with this project.

link

May 16, 2024

####                 Walrus Research              

Ecosystems Mission Area, Land Management Research Program, Species Management Research Program, Alaska Science Center

link

May 16, 2024

####   Walrus Research

Learn More

link

December 22, 2023

####                 Annual Data and Model-based Estimates of Pacific Black Brant Age Ratios              

Alaska Science Center

link

December 22, 2023

####   Annual Data and Model-based Estimates of Pacific Black Brant Age Ratios

Learn More

link

January 12, 2023

####                 Q&A: Improving Aerial Surveys of Geese in Alaska with Aerial Imagery              

Alaska Science Center

link

January 12, 2023

####   Q&A: Improving Aerial Surveys of Geese in Alaska with Aerial Imagery

Learn More

link

December 15, 2017

####                 Polar Bear Population Dynamics              

Species Management Research Program, Alaska Science Center

link

December 15, 2017

####   Polar Bear Population Dynamics

Learn More

Below are data or web applications associated with this project.

January 9, 2024

####                 Movement Data for Migrating Geese Over the Northeast Pacific Ocean, 2018-2021              

Alaska Science Center

December 15, 2022

####                 Walrus Haulout and In-water Activity Levels Relative to Vessel Interactions in the Chukchi Sea, 2012-2015              

Alaska Science Center

November 1, 2022

####                 Polar Bear Continuous Time-Correlated Random Walk (CTCRW) Location Data Derived from Satellite Location Data, Chukchi and Beaufort Seas, July-November 1985-2017              

Alaska Science Center

June 30, 2022

####                 Aerial Photo Imagery from Fall Waterfowl Surveys, Izembek Lagoon, Alaska, 2017-2019              

Alaska Science Center

April 6, 2022

####                 Counts of Birds in Aerial Photos from Fall Waterfowl Surveys, Izembek Lagoon, Alaska, 2017-2019              

Alaska Science Center

December 14, 2021

####                 Arthropod Abundance Data from the Colville River Delta, Alaska              

Alaska Science Center

December 14, 2021

####                 Environmental Data from the Colville River Delta, Alaska              

Alaska Science Center

December 14, 2021

####                 Avian Demographic Data from the Colville River Delta, Alaska              

Alaska Science Center

September 27, 2021

####                 Polar Bear Continuous Time-Correlated Random Walk (CTCRW) Location Data Derived from Satellite Location Data, Southern Beaufort Sea, 1986-2016              

Alaska Science Center

August 30, 2021

####                 Temporal Viral Viability Data from Avian Influenza A Viruses Maintained in Alaska Wetlands Under Experimental and Environmental Conditions              

Environmental Health Program, Alaska Science Center

December 16, 2020

####                 Data and Model-based Estimates from Black Brant (Branta bernicla nigricans) Fall Age Ratio Surveys at Izembek Lagoon, Alaska              

Alaska Science Center

June 28, 2020

####                 Multistate capture and search data from the southern Beaufort Sea polar bear population in Alaska, 2001-2016              

Alaska Science Center

#### Pagination

-                Current page            1 
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-  Last pageLast » 

USGS Alaska Science Center Ecosystems Analytics Program

March 30, 2023

#### USGS Alaska Science Center Ecosystems Analytics Program

link

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 Mission Area, Alaska Science Center, Alaska Science Center

March 30, 2023

#### USGS Alaska Science Center Ecosystems Analytics Program

link

#### USGS Alaska Science Center Ecosystems Analytics Program

link

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 Mission Area, Alaska Science Center, Alaska Science Center

Below are publications associated with this project.

September 5, 2023

####                 Informing management of recovering predators and their prey with ecological diffusion models              

Alaska Science Center

June 19, 2023

####                 A hierarchical modelling framework for estimating individual- and population-level reproductive success from movement data              

Alaska Science Center

December 13, 2022

####                 Optimizing surveys of fall-staging geese using aerial imagery and automated counting              

Ecosystems Mission Area, Alaska Science Center, Upper Midwest Environmental Sciences Center

December 6, 2022

####                 Estimating reproductive and juvenile survival rates when offspring ages are uncertain: A novel multievent mark-resight model with beluga whale case study              

Ecosystems Mission Area, Alaska Science Center

November 11, 2022

####                 Brown bear–sea otter interactions along the Katmai coast: Terrestrial and nearshore communities linked by predation              

Ecosystems Mission Area, Alaska Science Center

October 3, 2022

####                 Barrier islands influence the assimilation of terrestrial energy in nearshore fishes              

Alaska Science Center

September 24, 2022

####                 Diet energy density estimated from isotopes in predator hair associated with survival, habitat, and population dynamics              

Ecosystems Mission Area, Alaska Science Center, Fort Collins Science Center

September 22, 2022

####                 Estimating 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, population

Ecosystems Mission Area, Cooperative Research Units, Alaska Science Center, Upper Midwest Environmental Sciences Center

August 25, 2022

####                 Modeling the spatial and temporal dynamics of land-based polar bear denning in Alaska              

Ecosystems Mission Area, Alaska Science Center

June 24, 2022

####                 Prioritizing habitats based on abundance and distribution of molting waterfowl in the Teshekpuk Lake Special Area of the National Petroleum Reserve, Alaska              

Ecosystems Mission Area, Alaska Science Center

April 12, 2022

####                 Summer/fall diet and macronutrient assimilation in an Arctic predator              

Ecosystems Mission Area, Alaska Science Center, Fort Collins Science Center

January 27, 2022

####                 Abundance and distribution of sea otters (Enhydra lutris) in the southcentral Alaska stock, 2014, 2017, and 2019              

Ecosystems Mission Area, Alaska Science Center

#### Pagination

-                Current page            1 
-                Page            2 
-                Page            3 
-                Page            4 
-                Page            5 
-                Page            6 
-                Page            7 
-                Page            8 
-                Page            9 
-  Next page›› 
-  Last pageLast » 

January 16, 2024

####                 Proportion of time that Pacific Flyway geese are at risk of wind-turbine strikes during transoceanic migrations              

This tool shows the proportion of goose locations expected to be in or below a user-specified rotor-swept zone based on expected goose flight altitudes.

Alaska Science Center

Below are software products associated with this project.

January 29, 2024

####                 Eelgrass Biomass Model              

Alaska Science Center

January 16, 2024

####                 Scripts to Analyze Altitude Selection in Migrating Pacific Flyway Geese              

Alaska Science Center

December 28, 2023

####                 Rayleigh Step-Selection Functions              

Alaska Science Center

October 24, 2023

####                 algaeClassify              

Alaska Science Center

June 16, 2023

####                 Reproductive Success from Movement Data              

Alaska Science Center

December 12, 2022

####                 QFASA Robustness to Assumption Violations: Computer Code              

Ecosystems Mission Area, Species Management Research Program, Alaska Science Center

October 31, 2022

####                 R scripts for analysis of fall photographic waterfowl surveys, Izembek NWR, Alaska, 2017-2019              

Alaska Science Center

September 6, 2022

####                 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)              

Alaska Science Center

March 10, 2021

####                 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

Ecosystems Mission Area, Species Management Research Program, Alaska Science Center

March 23, 2020

####                 Arctic Shorebird Population Model              

Land Management Research Program, Alaska Science Center

August 22, 2016

####                 qfasar: Quantitative Fatty Acid Signature Analysis in R              

Alaska Science Center

Population declines in Alaska beluga whale population may be linked to low birth and survival rates

December 7, 2022

####   Population declines in Alaska beluga whale population may be linked to low birth and survival rates

Researchers studied over a decade of photographic records of individual whales and determined that belugas in Alaska's Cook Inlet have relatively low...

Read Article

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

View Media Details

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.

 

View Media Details

### 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

View Media Details

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

View Media Details

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. 

View Media Details

**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.

 

### Study Area

### Contacts

#### Emily L Weiser, Ph.D.

##### Wildlife Biologist

Alaska Science Center

eweiser@usgs.gov

907-786-7089

#### Vijay P Patil, Ph.D.

##### Wildlife Biologist

Alaska Science Center

vpatil@usgs.gov

907-786-7178

#### Rebecca Taylor, Ph.D.

##### Research Statistician

Alaska Science Center

rebeccataylor@usgs.gov

907-786-7004

#### Jeffrey Bromaghin, Ph.D.

##### Research Statistician

Alaska Science Center

jbromaghin@usgs.gov

907-786-7086

#### Joseph Eisaguirre, Ph.D. 

##### Research Wildlife Biologist

Alaska Science Center

jeisaguirre@usgs.gov

907-786-7062

### Explore Search

                      - Ecosystems Analytics
                      - Ecosystems
                      - Biology
                      - Ecosystems

View All **

Below are other science projects associated with this project.

link

May 16, 2024

####                 Walrus Research              

Ecosystems Mission Area, Land Management Research Program, Species Management Research Program, Alaska Science Center

link

May 16, 2024

####   Walrus Research

Learn More

link

December 22, 2023

####                 Annual Data and Model-based Estimates of Pacific Black Brant Age Ratios              

Alaska Science Center

link

December 22, 2023

####   Annual Data and Model-based Estimates of Pacific Black Brant Age Ratios

Learn More

link

January 12, 2023

####                 Q&A: Improving Aerial Surveys of Geese in Alaska with Aerial Imagery              

Alaska Science Center

link

January 12, 2023

####   Q&A: Improving Aerial Surveys of Geese in Alaska with Aerial Imagery

Learn More

link

December 15, 2017

####                 Polar Bear Population Dynamics              

Species Management Research Program, Alaska Science Center

link

December 15, 2017

####   Polar Bear Population Dynamics

Learn More

Below are data or web applications associated with this project.

January 9, 2024

####                 Movement Data for Migrating Geese Over the Northeast Pacific Ocean, 2018-2021              

Alaska Science Center

December 15, 2022

####                 Walrus Haulout and In-water Activity Levels Relative to Vessel Interactions in the Chukchi Sea, 2012-2015              

Alaska Science Center

November 1, 2022

####                 Polar Bear Continuous Time-Correlated Random Walk (CTCRW) Location Data Derived from Satellite Location Data, Chukchi and Beaufort Seas, July-November 1985-2017              

Alaska Science Center

June 30, 2022

####                 Aerial Photo Imagery from Fall Waterfowl Surveys, Izembek Lagoon, Alaska, 2017-2019              

Alaska Science Center

April 6, 2022

####                 Counts of Birds in Aerial Photos from Fall Waterfowl Surveys, Izembek Lagoon, Alaska, 2017-2019              

Alaska Science Center

December 14, 2021

####                 Arthropod Abundance Data from the Colville River Delta, Alaska              

Alaska Science Center

December 14, 2021

####                 Environmental Data from the Colville River Delta, Alaska              

Alaska Science Center

December 14, 2021

####                 Avian Demographic Data from the Colville River Delta, Alaska              

Alaska Science Center

September 27, 2021

####                 Polar Bear Continuous Time-Correlated Random Walk (CTCRW) Location Data Derived from Satellite Location Data, Southern Beaufort Sea, 1986-2016              

Alaska Science Center

August 30, 2021

####                 Temporal Viral Viability Data from Avian Influenza A Viruses Maintained in Alaska Wetlands Under Experimental and Environmental Conditions              

Environmental Health Program, Alaska Science Center

December 16, 2020

####                 Data and Model-based Estimates from Black Brant (Branta bernicla nigricans) Fall Age Ratio Surveys at Izembek Lagoon, Alaska              

Alaska Science Center

June 28, 2020

####                 Multistate capture and search data from the southern Beaufort Sea polar bear population in Alaska, 2001-2016              

Alaska Science Center

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USGS Alaska Science Center Ecosystems Analytics Program

March 30, 2023

#### USGS Alaska Science Center Ecosystems Analytics Program

link

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 Mission Area, Alaska Science Center, Alaska Science Center

March 30, 2023

#### USGS Alaska Science Center Ecosystems Analytics Program

link

#### USGS Alaska Science Center Ecosystems Analytics Program

link

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 Mission Area, Alaska Science Center, Alaska Science Center

Below are publications associated with this project.

September 5, 2023

####                 Informing management of recovering predators and their prey with ecological diffusion models              

Alaska Science Center

June 19, 2023

####                 A hierarchical modelling framework for estimating individual- and population-level reproductive success from movement data              

Alaska Science Center

December 13, 2022

####                 Optimizing surveys of fall-staging geese using aerial imagery and automated counting              

Ecosystems Mission Area, Alaska Science Center, Upper Midwest Environmental Sciences Center

December 6, 2022

####                 Estimating reproductive and juvenile survival rates when offspring ages are uncertain: A novel multievent mark-resight model with beluga whale case study              

Ecosystems Mission Area, Alaska Science Center

November 11, 2022

####                 Brown bear–sea otter interactions along the Katmai coast: Terrestrial and nearshore communities linked by predation              

Ecosystems Mission Area, Alaska Science Center

October 3, 2022

####                 Barrier islands influence the assimilation of terrestrial energy in nearshore fishes              

Alaska Science Center

September 24, 2022

####                 Diet energy density estimated from isotopes in predator hair associated with survival, habitat, and population dynamics              

Ecosystems Mission Area, Alaska Science Center, Fort Collins Science Center

September 22, 2022

####                 Estimating 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, population

Ecosystems Mission Area, Cooperative Research Units, Alaska Science Center, Upper Midwest Environmental Sciences Center

August 25, 2022

####                 Modeling the spatial and temporal dynamics of land-based polar bear denning in Alaska              

Ecosystems Mission Area, Alaska Science Center

June 24, 2022

####                 Prioritizing habitats based on abundance and distribution of molting waterfowl in the Teshekpuk Lake Special Area of the National Petroleum Reserve, Alaska              

Ecosystems Mission Area, Alaska Science Center

April 12, 2022

####                 Summer/fall diet and macronutrient assimilation in an Arctic predator              

Ecosystems Mission Area, Alaska Science Center, Fort Collins Science Center

January 27, 2022

####                 Abundance and distribution of sea otters (Enhydra lutris) in the southcentral Alaska stock, 2014, 2017, and 2019              

Ecosystems Mission Area, Alaska Science Center

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January 16, 2024

####                 Proportion of time that Pacific Flyway geese are at risk of wind-turbine strikes during transoceanic migrations              

This tool shows the proportion of goose locations expected to be in or below a user-specified rotor-swept zone based on expected goose flight altitudes.

Alaska Science Center

Below are software products associated with this project.

January 29, 2024

####                 Eelgrass Biomass Model              

Alaska Science Center

January 16, 2024

####                 Scripts to Analyze Altitude Selection in Migrating Pacific Flyway Geese              

Alaska Science Center

December 28, 2023

####                 Rayleigh Step-Selection Functions              

Alaska Science Center

October 24, 2023

####                 algaeClassify              

Alaska Science Center

June 16, 2023

####                 Reproductive Success from Movement Data              

Alaska Science Center

December 12, 2022

####                 QFASA Robustness to Assumption Violations: Computer Code              

Ecosystems Mission Area, Species Management Research Program, Alaska Science Center

October 31, 2022

####                 R scripts for analysis of fall photographic waterfowl surveys, Izembek NWR, Alaska, 2017-2019              

Alaska Science Center

September 6, 2022

####                 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)              

Alaska Science Center

March 10, 2021

####                 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

Ecosystems Mission Area, Species Management Research Program, Alaska Science Center

March 23, 2020

####                 Arctic Shorebird Population Model              

Land Management Research Program, Alaska Science Center

August 22, 2016

####                 qfasar: Quantitative Fatty Acid Signature Analysis in R              

Alaska Science Center

Population declines in Alaska beluga whale population may be linked to low birth and survival rates

December 7, 2022

####   Population declines in Alaska beluga whale population may be linked to low birth and survival rates

Researchers studied over a decade of photographic records of individual whales and determined that belugas in Alaska's Cook Inlet have relatively low...

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