Continuous-time correlated random walk model for animal telemetry data.
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 Two previously unpublished marine mammal telemetry data sets were analyzed to illustrate use of the model, by-products available from the analysis, and different modifications which are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.
Johnson
Devin S
DS
National Marine Mammal Laboratory, Alaska Fisheries Science Center, National Marine Fisheries Service, NOAA, 7600 Sand Point Way NE, Seattle, Washington 98115, USA. devin.johnson@noaa.gov
London
Joshua M
JM
Lea
Mary-Anne
MA
Durban
John W
JW
D000818:Animals; D001522:Behavior, Animal / Q000502:physiology*; D017753:Ecosystem; D046069:Fur Seals / Q000502:physiology; D008954:Models, Biological; D046049:Phoca / Q000502:physiology; D013686:Telemetry / Q000662:veterinary*; D013997:Time Factors