Research Publications: UM-SG-RS-2007-18
A framework for developing "ecological carrying capacity" mathematical models for bivalve mollusc aquaculture.
Source:Bulletin of Fisheries Research Agency 19:41-51
Aquacultural production of suspension-feeding bivalve molluscs can profit from information on the stocking density at which commercially valuable meat production is maximized. Predicting these stocking densities in the natural environment is difficult a priori because of the complex interacting effects of environmental variables on bivalve growth (e.g., food availability varies with rates of phytoplankton production, water currents affect "food flux" to the bivalves, etc.) In an effort to integrate the influence of environmental variables on bivalve growth a number of mathematical "carrying capacity" models have been developed that estimate the standing stock at which commercial harvests are maximized. This emphasis means that other important aspects of ecosystem carrying capacity, such as the ability of the culture site to process the excrement produced by the animals, may not be adequately modeled. I recommend that an open source- code community model be developed to assess "ecological carrying capacity" for bivalve aquaculture. The overall objective should be to develop a well-parameterized model that will allow a comprehensive assessment of the major interactions between cultivated bivalves and the ecosystem. For example, in addition to predicting tissue production, this model can be used to assess the ability of suspension-feeding bivalves to exert top-down control on phytoplankton stocks, reduce turbidity, enhance nutrient removal, and provide habitat for other organisms. These secondary benefits can have economic value to the aquaculturists as part of polyculture systems, environmental remediation, and nutrient trading schemes. By modeling major aspects of ecosystem function, such as competition for food with other suspension feeding organisms, rates and location of biodeposition etc., models can be used to predict and possibly minimize potential adverse effects of bivalve aquaculture.
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