Multi-scale movement of demersal fishes in Alaska

Abstract

Information on the movement of migratory demersal fishes such as Pacific halibut, Pacific cod, and sablefish is needed for management of these valuable fisheries in Alaska, yet available methods such as conventional tagging are too coarse to provide detailed information on migration characteristics. In this dissertation, I present methods for characterizing seasonal and annual demersal fish movement at multiple scales in space and time using electronic archival and acoustic tags. In Chapter 1, acoustic telemetry and the Net Squared Displacement statistic were used to identify and characterize small-scale movement of adult female Pacific halibut during summer foraging in a Marine Protected Area (MPA). The dominant movement pattern was home range behavior at spatial scales of less than 1 km, but a more dispersive behavioral state was also observed. In Chapter 2, Pop-up Satellite Archival Tags (PSATs) and acoustic tags were deployed on adult female Pacific halibut to determine annual movement patterns relative to MPA boundaries. Based on observations of summer home range behavior, high rates of year-round MPA residency, migration timing that largely coincided with winter commercial fisheries closures, and the demonstrated ability of migratory fish to return to previously occupied summer foraging areas, the MPA is likely to be effective for protecting both resident and migrant Pacific halibut brood stock year-round. In Chapter 3, I adapted a Hidden Markov Model (HMM) originally developed for geolocation of Atlantic cod in the North Sea for use on demersal fishes in Alaska, where maximum daily depth is the most informative and reliable geolocation variable. Because depth is considerably more heterogeneous in many regions of Alaska compared to the North Sea, I used simulated trajectories to determine that the degree of bathymetry heterogeneity affected model performance for different combinations of likelihood specification methods and model grid sizes. In Chapter 4, I added a new geolocation variable, geomagnetic data, to the HMM in a small-scale case study. The results suggest that the addition of geomagnetic data could increase model performance over depth alone, but more research is needed to continue validation of the method over larger areas in Alaska. In general, the HMM is a flexible tool for characterizing movement at multiple spatial scales and its use is likely to enrich our knowledge about migratory demersal fish movement in Alaska. The methods developed in this dissertation can provide valuable insights into demersal fish spatial dynamics that will benefit fisheries management activities such as stock delineation, stock assessment, and design of space-time closures.