IMAGe Seminar - Spatial-Temporal Generalized Linear Modeling of Bark Beetles and Disease in the Rocky Mountain Region

04/24/2012 - 12:00pm
Mesa Laboratory - Damon Room

Kimberly Kaufeld, University of Northern Colorado

Tree mortality due to bark beetles, in particular the mountain pine beetle, is a growing concern in the Rocky Mountains and across the country. As this issue has become more apparent in the last few years, various spatial analysis methods have been used to analyze the spread of the outbreaks of the mountain pine beetle. Zhu et al (2008) used a spatial-temporal autologistic binary model to account for both spatial and temporal dependence on discrete time intervals. It uses a logistic regression to model a response variable on explanatory variables and auto regression on responses from spatial neighborhoods. This research uses an autologistic binary model and a multinomial model to assess multiple damage agents that have occurred in the Rocky Mountain Region. Mortality data obtained from the U.S. Forest Service is used to assess the impacts of multiple damage causing agents, Mountain Pine Beetles, Pine Engravers, Five Needle Pine decline and others damage causing agents that occurred in the Rocky Mountain Region from 2005-2009. A spatial neighborhood structure with various distances was constructed and ordered based upon the adjacency of the initial site. The spatial-temporal autologistic regression model draws samples using Monte Carlo estimation using a Gibbs Sampler to obtain estimates of the model parameters. The multinomial model provides parameter estimation for the spatial, temporal, morality and host tree types, and interacts all factors that have been indicated to impact the various damage agents.

Tuesday April 24, 2012

Mesa Laboratory, Damon Room