Ecosystems Analytics Active
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
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
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.
Below are data or web applications associated with this project.
Below are publications associated with this project.
Sample-size considerations for a study of shorebird nest survival in the 1002 Area, Arctic National Wildlife Refuge, Alaska
Dietary fat concentrations influence fatty acid assimilation patterns in Atlantic pollock (Pollachius virens)
Prioritizing habitats based on abundance and distribution of molting waterfowl in the Teshekpuk Lake Special Area of the National Petroleum Reserve, Alaska
Storm impacts on phytoplankton community dynamics in lakes
Visualizing populations of North American sea ducks: Maps to guide research and management planning
Balancing sampling intensity against spatial coverage for a community science monitoring programme
Spatio-temporal population change of Arctic-breeding waterbirds on the Arctic Coastal Plain of Alaska
Energy-rich mesopelagic fishes revealed as a critical prey resource for a deep-diving predator using quantitative fatty acid signature analysis
Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor
Design considerations for estimating survival rates with standing age structures
Montane-breeding bird distribution and abundance across national parks of southwestern Alaska
Long‐term trends in fall age ratios of black brant
Below are software products associated with this project.
- 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
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
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
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.
- Science
Below are other science projects associated with this project.
- Data
Below are data or web applications associated with this project.
Filter Total Items: 17No Result Found - Multimedia
- Publications
Below are publications associated with this project.
Filter Total Items: 102Sample-size considerations for a study of shorebird nest survival in the 1002 Area, Arctic National Wildlife Refuge, Alaska
Authorization of lease sales for oil development in the 1002 Area of the Arctic National Wildlife Refuge has highlighted gaps in information about biological communities in the area. The U.S. Fish and Wildlife Service, which is planning a study to evaluate spatial variation in the nest survival of tundra-breeding shorebirds to identify hotspots with high nest survival, sought advice from the U.S.AuthorsEmily L. WeiserDietary fat concentrations influence fatty acid assimilation patterns in Atlantic pollock (Pollachius virens)
A key aspect in the use of fatty acids (FA) to estimate predator diets using Quantitative FA Signature Analysis (QFASA) is the ability to account for FA assimilation through the use of calibration coefficients (CC). Here, we tested the assumption that CC are independent of dietary fat concentrations by feeding Atlantic pollock (Pollachius virens) three formulated diets with very similar FA proportAuthorsSuzanne M. Budge, Katherine Townsend, Santosh P Lall, Jeffrey F. BromaghinPrioritizing 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, including large numbers of waterfowl and shorebAuthorsPaul L. Flint, Vijay Patil, Bradley Shults, Sarah J. ThompsonStorm impacts on phytoplankton community dynamics in lakes
In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short‐term runoff events from watersheds and physical mixing ofAuthorsJason D. Stockwell, Jonathan P. Doubek, Rita Adrian, Orlane Anneville, Cayelan C. Carey, Laurence Carvalho, Marieke A. Frassl, Lisette N. De Senerpont Domis, Bas W Ibelings, Hans-Peter Grossart, Gaël Dur, Marc J. Lajeunesse, Aleksandra M. Lewandowska, María E. Llames, Shin-Ichiro S. Matsuzaki, Emily Nodine, Peeter Noges, Vijay P. Patil, Francesco Pomati, Karsten Rinke, Lars G. Rudstam, James A. Rusak, Nico Salmaso, Christian T. Seltmann, Dietmar Straile, Stephen J. Thackeray, Wim Thiery, Pablo Urrutia‐Cordero, Patrick Venail, Piet Verburg, R. Iestyn Woolway, Tamar Zohary, Mikkel R. Andersen, Ruchi Bhattacharya, J. Hejzlar, Nasime Janatian, Alfred T. N. K. Kpodonu, Tanner J. Williamson, Harriet WilsonVisualizing populations of North American sea ducks: Maps to guide research and management planning
North American sea ducks generally breed in mid- to northern-latitude regions and nearly all rely upon marine habitats for much of their annual cycle. Most sea duck species remained poorly studied until the 1990s when declines were noted in several species and populations. Subsequent research, much of which was funded by the Sea Duck Joint Venture, began in the late 1990s with an emphasis on definAuthorsJohn M. Pearce, Paul L. Flint, Mary E. Whalen, Sarah A. Sonsthagen, Josh Stiller, Vijay P. Patil, Timothy D. Bowman, Sean Boyd, Shannon S. Badzinski, H.G. Gilchrist, Scott G. Gilliland, Christine Lepage, Pam Loring, Daniel McAuley, Nic McLellan, Jason Osenkowski, Eric T. Reed, Anthony J. Roberts, Myra Robertson, Tom Rothe, David E. Safine, Emily D. Silverman, Kyle A. SpragensBalancing sampling intensity against spatial coverage for a community science monitoring programme
Community science is an increasingly integral part of biodiversity research and monitoring, often achieving broad spatial and temporal coverage but lower sampling intensity than studies conducted by professional scientists. When designing a community‐science monitoring programme, careful assessment of sampling designs that could be both feasible and successful at meeting programme goals is essentiAuthorsEmily L. Weiser, Jay E. Diffendorfer, Ralph Grundel, Laura Lopez Hoffman, Samuel Pecoraro, Darius J. Semmens, Wayne E. ThogmartinSpatio-temporal population change of Arctic-breeding waterbirds on the Arctic Coastal Plain of Alaska
Rapid physical changes that are occurring in the Arctic are primary drivers of landscape change and thus may drive population dynamics of Arctic-breeding birds. Despite the importance of this region to breeding and molting waterbirds, lack of a comprehensive analysis of historic data has hindered quantifying avian population change. We estimated distribution, abundance, and spatially explicit popuAuthorsCourtney L. Amundson, Paul L. Flint, Robert A Stehn, Robert Platte, Heather M. Wilson, William W. Larned, Julian B. FischerEnergy-rich mesopelagic fishes revealed as a critical prey resource for a deep-diving predator using quantitative fatty acid signature analysis
Understanding the diet of deep-diving predators can provide essential insight to the trophic structure of the mesopelagic ecosystem. Comprehensive population-level diet estimates are exceptionally difficult to obtain for elusive marine predators due to the logistical challenges involved in observing their feeding behavior and collecting samples for traditional stomach content or fecal analyses. WeAuthorsChandra Goetsch, Melinda G. Conners, Suzanne M. Budge, Yoko Mitani, William A Walker, Jeffrey F. Bromaghin, Samantha E. Simmons, Colleen Reichmuth, Daniel P. CostaWrangling distributed computing for high-throughput environmental science: An introduction to HTCondor
Biologists and environmental scientists now routinely solve computational problems that were unimaginable a generation ago. Examples include processing geospatial data, analyzing -omics data, and running large-scale simulations. Conventional desktop computing cannot handle these tasks when they are large, and high-performance computing is not always available nor the most appropriate solution forAuthorsRichard A. Erickson, Michael N. Fienen, S. Grace McCalla, Emily L. Weiser, Melvin L. Bower, Jonathan M. Knudson, Greg ThainDesign considerations for estimating survival rates with standing age structures
Survival rate estimates are critical to understanding the dynamics and status of a population, and they are often inferred from samples of the population’s age structure. A recently developed method uses time series of standing age-structure data with information about population growth rate or fecundity to provide explicit maximum likelihood estimators of age-specific survival rates, without assuAuthorsRebecca L. Taylor, Mark S. UdevitzMontane-breeding bird distribution and abundance across national parks of southwestern Alaska
Between 2004 and 2008, biologists conducted an inventory of breeding birds during May–June primarily in montane areas (>100 m above sea level) in Aniakchak National Monument and Preserve (Aniakchak NMP), Katmai National Park and Preserve (Katmai NPP), and Lake Clark National Park and Preserve (Lake Clark NPP) in southwestern Alaska. Observers conducted 1,021 point counts along 169 transects withinAuthorsCourtney L. Amundson, Colleen M. Handel, Daniel R. Ruthrauff, T. Lee Tibbitts, Robert E. GillLong‐term trends in fall age ratios of black brant
Accurate estimates of the age composition of populations can inform past reproductive success and future population trajectories. We examined fall age ratios (juveniles:total birds) of black brant (Branta bernicla nigricans; brant) staging at Izembek National Wildlife Refuge near the tip of the Alaska Peninsula, southwest Alaska, USA, 1963 to 2015. We also investigated variation in fall age ratiosAuthorsDavid H. Ward, Courtney L. Amundson, Robert A. Stehn, Christian P. Dau - Web Tools
- Software
Below are software products associated with this project.
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