Research article - Peer-reviewed, 2016
Modeling interdependent animal movement in continuous time
Niu, Mu; Blackwell, Paul G.; Skarin, AnnaAbstract
This article presents a new approach to modeling group animal movement in continuous time. The movement of a group of animals is modeled as a multivariate Ornstein Uhlenbeck diffusion process in a high-dimensional space. Each individual of the group is attracted to a leading point which is generally unobserved, and the movement of the leading point is also an Ornstein Uhlenbeck process attracted to an unknown attractor. The Ornstein Uhlenbeck bridge is applied to reconstruct the location of the leading point. All movement parameters are estimated using Markov chain Monte Carlo sampling, specifically a Metropolis Hastings algorithm. We apply the method to a small group of simultaneously tracked reindeer, Rangifer tarandus tarandus, showing that the method detects dependency in movement between individuals.Keywords
Animal movement; Bayesian inference; Multivariate Ornstein Uhlenbeck process; Ornstein Uhlenbeck bridge; Stochastic differential equationPublished in
Biometrics2016, volume: 72, number: 2, pages: 315-324
Publisher: WILEY-BLACKWELL
Authors' information
Niu, Mu
University of Sheffield
Blackwell, Paul G.
University of Sheffield
Swedish University of Agricultural Sciences, Department of Animal Nutrition and Management
UKÄ Subject classification
Computational Mathematics
Behavioral Sciences Biology
Probability Theory and Statistics
Ecology
Publication Identifiers
DOI: https://doi.org/10.1111/biom.12454
URI (permanent link to this page)
https://res.slu.se/id/publ/77053