Modeling interdependent animal movement in continuous time

• Published in: Biometrics
• Main Authors: Niu, Mu, Blackwell, Paul G., Skarin, Anna
• Other Authors: Engineering and Physical Sciences Research Council
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2016
• Subjects: Applied Mathematics; General Agricultural and Biological Sciences; General Immunology and Microbiology; General Biochemistry, Genetics and Molecular Biology; General Medicine; Statistics and Probability; Hastings; Rangifer tarandus
• Online Access: http://dx.doi.org/10.1111/biom.12454; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fbiom.12454; https://onlinelibrary.wiley.com/doi/pdf/10.1111/biom.12454

Summary 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.