Modeling oyster populations. IV: Rates of mortality, population crashes and management

Date

1994

Authors

Powell, E.N.
Klinck, J.M.
Hofmann, E.E.
Ray, S.M.

Journal Title

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Abstract

A time-dependent energy-flow model was used to examine how mortality affects oyster populations over the latitudinal gradient from Galveston Bay, Texas, to Chesapeake Bay, Virginia. Simulations using different mortality rates showed that mortality is required for market-site oysters to be a component of the population's size-frequency distribution; otherwise a population of stunted individuals results. As mortality extends into the juvenile sizes, the population's size frequency shifts toward the larger sizes. In many cases adults increase despite a decrease in overall population abundance. Simulations, in which the timing of mortality varied, showed that oyster populations are more susceptible to population declines when mortality is restricted to the summer months. Much higher rates of winter mortality can be sustained. Comparison of simulations of Galveston Bay and Chesapeake Bay showed that oyster populations are more susceptible to intense population declines at higher latitudes. The association of population declines with disease agents causing summer mortality and the increased frequency of long-term declines at high latitudes result from the basic physiology of the oyster and its population dynamics cycle. Accordingly, management decisions on size limits, seasons and densities triggering early closure must differ across the latitudinal gradient and in populations experiencing different degrees of summer and winter mortality relative to their recruitment rate. More flexible size limits might be an important tool. When fishing is the primary cause of mortality, populations should be managed more conservatively in the summer. The latitudinal gradient in resistance to mortality requires more conservative management at higher latitudes and different management philosophies from those used in the Gulf of Mexico.

Description

p. 347-373

Keywords

oyster population, oyster mortality rates, simulation, oyster recruitment rates, oyster resource management

Citation