"Everything should be made as simple as possible, but not simpler." - Albert Einstein

Seminar Announcement

Modeling bobcat movement in relationship to land cover classification using artificial neural network

Sun He Bak, STAT-DD-MS Candidate, Colorado State University

Monday, November 8, 2010

10:00 a.m., room 008, Statistics Bldg

ABSTRACT

The study of animal movement in space has become increasingly important given recent trends in landscape change due to housing and urban development. Such study has numerous uses ranging from managing threatened or endangered species to assessing human risk of being encountered by aggressive animals in recently developed areas.  The modeling of animal movement is challenging because of landscape complexity and the multitude of factors affecting animal behavior. In this paper, we apply a new statistical method developed by Jeff Tracey et. al (2010) to analyze bobcat movement data in Southern California and evaluate the need for more extensive analysis in the future.

Advisory Committee:

Dr. Jun Zhu, Advisor

Dr. Myung Hee Lee, Committee Member, Statistics Department, CSU

Dr. Kevin Crooks, Outside Member, Fish, Wildlife & Conservation Biology