Effect of Stochasticity on Optimal Harvesting Strategies in Some Lumped-Parameter Fishery Models

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Abstract
This paper introduces some methods for anticipating the difference between optimal harvesting strategies in a fishery model with stochastic recruitment and in the corresponding deterministic model with recruitment equal to its expected value. It extends known results on the sign of the difference and presents ways to estimate the magnitude. Two classes of lumped-parameter models are discussed. In myopic models, the policy difference is likely to be insignificant. In more general models with downward sloping demand for fish and increasing marginal cost of fishing effort, a heuristic measure is introduced that can suggest the direction and magnitude of the policy shift.

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