© 2001 by ICES/CIEM International Council for the Exploration of the Sea/Conseil International pour l'Exploration de la Mer
Fishing behavior of factory trawlers: a hierarchical model of information processing and decision-making
Alaska Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration 7600 Sand Point Way NE, BINC 15700, Seattle, WA, 98115-0070, USA; email: martin.dorn{at}noaa.gov
This study presents a model of an individual factory trawler conducting fishing operations off the west coast of North America in the Pacific hake (Merluccius productus) fishery. The model is used to explore several concepts that provide new insight into fishing behavior. A central theme of the model is the role of decision-making at different spatio-temporal scales. Decision-making occurs at two scales: (1) choosing an area to fish, and (2) scheduling haul setting and retrievals whilst fishing within an area. These decisions are considered to be state-dependent, with state consisting of both the internal state of the vessel, represented by the amount of fish in holding bins and the amount of fish already in the net, and the external state of the environment, represented by the density of Pacific hake in the area. A novel aspect of the model is a quantitative procedure, based on the Kalman filter, for modeling expert knowledge about local fish densities gained by searching and fishing. Information about local fish density is processed by the fisherman and retained in memory as a symbolic representation, or a "map". Although the spatial structure of the map and the updating procedures are quite simple in the model presented in this paper, the concept is general and can be extended to other kinds of information available to the fisherman about local fish densities. The model is used to characterize the optimal decision rules and to evaluate the usefulness of indices derived from factory trawler catch data to monitor population abundance trends.
Keywords: Pacific hake fishery, factory trawlers, fishing behavior, decision-making, Kalman filter, optimal foraging models
Received 12 February 1999; accepted 11 September 2000.
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