Document Type

Article

Publication Date

2001

Abstract

Setting the yearly allocation for a fished stock is always an uncertain endeavor. Populations suffering significant mortality from disease require particularly careful management. Disease mortality is not a standard component of Fisheries models, however. Here, we develop a model for the management of fished oyster populations in which disease mortality is a controlling influence. The model requires a quantitative estimate of abundance by size class, some knowledge about growth rates to establish the size range recruiting into the fishery, and an estimate of the anticipated natural mortality rate. The latter is of considerable consequence because small changes in mortality rate effect large changes in predicted outcomes. The model permits investigation of scenarios that include a range of allocations, timing of fishing seasons, variation in fishing efforts within seasons to establish a preferred harvest level, variations in the distribution of fishing among beds to minimize overharvesting of disease-affected beds (area management), and rebuilding plans to increase total stock abundance after epizootic mortality or periods of overharvesting. The model is sufficiently general that it can be applied to any commercial shellfish species. Simulations show that appropriate timing of the fishing season with respect to the timing of disease mortality can more than double the yearly allocation to the fishery. Some harvested animals would otherwise have died from disease. Besides disease, the other model parameter that most affects simulation outcome is the abundance of submarket-size oysters that can be expected to recruit to the fishery in the simulated year. Population stability is strongly determined by the number of recruits available to replace the deaths that decimate the market-size population each year. The number of recruits is a function of survivorship in previous years, but also the anticipated growth rate that defines the size range of oysters at the beginning of the fishing year that can be expected to recruit to the fishery. This modeling exercise points to the critical need to understand population dynamics and survival of size classes below market size that are not often the targets of investigatory activities.

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