Model-Based Adaptive Monitoring: Improving the Effectiveness of Reef Monitoring Programs

Project overview

Pubudu Thilan (PhD Candidate)

My PhD research (includes three studies) focuses on developing an innovative adaptive modelling and sampling framework for monitoring coral reefs using new Bayesian computational algorithms. In the first two studies, I worked on the Great Barrier Reef (GBR) data and then in the third study, I am working on the Scott Reef data.

Coral reefs are dynamic ecosystems that support enormous biodiversity. They play a vital role in protecting the coastline from harmful effects of waves and tropical storms, provide habitat to numerous marine organisms and maintain the carbon level in the water. However, some environmental threats such as cyclone have an impact on the health and the long-term resilience of coral reefs. The aim of my PhD project is to use adaptive design methods to determine when and where samples should be collected based on a particular environmental disturbance to quantify its impact.


The adaptive design methods have been shown to be cost effective and yield highly informative data. Thus, these methods should help to improve the effectiveness of reef monitoring programs.

Project team

QUT team members: Pubudu Thilian (PhD Candidate); A/Prof James McGree and Dr Helen Thompson, Dr Julian Carely

External team members: Dr Patricia Menéndez (AIMS and Monash); Dr James Gilmour (AIMS); and Dr Rebecca Fisher (AIMS)