Modelling radio-tracking data

Abstract

This paper considers the analysis of locational data collected by sampling the path of an animal as it moves about its home range. In particular, the use of the bivariate Omstein-Uhlenbeck diffusion process as a model of path movement for a single animal, proposed by Dunn and Gipson (1977, Biometrics33, 85–101), is studied when the tracking data are generated from more complex processes. Three distinct cases are investigated. These represent movement patterns that frequently occur in real tracking data. Although Dunn's model is often considered to be inappropriate in such situations, it is shown that the parameter estimates may still be used in a descriptive way to summarize complex animal movement patterns as they contain information on three important aspects of movement: the average location, the dispersion and the correlation between successive radio-locations. Radio-tracking data on a male coyote are used to illustrate a quasi-Newton method for calculating maximum likelihood estimates, and a method for assessing model adequacy. There is found to be a systematic departure from the assumed process, but estimates are interpreted as a summary of the coyote's movement pattern, and non-parameric standard errors are obtained.