Class
Article
College
College of Science
Faculty Mentor
Thomas Edwards
Presentation Type
Oral Presentation
Abstract
An important component of population ecology is understanding the impact on animal movement. Modeling animal movement helps us understand how this impact manifests itself in animal behavior and habitat selection as well as human impact on wildlife. Correlated movement and heterogeneous landscapes add complexity to these models and are often neglected. How do landscape features condition population movement and habitat choice? I answer this question by showing that motility does play a significant role in population dynamics. The ecological telegrapher's equation (ETE) incorporates both variable landscape and correlated movement. The solution to the ETE predicts the PDF of future locations. I use this PDF in a maximum likelihood process to parameterize the ETE with simulated data. In this work, I develop code to generate test data by simulating trajectories with a correlated random walk on a simulated terrain. I determine the accuracy of the MLE procedure by parameterizing the ETE with the simulated data and comparing with the assigned values in the simulated landscape. Applying the same MLE procedure to actual telemetry data from mule deer in Southern Utah will yield the impact of different landscape types on mule deer.
Location
Room 204
Start Date
4-12-2018 3:00 PM
End Date
4-12-2018 4:15 PM
Advanced Mathematical Approaches for Modeling Animal Movement through Landscapes
Room 204
An important component of population ecology is understanding the impact on animal movement. Modeling animal movement helps us understand how this impact manifests itself in animal behavior and habitat selection as well as human impact on wildlife. Correlated movement and heterogeneous landscapes add complexity to these models and are often neglected. How do landscape features condition population movement and habitat choice? I answer this question by showing that motility does play a significant role in population dynamics. The ecological telegrapher's equation (ETE) incorporates both variable landscape and correlated movement. The solution to the ETE predicts the PDF of future locations. I use this PDF in a maximum likelihood process to parameterize the ETE with simulated data. In this work, I develop code to generate test data by simulating trajectories with a correlated random walk on a simulated terrain. I determine the accuracy of the MLE procedure by parameterizing the ETE with the simulated data and comparing with the assigned values in the simulated landscape. Applying the same MLE procedure to actual telemetry data from mule deer in Southern Utah will yield the impact of different landscape types on mule deer.