Understanding algal bloom microbiome function to improve seafood safety. Current phytoplankton ecological theory is derived primarily from lab cultures, but in nature phytoplankton have unique microbiomes that support their growth and ongoing ocean primary production. This project aims to establish the structure and function of these natural microbiomes, and how they contribute to seafood poisoning caused by bacteria and algal biotoxins. Using advanced flow cytometry with single-cell microbial ....Understanding algal bloom microbiome function to improve seafood safety. Current phytoplankton ecological theory is derived primarily from lab cultures, but in nature phytoplankton have unique microbiomes that support their growth and ongoing ocean primary production. This project aims to establish the structure and function of these natural microbiomes, and how they contribute to seafood poisoning caused by bacteria and algal biotoxins. Using advanced flow cytometry with single-cell microbial profiling, we will sample nano-scale plankton microbiomes and synthetic microbiome phylogenomics to the link between microbiomes and seafood poisoning outbreaks. The outcomes will underpin enhanced predictive modelling of seafood risk to ensure the safety and export security of Australia's $2 billion seafood industry.Read moreRead less
Managing infectious disease through partial wildlife social networks. This project aims to investigate the dynamics of the spread of infectious disease in wildlife, derived from incomplete information about contact networks. Infectious diseases in wildlife are difficult to track and control, because it is not feasible to monitor each individual in a population and know the contact network for a population. The project will create ways to best utilise incomplete observational data of contact netw ....Managing infectious disease through partial wildlife social networks. This project aims to investigate the dynamics of the spread of infectious disease in wildlife, derived from incomplete information about contact networks. Infectious diseases in wildlife are difficult to track and control, because it is not feasible to monitor each individual in a population and know the contact network for a population. The project will create ways to best utilise incomplete observational data of contact networks to develop robust predictions of disease spread and population fate, and to reliably predict the outcomes of management interventions. These robust prediction methods will provide better insights for conservation of Australian wildlife.Read moreRead less