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Forecasting the trajectories of Southern Resident Killer Whales with stochastic continuous-time movement models

Teng-Wei Lin

Department of Statistics and Actuarial Science

The Southern Resident Killer Whale (SRKW) is an endangered population of killer whales that is present in the Salish Sea. This fish-eating predator has been heavily impacted by human activities in the region, particularly by commercial vessels in shipping lanes that traverse federally-designated SRKW critical habitat. Forecasting the movement trajectories of these whales would help provide early warning alerts to slow down or reroute commercial vessels, and reduce the risks of ships overlapping with whale presence. In this study, we develop a stochastic animal movement model that is guided by a historical database of sighting records of SRKW. Specifically, we make use of a continuous-time Ornstein-Uhlenbeck (O- U) velocity process that provides the basis for a movement forecast system and simulates realizations of SRKW velocities and trajectories given initial conditions. However, if the forecast system were to simply rely on the O-U velocity process alone, it would steer simulated whale trajectories to areas where SRKWs are rarely found. To address this, we propose a direction blending scheme to project the simulated velocities in more realistic directions. It makes use of historical directional information along with the O-U velocity process to create more probable pathways consistent with observed SRKW movement patterns. By integrating the simulated trajectories generated from the simulated velocities, we establish a dynamic probability-based forecast scheme that demonstrates skill in forecasting SRKW trajectories on a time-scale that aligns with the time to slow and reroute commercial vessels.