This report presents results from Wapengo Lake, one of the estuaries selected as part of Stage 1 of the NSW Oyster Industry Transformation Project 2017-2021. To predict the impact of rainfall on potentially pathogenic bacteria, Harmful Algal Blooms (HABs) and oyster disease, precise environmental data with a high temporal frequency were collected and modelled. Combined with state-of-the-art molecular genetic methods, this information will help to improve efficiency and transparency in food safety regulation, provide predictive information and provide insights for more informed and responsive management of shellfish aquaculture.
The project team installed a real-time sensor in the Wapengo Front Lake harvest area, Wapengo Lake, recording high-resolution temperature, salinity and depth data. Oyster farmers collected weekly biological samples (444 environmental DNA samples and 198 deployed/retrieved oysters for growth assessment) from the sensor site. They developed a rapid molecular qPCR (quantitative polymerase chain reaction) assay for E. coli, which could directly compare to the currently used plate count by commercial laboratories. They also developed specific qPCR assays that could determine which animals were contributing to the E. coli load in the river system. Using these assays, the project team observed trends in faecal pollution and modelled these in relation to environmental variables (salinity, temperature, rainfall, nutrients etc.), to develop predictive models. Finally, the team developed an additional model to link oyster growth with environmental variables and assessed its predictive capability.