A Bayesian State Space Model for Movement of Halibut in the Gulf of Alaska

• Activity Number: 471
• Type: Invited
• Date/Time: Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics and the Environment
• Author(s): Margaret Short* and Andrew Seitz and Julie Nielsen and Ani Mikheeva
• Companies: University of Alaska - Fairbanks and University of Alaska Fairbanks School of Fisheries and Ocean Sciences and University of Alaska Fairbanks School of Fisheries and Ocean Sciences and University of Alaska Institutional Research and Analysis
• Keywords: state space model ; halibut ; Markov chain Monte Carlo ; bathymetry data

Abstract

Popup archival tags are used to study the fall migration of halibut, an important commercial species inhabiting the Gulf of Alaska. Halibut are demersal fish, mainly staying near the ocean floor.  Each tag records maximum daily depth - as well as several other potentially useful pieces of information - which is transmitted via satellite when the tag pops loose at a preprogrammed time.  We use a Bayesian state space model along with a detailed bathymetry map to estimate the path. This method applies to other demersal fish such as cod and pollock.