572 



Fishery Bulletin 90(3). 1992 



passively adaptive strategy which is asymptotically 

 optimal over time (Walters 1987). Most important for 

 the purposes of the present study, though, is the fact 

 that the myopic Bayes solution is computationally much 

 simpler than the actively adaptive solution. 



In conclusion, it should be stressed that while the ap- 

 proach suggested here was developed in the context 

 of a particular model and particular loss and probability 

 density functions, this development was meant primar- 

 ily to illustrate the approach, not to limit it. More 

 sophisticated applications— utilizing alternative as- 

 sumptions, functional forms, and solution techniques- 

 are certainly to be encouraged. In particular, future 

 research might incorporate recruitment stochasticity, 

 positive discount and cost rates, additional objective 

 function components (e.g., yield variability), and uncer- 

 tainty in other parameters and variables (e.g., the 

 natural mortality rate, growth rate, and stock size). 



Acknowledgments 



I would like to thank James Balsiger, Nicholas Bax, 

 Russell Kappenman, Daniel Kimura, Richard Methot, 

 and Thomas Wilderbuer of the Alaska Fisheries Sci- 

 ence Center for reviewing all or portions of this paper 

 in various stages of development. Three anonymous 

 reviewers also provided helpful suggestions. In addi- 

 tion, I would like to thank Robert Burr and Loveday 

 Conquest of the University of Washmgton's Center for 

 Quantitative Science for their assistance. 



Citations 



Bernoulli, D. 



1954 Exposition of a new theory on the measurement of risk. 

 Econometrica 22:23-36. 

 Box, G.E.P., and G.C. Tiao 



1973 Bayesian inference in statistical analysis. Addison-Wes- 

 ley, Reading, MA, 588 p. 

 Charles, A.T. 



1988 In-season fishery management: A Bayesian model. Nat. 

 Resour. Model. 2:599-629. 

 Clark, C.W. 



1985 Bioeconomic modelling and fisheries management. John 

 Wiley, NY, 291 p. 

 Clark, C.W., A.T. Charles, J.R. Beddingrton, and M. Mangel 

 1985 Optimal capacity decisions in a developing fishery. Mar. 

 Resour. Econ. 2:25-53. 

 Cushing, D.H. 



1971 The dependence of recruitment on parent stock in dif- 

 ferent groups of fishes. J. Cons. Cons. Int. Explor. Mer 33: 

 340-362. 

 DeGroot, M.H. 



1970 Optimal statistical decisions. McGraw-Hill, NY, 489 p. 

 Deriso, R.B. 



1985 Risk adverse harvesting strategies. Lect. Notes Bio- 

 math. 61:65-73. 



Getz, W.M., and R.G. Haight 



1989 Population harvesting: Demographic models of fish, 

 forest, and animal resources. Princeton Univ. Press, Prince- 

 ton, 391 p. 



Gleit, A. 



1978 Optimal harvesting in continuous time with stochastic 

 growth. Math. Biosci. 41:111-123. 



Hightower, J.E. 



1990 Multispecies harvesting policies for Washington- 

 Oregon-California rockfish trawl fisheries. Fish. Bull., U.S. 

 88:645-656. 



Hightower, J.E., and G.D. Grossman 



1987 Optimal policies for rehabilitation of overexploited fish 

 stocks using a deterministic model. Can. J. Fish. Aquat. Sci. 

 44:803-810. 



Hightower, J.E., and W.H. Lenarz 



1989 Optimal harvesting policies for the widow rockfish fish- 

 ery. In Edwards, E.F., and B.A. Megrey (eds.), Catch-at-age, 

 bioenergetics, system, and sampling models for microcomputer 

 analyses for fishery dynamics, p. 83-91. Am. Fish. Soc. Symp. 

 6. Bethesda. 



Holloway, C.A. 



1979 Decision making under uncertainty: Models and choices. 

 Prentice-Hall, Englewood Cliffs, NJ, 522 p. 



Hulme, H.R., R.J.H. Beverton, and S.J. Holt 



1947 Population studies in fisheries biology. Nature (Lond.) 

 159:714-715. 

 Kimura, D.K. 



1988 Stock-recruitment curves as used in the stock-reduction 

 analysis model. J. Cons. Cons. Int. Explor. Mer 44:253-258. 



Larkin, P.A. 



1973 Some observations on models of stock and recruitment 

 relationships for fishes. Rapp. P.-V. Reun. Cons. Int. Explor. 

 Mer 164:316-324. 

 Larkin, P.A., and W.E. Ricker 



1964 Further information on sustained yields from fluctuating 

 environments. J. Fish. Res. Board Can. 21:1-7. 

 Lewis, T.R. 



1981 Exploitation of a renewable resource under uncertainty. 

 Can. J. Econ. 14:422-439. 



1982 Stochastic modeling of ocean fisheries resource manage- 

 ment. Univ. Wash. Press, Seattle, 109 p. 



Lord, G.E. 



1973 Characterization of the optimum data acquisition and 

 management of a salmon fishery as a stochastic dynamic pro- 

 gram. Fish. Bull., U.S. 71:1029-1037. 

 1976 Decision theory applied to the simulated data acquisition 

 and management of a salmon fishery. Fish. Bull., U.S. 74: 

 837-846. 

 Ludwig. D., and R. Hilborn 



1983 Adaptive probing strategies for age-structured fish 

 stocks. Can. J. Fish. Aquat. Sci. 40:559-569. 



Ludwig, D., and C.J. Walters 



1981 Measurement errors and uncertainty in parameter esti- 

 mates for stock and recruitment. Can. J. Fish. Aquat. Sci. 

 38:711-720. 



1982 Optimal harvesting with imprecise parameter estimates. 

 Ecol. Model. 14:273-292. 



Mangel, M., and C.W. Clark 



1983 Uncertainty, search, and information in fisheries. J. 

 Cons. Cons. Int. Explor. Mer 41:93-103. 



Mangel, M., and R.E. Plant 



1985 Regulatory mechanisms and information processing in 

 uncertain fisheries. Mar. Resour. Econ. 1:389-418. 



