690 



Fishery Bulletin 94(4), 1996 



at least to the extent of investigating the effects of 

 such errors on modeling results. 



One final note. In this paper we have not empha- 

 sized model output beyond biomass traces and basic 

 parameter estimates. For example, annual estimates 

 of fishing mortality rates and exploitation rates were 

 obvious byproducts of the model fits we presented. 

 The models presented here can be thought of as ex- 

 tensions to what we earlier called Stock Reduction 

 Analysis (Kimura and Tagart, 1982; Kimura et al., 

 1984; Kimura 1985, 1988). These papers contain vari- 

 ous methods of analysis that are useful for provid- 

 ing fishery management advice. For example, out- 

 put from both the Kalman filter and nonlinear least- 

 squares models can be treated as a constant recruit- 

 ment model, and target ABC's (allowable biological 

 catches) or target biomass levels can be made on the 

 basis of this assumption. 



Acknowledgments 



This paper was inspired by J. J. Pella's lucid appli- 

 cation of the Kalman filter method (Pella, 1993). We 

 thank J. J. Pella for reviewing the manuscript, and 

 providing numerous corrections, clarifications, and 

 improvements. Also, we thank two anonymous re- 

 viewers for helpful comments and corrections. 



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