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Precautionary fishery management requires that a distinction be made between target and limit reference points. We present a simple probability framework for deriving a target reference point for the fishing mortality rate (F) or biomass (B) from the corresponding limit reference point. Our framework is a generalization of one devised previously by Caddy and McGarvey (1996). Both methods require an a priori management decision on the allowable probability of exceeding the limit reference point; our method removes a major assumption by accounting for the uncertainty in the limit reference point. We present the theory underlying the method, an algorithm for solution, and examples of its application. The new procedure, like the old, requires an estimate of the implementation uncertainty expected in the following year's management, an estimate that might be obtained by a review of the effectiveness of past management actions. Either method can be implemented easily on a modern desktop computer. Our generalized framework is more complete, and we believe that it has wide applicability in the use of fishery reference points or, for that matter, in other conservation applications that strive for resource sustainability.

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Shertzer, K. W., and Prager, M. H. 2007. Delay in fishery management: diminished yield, longer rebuilding, and increased probability of stock collapse. ICES Journal of Marine Science, 64: 149–159. When a stock is depleted, catch reductions are in order, but typically they are implemented only after considerable delay. Delay occurs because fishery management is political, and stricter management, which involves short-term economic loss, is unpopular. Informed of stock decline, managers often hesitate, perhaps pondering the uncertainty of scientific advice, perhaps hoping that a good year class will render action moot. However, management delay itself can have significant costs, when it exacerbates stock decline. To examine the biological consequences of delay, we simulated a spectrum of fisheries under various degrees of delay in management. Increased delay required larger catch reductions, for more years, to recover benchmark stock status (here, spawning-stock biomass at maximum sustainable yield). Management delay caused stock collapse most often under two conditions: (1) when the stock–recruitment relationship was depensatory, or (2) when catchability, unknown to the assessment, was density-dependent and fishing took juveniles. In contrast, prompt management resulted in quicker recoveries and higher cumulative yields from simulated fisheries. Benefits to stock biomass and fishery yield can be high from implementing management promptly.