Session Detail

73.Hierarchical models for wildlife surveys over time and space.
Wednesday, Oct 17, 2012, 8:30 AM -12:20 PM
Session Description

Hierarchical Models for Wildlife Surveys over Time and Space

Organizers: Devin Johnson, National Marine Mammal Laboratory National Oceanic and Atmospheric, Seattle, WA

Paul Conn, National Marine Mammal Laboratory National Oceanic and Atmospheric Administration Seattle, WA

Mevin Hooten, USGS Colorado Cooperative Fish and Wildlife Research Unit, Colorado State University, Fort Collins, CO

Sponsors: TWS Biometrics Working Group

TWS Spatial Ecology and Telemetry Working Group

Wildlife ecologists and managers often use survey data to make inferences about demography and population trends over space and time. Such data are often imperfect with regards to the parameter of interest. For instance, animals are often imperfectly detected, and some quantities of interest (e.g., population trend, survival) are never directly observed, and must be inferred indirectly. In many such cases, hierarchical modeling provides a mechanism for making inferences from these data. Hierarchical modeling also is a natural framework for addressing temporal and spatial autocorrelation in survey data, two features that are ubiquitous in ecological datasets. In this symposium, we bring together a diverse group of speakers who address recent method developments in hierarchical modeling for wildlife surveys, as well as case studies and practical applications.

10/17/2012 8:30:00 AM
Devin S. Johnson, 1 Contact:

10/17/2012 8:30:00 AM
Paul B. Conn, 1 Contact:

10/17/2012 8:30:00 AM
Mevin B. Hooten, 1 Contact:

10/17/2012 8:30:00 AM
Historical perspective on hierarchical models, their implementation and use in wildlife studies.
Mevin B. Hooten, Colorado State University, Fort Collins, CO, Contact:

10/17/2012 8:50:00 AM
Hierarchical models for wildlife transect surveys
Paul B. Conn, 1 Contact:

10/17/2012 9:10:00 AM
Estimating abundance while accounting for excess zeros, correlated behavior of animals, and other sources of dependence
Robert M. Dorazio1, Julien Martin2, Holly H. Edwards2, 1U.S. Geological Survey, Gainesville, FL, 2Florida Fish and Wildlife Conservation Commission, St. Petersburg, FL, Contact:

10/17/2012 9:30:00 AM
Combining spatial hierarchical models for dynamic populations: a case of surveying seals in the bering sea
Jay M. Ver Hoef1, Michael F. Cameron2, Peter L. Boveng2, Josh M. London2, Erin E. Moreland2, 1NOAA Alaska Fisheries Science Center, Fairbanks, AK, 2NOAA Alaska Fisheries Science Center, Seattle, WA, Contact:

10/17/2012 9:50:00 AM
Exploring environmental monitoring data via model-based clustering
Devin S. Johnson, 1 Contact:

10/17/2012 10:10:00 AM
P. Placeholder;
National Wildlife Research Center, Fort Collins, CO.

10/17/2012 10:40:00 AM
Spatially varying estimates of extinction risk from North American Breeding Bird Survey indices: application of a hierarchical state-space approach
Wayne E. Thogmartin1, Patrick C. McKann2, 12IAP WorldServices, USGS, Spokane, WA, Contact:

10/17/2012 11:00:00 AM
Reducing effort while improving inference: Estimating Dall’s sheep abundance and composition in small areas
Joshua H. Schmidt1, Kumi L. Rattenbury2, 1U.S. National Park Service, Central Alaska Network, Fairbanks, AK, 2U.S. National Park Service, Arctic Network, Fairbanks, AK, Contact:

10/17/2012 11:20:00 AM
Better ignorant than misled: including uncertainty in models supporting decisions in wildlife management
N. Thompson Hobbs, Colorado State University, Fort Collins, CO, Contact:

10/17/2012 11:40:00 AM
Hierarchical spatial models for large scale animal occupancy surveys in remote boreal forests of northern Ontario
Justina C. Ray, 1 Contact:

10/17/2012 12:00:00 PM
Evaluating the predictive abilities of hierarchical community occupancy models.
Elise F. Zipkin1, Evan Grant1, Viviana Ruiz-Gutiérrez2, 1USGS Patuxent Wildlife Research Center, Laurel, MD, 2Colorado State University, Fort Collins, CO, Contact:


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