State-space models provide a powerful way to scale up inference of movement behaviours
from individuals to populations when the inference is made across multiple individuals …

Recent technological advances have permitted the collection of detailed animal location and
ancillary biotelemetry data that facilitate inference about animal movement and associated …

Bayesian state‐space movement models have been proposed as a method of inferring
behavioural states from movement paths (Morales et al. 2004), thereby providing insight into …

Movement ecology has rapidly advanced owing to recent developments of animal-attached
devices and wide applications of sophisticated statistical and machine learning techniques …

It is natural to regard most animal movement as a continuous‐time process, generally
observed at discrete times. Most existing statistical methods for movement data ignore this; …

Remotely sensed tracking data collected on animal movement is vastly underutilized due to
a lack of statistical tools for appropriate analysis. Features of such data that make analysis …

Detailed observation of the movement of individual animals offers the potential to
understand spatial population processes as the ultimate consequence of individual …

Background Characterizing the movement patterns of animals is an important step in
understanding their ecology. Various methods have been developed for classifying animal …

Simulating animal movement in spatially explicit individual-based models (IBMs) is both
challenging and critically important to accurately estimating population dynamics. A number …

Understanding animal movement and resource selection provides important information
about the ecology of the animal, but an animal's movement and behavior are not typically …