A Probability Transition Matrix Model for Yield Estimation in Fisheries with Highly Variable Recruitment

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Abstract
This paper addresses the problem of estimating the yield variability that is encountered when managing a fishery that exhibits high recruitment variability. A model is developed that combines elements of a discrete time, age-structured matrix model, a Beverton–Holt continuous time harvest yield model, and a stock–recruitment Markov probability transition matrix model. The model calculates the mean and variance of the stock levels and fishery yields associated with given fishing effort levels, and this type of information can be used to examine the response of the fishery to the implementation of various management strategies. The model is used to contrast the effects of recruitment variability in three fisheries, viz. the South African anchovy (Engraulis capensis) purse-seine fishery, the southern New England yellowtail flounder (Limanda ferruginea) trawl fishery, and the Georges Bank haddock (Melanogrammus aeglefinus) fishery.Key words: stochastic population dynamics, fisheries yield estimation model, variable recruitment, anchovy, yellowtail flounder, haddock