James Thorburn

The paper applies Bayesian inference to large acoustic telemetry datasets to improve movement pattern analysis and residency estimation in aquatic ecosystems.

This paper improves animal movement modeling using particle algorithms to enhance MPA design and conservation efforts for flapper skates.

The paper introduces the patter package for Bayesian state-space modeling of animal tracking data, demonstrating its use in reconstructing movement paths and analyzing space use.

This paper introduces a Bayesian filtering-smoothing algorithm for animal movement modelling in autonomous receiver networks, showing it outperforms heuristic methods in accuracy and flexibility.