Physiological indices as indicators of ecosystem status in shellfish aquaculture sites

The filtration activity of cultured mussels may exert a strong control on phytoplankton populations. Given that phytoplankton constitutes the base of marine food webs, carrying capacity in shellfish aquaculture sites has been commonly studied in terms of phytoplankton depletion. However, spatial and temporal variability of phytoplankton concentration in coastal areas present a methodological constraint for using phytoplankton depletion as an indicator in monitoring programs, and necessitates intensive field campaigns. The main goal of this study is to explore the potential of different bivalve performance indices for use as alternatives to phytoplankton depletion as cost-effective indicators of carrying capacity. For that, a fully spatial hydrodynamic–biogeochemical coupled model of Tracadie Bay, an intensive mussel culture embayment located in Prince of Edward Island (Canada), has been constructed and scenario building has been used to explore the relationship between phytoplankton depletion and bivalve performance. Our underlying premise is that overstocking of bivalves leads to increased competition for food resources, i.e. phytoplankton, which may ultimately have a significant effect on bivalve growth rate and performance. Following this working hypothesis, the relationships among bay-scale phytoplankton depletion and three bivalve physiological indices, one static, condition index, and two dynamic, tissue mass and shell length growth rates, have been simulated. These three metrics present methodological advantages compared to phytoplankton depletion for incorporation into monitoring programs. Although significant correlations among phytoplankton depletion and the three physiological indices have been observed, shell length growth rate is shown as the most sensitive indicator of carrying capacity, followed by tissue mass growth rate and then by condition index. These results demonstrate the potentiality of using bivalve physiological measurements in monitoring programs as indicators of ecosystem status.