A dynamic programming model of fishing strategy choice in a multispecies trawl fishery with trip limits

Dynamic programming was used to model targeting decisions made by bottom trawling vessels in the U.S. west coast groundfish fishery, under management-imposed limits on landings of each target species (trip limits). A model of choice of assemblage (bottom rockfish (Sebastes sp.) versus deepwater Dover sole (Microstomus pacificus) complex) within a fishing trip was parameterized with data from an observer study conducted in 1988 through 1990. The model predicted that the vessel would fish the bottom rockfish strategy exclusively without limits but would switch between strategies several times under restrictive trip limits. That higher limits increased switching was consistent with actual landings from trips made by the same vessels under the same trip limit regimes, although the actual landings were more variable. Different trip limits or different market prices for the limited species changed the predicted decisions. Changing the cost of fishing each strategy, probability of a premature trip ending, tow du...

[1]  Lee G. Anderson,et al.  The Economics of Fisheries Management , 1977 .

[2]  S. Cunningham Fishermen's Incomes and Fisheries Management , 1994, Marine Resource Economics.

[3]  Ellen K. Pikitch,et al.  Numerical Definition of Groundfish Assemblages Caught Off the Coasts of Oregon and Washington Using Commercial Fishing Strategies , 1992 .

[4]  Ray Hilborn,et al.  Fleet Dynamics and Individual Variation: Why Some People Catch More Fish than Others , 1985 .

[5]  D. Lane,et al.  Fisheries management science: the framework to link biological, economic, and social objectives in fisheries management , 1995 .

[6]  J. Wallace,et al.  The statistical design of comparative fishing experiments , 1990 .

[7]  E. K. Pikitch,et al.  Implications of trip regulations for high-grading; a model of the behavior of fishermen , 1995 .

[8]  John Rust Numerical dynamic programming in economics , 1996 .

[9]  Dimitri P. Bertsekas,et al.  Dynamic Programming and Optimal Control, Two Volume Set , 1995 .

[10]  J. Rogers Assemblages of groundfish caught using commercial fishing strategies off the coasts of Oregon and Washington from 1985-1987 , 1994 .

[11]  C. Clark,et al.  Dynamic Modeling in Behavioral Ecology , 2019 .

[12]  Courtland L. Smith,et al.  Attitudes of Trawl Vessel Captains about Work, Resource Use, and Fishery Management , 1993 .

[13]  Daniel E. Lane,et al.  Investment Decision Making by Fishermen , 1988 .

[14]  A. Colman Game Theory and its Applications: In the Social and Biological Sciences , 1995 .

[15]  Price Uncertainty, Expectations Formation and Fishers' Location Choices , 1993, Marine Resource Economics.

[16]  James E. Wilen,et al.  An Examination of Fishing Location Choice in the Pink Shrimp Fishery , 1986, Marine Resource Economics.

[17]  A. Charles Fishery science: the study of fishery systems , 1995 .

[18]  E. K. Pikitch,et al.  Dynamic discarding decisions: foraging theory for high-grading in a trawl fishery , 1995 .

[19]  David B. Sampson Fishing Tactics in a Two-Species Fisheries Model: The Bioeconomics of Bycatch and Discarding , 1994 .

[20]  John Rust Using Randomization to Break the Curse of Dimensionality , 1997 .

[21]  Martin L. Puterman,et al.  Markov Decision Processes: Discrete Stochastic Dynamic Programming , 1994 .

[22]  D. Erickson,et al.  Cod-end mesh size selection for rockfish and flatfish of the US West Coast , 1998 .

[23]  C. Clark,et al.  Uncertainty, search, and information in fisheries , 1983 .

[24]  Randall M. Peterman,et al.  Movement Dynamics in a Fishery: Application of the Ideal Free Distribution to Spatial Allocation of Effort , 1993 .

[25]  Spatial pattern in catch rates: A test of economic theory , 1992 .