Using models to explore copper bioaccumulation in the Sydney Rock Oyster (Saccostrea glomerata) in a large coastal embayment
Russell Geoffrey Richards (2007). Using models to explore copper bioaccumulation in the Sydney Rock Oyster (Saccostrea glomerata) in a large coastal embaymentPhD Thesis, School of Engineering, The University of Queensland.
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This study represents the first known attempt at modelling the uptake and bioaccumulation of copper by the Sydney Rock Oyster (Saccostrea glomerata) using an integrated ecological modelling framework. Oysters have been used to provide time-integrated measurements of contaminants all over the world and pivotal to their effectiveness is the capability of interpreting the relationship between the oyster and its environment. Bioaccumulation models provide a method of achieving this. Current bioaccumulation modelling focuses on using first-order differential equations that incorporate important physiological responses of the organism. However, there is a paucity of field based experiments dedicated to quantifying trace metal kinetics with most models parameterised through laboratory studies using tracer techniques. Such methods may not adequately represent the processes occurring in the natural environment and inherently precludes copper because of the lack of a stable isotope for this metal. Instead, this study employed an integrated ecological modelling framework because it provides a framework for heuristically and holistically exploring copper bioaccumulation in the natural environment. The models consisted of a statistical model, copper speciation model, a biokinetic model and a simple ecosystem model. Oysters were initially collected from along the intertidal zone of Moreton Bay and analysed for copper to provide a rapid assessment of the copper gradient in the bay. Oysters collected from the western shoreline near the Queensland capital city of Brisbane had higher copper concentrations than oysters collected from the sparsely populated eastern shoreline. An existing water quality dataset for Moreton Bay was then assessed using Bayesian regression modelling techniques. This novel statistical modelling technique allowed phytoplankton (as chlorophyll-a) data to be simultaneously assessed for spatial and temporal trends and several informative covariates. This showed the spatial distribution of phytoplankton in the bay correlates wells with the distribution of suspended sediment and is comparable to the pattern of copper concentration observed in the shoreline oysters. This supported the theory that phytoplankton are an important vector of copper bioaccumulation by oysters in the bay. Field experiments were conducted to provide copper uptake and loss kinetics for S.glomerata and to provide important data for the copper speciation and oyster biokinetic models. The copper concentration in oysters deployed at an impacted site increased to 400 µgg-1 over a twelve month period while oysters deployed at a control site remained at around 80 µgg-1. After nine months, oysters were moved from the impacted site to the control site and their copper concentrations subsequently decreased to approximately 80 µgg-1 over five months. The spatial distribution of soft-tissue copper concentrations observed in the deployed oysters was similar to the spatial distribution of chlorophyll-a in the Bayesian modelling and provided further evidence of phytoplankton’s importance as a vector of copper uptake. A copper speciation model was developed to estimate copper concentrations to be used as input for the oyster biokinetic model and the simple ecosystem model. The parameters and constants for the speciation model were compiled from data obtained through the field experimental program and from an extensive and critical review of literature. The speciation model predicted that copper partitions evenly between the dissolved and particulate phases. At both sites (impacted and control), dissolved copper predominantly complexed with dissolved organic matter (DOM) while phytoplankton