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We propose a continuous-time version of the correlated random walk model for animal telemetry data. The continuous-time formulation allows data that have been nonuniformly collected over time to be modeled without subsampling, interpolation, or aggregation to obtain a set of locations uniformly spaced in time. The model is derived from a continuous-time Ornstein-Uhlenbeck velocity process that is integrated to form a location process. The continuous-time model was placed into a state–space framework to allow parameter estimation and location predictions from observed animal locations. Two previously unpublished marine mammal telemetry data sets were analyzed to illustrate use of the model, by-products available from the analysis, and different modifications which are possible. A harbor seal data set was analyzed with a model that incorporates the proportion of each hour spent on land. Also, a northern fur seal pup data set was analyzed with a random drift component to account for directed travel and ocean currents.

Item Type:	Refereed Article
Keywords:	Argos location; Callorhinus ursinus; correlated random walk; harbor seal; integrated stochastic process; kalman filter; marine mammals; northern fur seal; Phoca vitulina; satellite telemetry; state–space model.
Research Division:	Mathematical Sciences
Research Group:	Statistics
Research Field:	Applied statistics
Objective Division:	Environmental Policy, Climate Change and Natural Hazards
Objective Group:	Natural hazards
Objective Field:	Natural hazards not elsewhere classified
UTAS Author:	Lea, MA (Professor Mary-Anne Lea)
ID Code:	52290
Year Published:	2008
Web of Science® Times Cited:	374
Deposited By:	Zoology
Deposited On:	2008-06-16
Last Modified:	2014-11-24
Downloads:	2 View Download Statistics