ASSESSMENT OF INTERACTION BETWEEN NORTH PACIFIC ALBACORE, 

 THUNNUS ALALUNGA , FISHERIES BY USE OF A SIMULATION MODEL 



p. Kleiber and B. BakerI 



ABSTRACT 



Using a simulation model of a typical year in the North Pacific albacore fisheries in the 1970s, we 

 tested for the degree to which the activity of fleets affects the performance of other fleets. The results 

 show that rather drastic (factor of two) changes in the activity of any of the three principal albacore 

 fleets have only a mild effect on the catch of the other fleets. With the overall exploitation rate in the 

 model close to the exploitation rate determined from tagging results (6%), the maximum degree of 

 interaction was a 7.5'7f drop in longline catch resulting from doubling the baitboat effort. The mild 

 degree of interaction was insensitive to exploitation rate up to approximately 10% exploitation, 

 although interaction became more severe at higher levels of exploitation. 



Fishery interaction, the effect of one fishing fleet 

 on another, is a phenomenon of growing concern 

 to those involved in the management and devel- 

 opment of pelagic fisheries. This concern has 

 arisen from the growing awareness that oceanic 

 fishery resources are not unlimited and from the 

 evolution of exclusive economic zones to protect 

 local interests against large international fishing 

 fleets. Assessing the potential for interaction be- 

 tween tuna fisheries in different island countries 

 was one of the principal reasons that the South 

 Pacific Commission conducted the Skipjack Sur- 

 vey and Assessment Programme (Kearney 1983). 

 Workshops on this topic have been held during 

 international tuna fishery meetings, and a Tuna 

 Fisheries Interaction Programme has been pro- 

 posed within the Indo-Pacific Tuna Development 

 and Management Programme. 



Because there is a multiplicity of fleets and na- 

 tions involved in harvesting albacore, Thunnus 

 alalunga , a tuna, in the North Pacific, there is a 

 potential concern about interaction between 

 these fleets. A history of North Pacific alba- 

 core fishing since the 1950s is summarized by 

 Laurs (1983). Three principal fleets have been 

 responsible for the catch: the Japanese baitboat, 

 the Japanese longline, and the United States jig- 

 boat fleets (Fig. 1). In the 1970s these accounted 

 for more than gO'/f (60%, 15%, and 18%, respec- 

 tively) of the total catch. In recent years, 

 Japanese gill net gear has become important, ac- 



'Southwest Fisheries Center La JoUa Laboratory, National 

 Marine Fisheries Service, NOAA, P.O. Box 271, La JoUa, CA 

 92038. 



Manuscript accepted July 1987 



FISHERY BULLETIN: VOL 85. NO 4, 1987 



counting for approximately 20% of the total catch 

 from 1981 through 1983 (Fig. 1). Detailed statis- 

 tics on this emerging fishery are not currently 

 available. 



Among the three principal fleets, the U.S. fleet 

 tends to take the smallest fish, and the longline 

 the largest, but the size distributions in the catch 

 overlap to a large extent (Fig. 2). The geographic 

 distribution of the fleets is indicated in Figure 3, 

 but the overlap is overemphasized because there 

 is seasonal separation in many cases. Neverthe- 

 less, the migratory nature of albacore makes for 

 potentially significant interaction between fleets 

 that are separated in time and space. 



Because there have been no clear trends in 

 catch or in catch per effort (Laurs 1983), it has 

 been assumed that the albacore stocks have not 

 been adversely affected by the fisheries, and such 

 woes as the fishermen have had have not been 

 blamed on poor status of stocks. Therefore there 

 has been little reason for fleets to accuse one 

 another of depleting the stocks and thus little 

 concern about fishery interaction. To verify that 

 sanguine view, we have estimated the degree of 

 interaction between the three principal albacore 

 fisheries in the North Pacific. We defined interac- 

 tion to be the degree to which changes in the 

 activity (effort) of one fleet affect the performance 

 (catch) of another fleet. The magnitude of this 

 kind of interaction cannot be calculated di- 

 rectly from fishery data, nor can controlled, real- 

 life experiments be conducted on the grand scale 

 necessary to address this topic. However, experi- 

 ments conducted on simulation model are feasi- 

 ble. The results of such experiments with an 



703 



